**Quantum Dots for Pharmaceutical and Biomedical Analysis**

Hayriye Eda Şatana Kara and Nusret Ertaş

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.70034

#### **Abstract**

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[26] Marian E, Jurca T, Simon V, Banica F, Cavalu S. Spectroscopic behaviour of copper complexes of tolbutamine. Studia Universitatis Babes-Bolyai Physica. 2004;**69**(2):71–75. [27] Marian E, Jurca T, Simon V, Vicas L, Bănică F, IR and EPR investigation of copper com-

[28] Jurca T, Cavalu S, Cinta-Panzaru S, Simon V. Synthesis and spectroscopic characterisation of guanfacine with transition metals. In: The 10th European Conference on the Spectroscopy of Biological Molecules; 30.08–4.09; Szeged, Hungary; 2003. Book of

plexes of tolbutamide. Timişoara Medical Journal. 2005;**55**(5):130–132.

Târgu-Mureş. 2004;**50**(2):171–175.

142 Spectroscopic Analyses - Developments and Applications

Abstracts, p. 116. ISBN: 963-482-614-8.

Quantum dots (QDs) are luminescent semiconductor nanocrystals that have extraordinary luminescence emission properties. Their semiconductor properties are different from bulk material because of the quantum confinement effects. These properties allow the use of QDs as a luminescent probe for pharmaceutical and biomedical analysis. Herein, we want to mention the synthesis, surface modification, characterization, and application of QDs. The aim of this chapter is to compile and discuss the advantages and disadvantages of QDs and their usage areas.

**Keywords:** quantum dots, luminescence, fluorescence, chemiluminescence, phosphorescence, pharmaceutics

#### **1. Introduction**

The semiconductor nanoparticles known as quantum dots (QDs) are one of the most relevant developments in the nanotechnology area. Therefore, they are finding new important fields of application in pharmaceutical, biomedical, and food analysis and biomonitoring. QDs are zero-dimensional materials composed of II–VI groups (e.g., CdSe, CdTe, CdS, and ZnS) or III–V elements (e.g., InAs) [1–4]. Colloidal semiconducting QDs have spherical shape, and their radii are in between 2 and 10 nm in diameter, which is less than or equal to the excitation Bohr radius [5–8]. A decrease in the crystal size causes emission at longer wavelength due to increase of the Stokes shift. At such small sizes, these nanoparticles behave differently from the bulk form because of quantum confinement effect, which is responsible for the optoelectronic properties of QDs such as narrow spectral band and high quantum yield (QY).

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

In the last decades, QDs have gained great interests as luminescent probes for the determination of pharmaceuticals [9–12] in different sample matrices, *in vitro* bioimaging [13–18] and *in vivo* applications [19–21], as well as computing, light-emitting devices, and photodetector devices. Because of their unique optical properties, including good optical properties, stability against photobleaching and chemical reaction, broad excitation bands, sharp and symmetric emission bands, size control luminescence, as well as high photoluminescence QY, QDs are used as an alternative to organic and inorganic fluorophores [22–24].

QDs can be modified by different molecules such as polymers and biomolecules in order to make them water soluble and biocompatible. Modification of QDs with biomolecules (e.g., DNA, enzyme, antibody, antigen) [25–27] and metal ions [28–31] has formed an important field of sensor applications [32–34] for the analysis of ions [35–38], biomacromolecules, pharmaceuticals, and small molecules [12, 39–41]. In addition, the surface modification of QDs can increase their luminescent QYs, prevent them from chemical instability and aggregation, and give a special feature to interact with target molecules.

#### **2. Structural and optical properties**

#### **2.1. Structural properties**

Generally, QDs are composed of core, shell, and surface-coating parts, which gain high photoluminescence QY, surface activation, and stability to chemicals and photons [42, 43]. The core is composed of few monolayers of a semiconductor material, i.e., CdSe, CdTe, fluorescence emission, as well as excitation wavelengths, depends on the composition of the core. Shell part surrounds and stabilizes the core. Shell is also effective on the fluorescence QY, decay kinetics, and photostability of QDs. The organic capping determines its stability, biological functionality, and solubility [44]. Coating part at initially prepared QDs is hydrophobic, whereas nowadays hydrophilic polymers or molecules are used. These amphiphilic polymers increase the water solubility of QDs and allow incorporating ionizable functional groups. Both shell and capping are covered to the particle surface and optimize these characters. Typical QDs are core or core-shell structures. The passivation shell is chemical coating, and coated nanoparticles are called core-shell systems. Core (for example, CdTe) or core-shell (for example, CdSe/ZnS and CdTe/CdS) QDs are functionalized with different coatings. In core-shell system, the band gap of the shell is higher than the band gap of core [45–50]. Additionally, a slight red shift in absorption and emission is observed because of tunneling of charge carriers into the shell.

#### **2.2. Characterization**

Definition of size, structure, and shape of synthesized QDs is important. The characterization of QDs is evaluated by high-resolution transmission electron microscopy (HR-TEM), scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray fluorescence (XRF), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR) methods. The size of QDs is generally detected by TEM and SEM [3, 51–53]. In addition to these methods, Brus equation is also used to calculate the diameter of QDs [39]. The optical characterization is made by UV-visible (UV-vis), fluorescence, Raman, and nuclear magnetic resonance spectroscopy (NMR) [54, 55].

#### **2.3. Optical properties of QDs**

In the last decades, QDs have gained great interests as luminescent probes for the determination of pharmaceuticals [9–12] in different sample matrices, *in vitro* bioimaging [13–18] and *in vivo* applications [19–21], as well as computing, light-emitting devices, and photodetector devices. Because of their unique optical properties, including good optical properties, stability against photobleaching and chemical reaction, broad excitation bands, sharp and symmetric emission bands, size control luminescence, as well as high photoluminescence QY, QDs

QDs can be modified by different molecules such as polymers and biomolecules in order to make them water soluble and biocompatible. Modification of QDs with biomolecules (e.g., DNA, enzyme, antibody, antigen) [25–27] and metal ions [28–31] has formed an important field of sensor applications [32–34] for the analysis of ions [35–38], biomacromolecules, pharmaceuticals, and small molecules [12, 39–41]. In addition, the surface modification of QDs can increase their luminescent QYs, prevent them from chemical instability and aggregation, and

Generally, QDs are composed of core, shell, and surface-coating parts, which gain high photoluminescence QY, surface activation, and stability to chemicals and photons [42, 43]. The core is composed of few monolayers of a semiconductor material, i.e., CdSe, CdTe, fluorescence emission, as well as excitation wavelengths, depends on the composition of the core. Shell part surrounds and stabilizes the core. Shell is also effective on the fluorescence QY, decay kinetics, and photostability of QDs. The organic capping determines its stability, biological functionality, and solubility [44]. Coating part at initially prepared QDs is hydrophobic, whereas nowadays hydrophilic polymers or molecules are used. These amphiphilic polymers increase the water solubility of QDs and allow incorporating ionizable functional groups. Both shell and capping are covered to the particle surface and optimize these characters. Typical QDs are core or core-shell structures. The passivation shell is chemical coating, and coated nanoparticles are called core-shell systems. Core (for example, CdTe) or core-shell (for example, CdSe/ZnS and CdTe/CdS) QDs are functionalized with different coatings. In core-shell system, the band gap of the shell is higher than the band gap of core [45–50]. Additionally, a slight red shift in absorption and emission is observed because of tunneling of charge carriers into the shell.

Definition of size, structure, and shape of synthesized QDs is important. The characterization of QDs is evaluated by high-resolution transmission electron microscopy (HR-TEM), scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray fluorescence (XRF), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR) methods. The size of QDs is generally detected by TEM and SEM [3, 51–53]. In addition to these methods, Brus equation is also used to calculate the diameter of QDs [39]. The optical characterization

are used as an alternative to organic and inorganic fluorophores [22–24].

give a special feature to interact with target molecules.

**2. Structural and optical properties**

144 Spectroscopic Analyses - Developments and Applications

**2.1. Structural properties**

**2.2. Characterization**

Although QDs are composed of semiconductor materials, their small size results in spectroscopic properties that are radically different from bulk forms. The electron of the valence band moves to conductance band when QDs absorb the photon. Absorption occurs as long as the energy of photon is higher than the bandgap energy of QDs; thus, excitons can be created with a wide range of energies within the core. The higher energy excitons relax to the lowest bandgap energy before emitting a photon. Therefore, excitation spectrum is broad, whereas the emission spectrum is narrow (**Figure 1**).

QDs are artificial atoms with typical dimensions ranging from 2 to 10 nm. QDs can be designed to have different emission wavelength by adjusting their size (**Figure 2**). The emission is adjusted by the particle diameter in the visible area and by particle composition in the longer wavelength. As diameter of QDs gets bigger, red shift is observed in the emitted light [56, 57]. The properties of QDs are changed by constructing the properties of the electron and hole. The electrons and holes of QDs also present discrete energy levels. As nanoparticles size get smaller, the band gap will be larger, and energy difference between the highest valence band and the lowest conduction band will be increased. As a result, the high energy is required to excite the dots, and therefore, more energy is emitted when nanoparticles return to ground state.

QDs have broad absorption band and a narrow symmetrical emission band; therefore, overlap with other emission colors is minimal. The wavelengths of absorption and emission are tunable by particle size as mentioned before. The broad absorption bands allow selection of the excitation wavelength, and consequently, excitation and emission wavelengths can be separated [48, 58–61]. Physicochemical and optical properties of QDs are summarized in **Table 1**.

**Figure 1.** Excitation (dot line) and emission (line) spectra of MPA-capped CdTe QDs.

**Figure 2.** Photoluminescence spectra of the QDs by changing the size of the particle.


**Table 1.** Properties of QDs.

#### **2.4. Synthesis and surface chemistry**

**Figure 2.** Photoluminescence spectra of the QDs by changing the size of the particle.

Thermal stability High, depends on shell

Chemical stability More resistant to degradation

Brightness 10–20 times more than organic dyes

Photostability High, stable fluorophores due to their inorganic

Absorption spectra Broader absorption spectra enables selection of excitation

Emission spectra A narrow (30–90 nm), symmetric, sharply defined

Lifetime Longer lifetime helps to eliminate background signal Excitation by single or multiple sources Ideal for the same source and multicolor experiments

composition

wavelength

–10<sup>6</sup>

emission peak

M−1 cm−1

**Property Quantum dots** Size 2–10 nm

146 Spectroscopic Analyses - Developments and Applications

Molar absorption coefficient 105

Quantum yield 0.1–0.8

Stokes shift Large stokes shift

Sensitivity High S/N ratio

Applicability to single-molecule analysis Good

**Table 1.** Properties of QDs.

Solubility Depends on surface modification

Bioimaging Better contrast with electron microscope

Synthesis step of semiconductor nanocrystals plays a critical role. The solvent selection is crucial because this step is not only controlling nanocrystal size but also changing their polarity, solubility in aqueous or organic medium, functionality, and applicability. QDs can be synthesized in the organic or aqueous medium. When compared to organic way, water-based QDs synthesis is less toxic, useful for biological applications, and cheaper.

In order to prepare QDs, different types of materials and methods have been reported. In these methods, colloidal synthesis is commonly used technique for the preparation of QDs. During early 1990s, Murray et al. [62] first reported the synthesis for highly monodisperse, size-tunable QDs. In this method, trioctylphosphine (TOP) and trioctylphosphine oxide (TOPO) are used for the synthetic approach for II–VI QDs such as CdSe, CdS, and CdTe. Highly luminescent Cd-E (E = Se/Te/S) nanocrystals were synthesized by using dimethylcadmium (Cd(CH<sup>3</sup> )2 ) as QDs precursors in the coordinating solvent (TOPO) at high temperature (300°C). However, nowadays, cadmium oxide (CdO) is used instead of dimethylcadmium due to its toxicity. The commonly used method for synthesis of colloidal nanocrystal is based on core growth process, starting from organometallic precursor in a mixed solvent including organic surfactants and coordinating solvents. Briefly, reaction medium is heated to high temperature, and precursors are injected while solution stirring. At this step, precursors transform into monomers. As the process continues, nanocrystal growth starts with a nucleation process, and the color of solutions changes from yellow to red. Coordinating solvent caps the nanocrystal surface and stabilizes its surface, moreover, changes its solubility in organic and aqua media and prevents aggregation. Organic surfactants are used to avoid aggregation and give water soluble character [4, 63–66]. At nanocrystal-growth process, not only solvent but also temperature, pH, and growth time are important. Generally, when the heated and unheated forms of QDs are compared, heated QDs show emission, whereas unheated QDs do not have an emission band. Minor variations in pH values affect the diameter of nanocrystals.

Coordinating solvents can be hydrophobic or hydrophilic. Hydrophobic coatings are not suitable for aqueous assay especially biological analysis; therefore, hydrophilic capping agent must be introduced for this purpose. Various approaches have been developed to make water soluble. The hydrophobic layer can be changed with acidic and hydrophilic groups. Hydrophobic part reacts with the hydrophobic surface of QDs, whereas the hydrophilic part on the outer end will give water soluble character. The stability of water dispersed QDs is generally achieved by using charged organic molecules or polymers such as mercaptopropionic acid (MPA), mercaptoacetic acid (MAA), mercaptosuccinic acid (MSA), and cysteine [67–69].

Doping of QDs with transition-metal ions such as Mn2+ and Cu2+ has been widely studied to enrich the features of nanocrystals. These advantages include stability, large Stokes shift, and longer emission lifetime which allow phosphorescent measurement [70–72]. In these doped QDs, Mn-doped ZnS which have orange-yellow emission is widely used as a phosphorescent probe for analysis of different kinds of analytes [73–75]. The purification step is needed to remove unreacted precursors and other chemicals. A widely used method for this purpose is precipitation of QDs in methanol or ethanol and centrifugation.

Additionally, lithography [76, 77], epitaxy [76, 78], electrochemical assembly [79–81], plasma synthesis [82–86], biological synthesis [87, 88], gamma-irradiation [89–91], and microwaveassisted synthesis [92, 93] ways are also used for the synthesis of QDs.

#### **3. Applications of QDs**

Surface properties of QDs affect the luminescence character. The chemical or physical interaction of analytes and QDs can influence the optical properties of the QDs. Depending on this change, QDs have been widely applied to detect different kinds of analytes including ions, pharmaceuticals, small molecules, and biological macromolecules. In these analytes, direct analysis of pharmaceutical and biological samples is difficult due to interference molecules. However, chemical surface modifications of QDs with functional groups or biomolecules enhance the selectivity and favorable luminescence features. Most of the detection methods are based on the fluorescence properties of these QDs. Besides, in recent years, increasing number of work on making use of the inherent phosphorescent properties of QDs is in the literatures. In most QDs applications, the detection is based on quenching of luminescence signal, while new methods are developed on signal enhancing.

#### **3.1. Fluorescence-based measurements**

The luminescence properties of QDs are used for qualitative or quantitative analysis of different kinds of analytes. Initial studies are generally based on measuring the enhancement or quenching of luminescence signal of QDs resulting from the interaction of the QDs and the analyte. This surface interaction generally is not specific and allows interacting with simple and small molecules. Nonspecifically binding is a major problem especially in biomedical applications due to the interaction of a variety of biomolecules and structures including nucleic acids, proteins, or matrix compounds. In order to increase selectivity, conjugation of QDs with polymers, antibodies, amino acids, and proteins has been proposed and applied [94, 95].

In a pioneering work, Cd-based QDs have been reported for optical sensing of small molecules and ions. Many studies in this field, focusing on interactions between QDs and analyte, showed that the luminescence response was affected by the surface capping ligands. For example, the addition of Cd ions to a basic solution, including CdS nanoparticle, has caused increasing the luminescence QY of the nanoparticle. This effect was attributed to the formation of a Cd(OH)<sup>2</sup> shell on the CdS core which eliminates the nonradiative pathways. Furthermore, addition of Zn2+ and Cd2+ ions to basic CdS or ZnS colloidal solutions caused similar photoluminescence-activation effect [96–98]. In addition, organic capping agents such as mercapto acids and mercaptoamines have been used for the modification of QDs surface [99]. Modification strategies are based on not only intensity enhancing but also quenching and emission wavelength shifting. Quenching mechanism depends on the interaction of quencher and nanoparticle and includes different deactivation pathways such as electrotransfer process, nonradiative pathways, inner-filter effect, and complex formation. Quenching occurs by two different mechanisms called dynamic (collisional) and static quenching. In dynamic quenching, the quencher and fluorophore come into contact during the lifetime of the excited state, and the fluorophore returns to the ground state without emission. In static quenching, fluorophore and quencher form a nonfluorescent complex at the ground state. These quenching systems can be differentiated by their different dependence on temperature and viscosity. At higher temperatures, dynamic quenching increases due to faster diffusion. On the contrary, in the static quenching, dissociation of weakly bound complexes causes decreasing of quenching. In some cases, the fluorophore can be quenched by collisions and complex formation with the same quencher at the same time [100].

Additionally, lithography [76, 77], epitaxy [76, 78], electrochemical assembly [79–81], plasma synthesis [82–86], biological synthesis [87, 88], gamma-irradiation [89–91], and microwave-

Surface properties of QDs affect the luminescence character. The chemical or physical interaction of analytes and QDs can influence the optical properties of the QDs. Depending on this change, QDs have been widely applied to detect different kinds of analytes including ions, pharmaceuticals, small molecules, and biological macromolecules. In these analytes, direct analysis of pharmaceutical and biological samples is difficult due to interference molecules. However, chemical surface modifications of QDs with functional groups or biomolecules enhance the selectivity and favorable luminescence features. Most of the detection methods are based on the fluorescence properties of these QDs. Besides, in recent years, increasing number of work on making use of the inherent phosphorescent properties of QDs is in the literatures. In most QDs applications, the detection is based on quenching of luminescence

The luminescence properties of QDs are used for qualitative or quantitative analysis of different kinds of analytes. Initial studies are generally based on measuring the enhancement or quenching of luminescence signal of QDs resulting from the interaction of the QDs and the analyte. This surface interaction generally is not specific and allows interacting with simple and small molecules. Nonspecifically binding is a major problem especially in biomedical applications due to the interaction of a variety of biomolecules and structures including nucleic acids, proteins, or matrix compounds. In order to increase selectivity, conjugation of QDs with polymers, antibodies, amino acids, and proteins has been proposed and applied

In a pioneering work, Cd-based QDs have been reported for optical sensing of small molecules and ions. Many studies in this field, focusing on interactions between QDs and analyte, showed that the luminescence response was affected by the surface capping ligands. For example, the addition of Cd ions to a basic solution, including CdS nanoparticle, has caused increasing the luminescence QY of the nanoparticle. This effect was attributed to the

Furthermore, addition of Zn2+ and Cd2+ ions to basic CdS or ZnS colloidal solutions caused similar photoluminescence-activation effect [96–98]. In addition, organic capping agents such as mercapto acids and mercaptoamines have been used for the modification of QDs surface [99]. Modification strategies are based on not only intensity enhancing but also quenching and emission wavelength shifting. Quenching mechanism depends on the interaction of quencher and nanoparticle and includes different deactivation pathways such as electrotransfer process, nonradiative pathways, inner-filter effect, and complex formation. Quenching occurs by two

shell on the CdS core which eliminates the nonradiative pathways.

assisted synthesis [92, 93] ways are also used for the synthesis of QDs.

signal, while new methods are developed on signal enhancing.

**3.1. Fluorescence-based measurements**

[94, 95].

formation of a Cd(OH)<sup>2</sup>

**3. Applications of QDs**

148 Spectroscopic Analyses - Developments and Applications

Literature survey shows that a great number of fluorescence methods have been developed for analysis of pharmaceuticals and biomolecules (**Table 2**). These methods are generally based on quenching of fluorescence intensity of QDs (**Figure 3**). Thioglycolic acid (TGA)–modified water-soluble CdSe QDs were synthesized and used for determination of paraoxon, which is acetylcholinesterase inhibitor. In this study, multilayers of chitosan, TGA-capped CdSe QDs, and organophosphorus hydrolase polyelectrolytes were incorporated into layer-by-layer architecture. The size of the nanoparticles was determined by HR-TEM and found 3.4 nm. The presence of paraoxon in the sample solution caused decreasing fluorescence emission of QDs, attributed to an interaction of the analyte with QDs and to change surface conformation [101].


**Table 2.** QD-based fluorescent probes for determination of pharmaceuticals.

**Figure 3.** The general aspect of fluorescence spectra of QDs at different concentration of quencher. The inset is the calibration curve of *F*<sup>0</sup> /*F* versus the concentration of quencher.

Yu et al. have developed a fluorescence switch sensor consisting of Mn-doped CdTe QDsmethyl viologen (MV2+) nanohybrids to analyze bioactive peptide glutathione (GSH). Characterization of QDs was performed by TEM, XRD, and FT-IR methods. The results obtained from these studies showed that prepared QDs were monodisperse and have spherical shape with sizes 20 nm and hexagonal crystalline structure. In addition, TGA molecules and QDs conjugated successfully. In the sensor, MV2+ has two quaternary ammonium groups which link TGA on the surface of QDs through electrostatic interaction. Because of the electron transfer between QDs and quencher, the fluorescence signal is quenched. As the addition of GSH, the peptide can effectively replace TGA ligands on the surface of QDs, and fluorescence intensity is again recovered. Fluorescence recovery level of QDs is depended to the amount of GSH [102].

Synthesized by sonochemical technique, TGA-capped CdTe is used as a fluorescent probe for determination of doxycycline (DC), a member of tetracycline antibiotics, in honey and human serum. Prepared QDs were identified by FT-IR. In here, the peak related to SH group of TGA was not observed in the spectrum of TGA-QDs hybrids due to interaction between thiol and CdTe QDs. Furthermore, the TEM images showed that size distribution and shape were 4–6 nm and spherical, respectively. Similar to previous studies, the fluorescence intensity of QDs was quenched by adding of DC. To identify the mechanism of quenching process, Stern-Volmer equation has been plotted at a different temperature. Obtained results showed that the quenching mechanism was dynamic [103].

l-Cysteine is also widely used surface modification agent which gives hydrophilic character to QDs. l-Cysteine–coated CdS QDs have prepared, characterized, and used to analyze ceftriaxone (CFX) in biological samples [104]. Optical characterization was identified by fluorimetry and UV-vis spectrometry. QDs have a broad absorption band in pH 7 buffer solution. Moreover, symmetric and narrow emission peak was at around 556 nm with excitation wavelength 359 nm. Recorded FT-IR spectra indicated that characteristic S-H band was absent in the l-cysteine–capped QDs. Also, the band at 3175 cm−1 belongs to CFX was not seen in the spectrum of l-cysteine/QDs/CFX complex. Prepared and characterized QDs were used in determination of CFX in urine. The effects of reaction time, temperature, and pH were identified, and 10 min, 25°C, and pH 7 were selected as optimum conditions.

Liang et al. have developed a method based on the quenching of the fluorescence of CdSe QDs by spironolactone in organic media. CdSe QDs were prepared from CdO as a precursor and stearic acid. After heating step under Ar flow, trioctylphosphine oxide and hexadecylamine were added, heated again at high temperature, and Se solution was injected. Obtained dried nanoparticles were redispersed in hexane. The emission spectra of QDs were recorded after titration with spironolactone [105].

Core-shell nanoparticles were also used for sparfloxacin in tablets. Water-soluble CdSe/ CdS QDs modified with TGA have been synthesized and acted as a fluorescent probe. Hyperchromicity and forming of new absorption band were observed when the spectra of CdS and CdSe/CdS QDs were compared. This result indicated that CdS coated the surface of CdSe. After optimization of working conditions, TGA-capped CdSe/CdS QDs was used for the determination of sparfloxacin. Quenching mechanism was found static according to results of Stern-Volmer equation [106].

Yu et al. have developed a fluorescence switch sensor consisting of Mn-doped CdTe QDsmethyl viologen (MV2+) nanohybrids to analyze bioactive peptide glutathione (GSH). Characterization of QDs was performed by TEM, XRD, and FT-IR methods. The results obtained from these studies showed that prepared QDs were monodisperse and have spherical shape with sizes 20 nm and hexagonal crystalline structure. In addition, TGA molecules and QDs conjugated successfully. In the sensor, MV2+ has two quaternary ammonium groups which link TGA on the surface of QDs through electrostatic interaction. Because of the electron transfer between QDs and quencher, the fluorescence signal is quenched. As the addition of GSH, the peptide can effectively replace TGA ligands on the surface of QDs, and fluorescence intensity is again recovered. Fluorescence recovery level of QDs is depended to the

**Figure 3.** The general aspect of fluorescence spectra of QDs at different concentration of quencher. The inset is the

/*F* versus the concentration of quencher.

Synthesized by sonochemical technique, TGA-capped CdTe is used as a fluorescent probe for determination of doxycycline (DC), a member of tetracycline antibiotics, in honey and human serum. Prepared QDs were identified by FT-IR. In here, the peak related to SH group of TGA was not observed in the spectrum of TGA-QDs hybrids due to interaction between thiol and CdTe QDs. Furthermore, the TEM images showed that size distribution and shape were 4–6 nm and spherical, respectively. Similar to previous studies, the fluorescence intensity of QDs was quenched by adding of DC. To identify the mechanism of quenching process,

amount of GSH [102].

calibration curve of *F*<sup>0</sup>

150 Spectroscopic Analyses - Developments and Applications

Besides these applications, fluorescence enhancement method has been developed for the determination of pharmaceuticals. Pawar et al. has used MPA-modified CdS nanoparticles as a turn-on probe to determine penicillamine. The obtained results showed that QDs aggregated after addition of the drug, the average size of QDs increased, and the fluorescence intensity of QDs was enhanced due to the interaction between QDs and penicillamine [107].

Nowadays, innovations and applications related to QDs are continuously increased. One of these is the using of QDs in automated systems. Rifampicin and rifaximin, which are complex macrocyclic antibiotics, have been analyzed by automated QDs-based analytical method using flow system. The automated flow system allows repeatable handling solutions, automation, miniaturization, lower reagent consumption, and waste. In this method, in the initial status, carrier (Na2 CO<sup>3</sup> /NaHCO<sup>3</sup> buffer solution) flowed through the flow cell, and then valves of sample solutions and QDs were switched on. The analytical signal of QDs-sample mixture was recorded. A blank signal which is only QDs signal was also recorded before any sample analysis [108].

Most inorganic QDs such as CdX nanoparticles consist of highly toxic heavy metal ions, and this could be a major concern for *in-vivo* applications. Therefore, novel fluorescence carbon-based nanoparticles have found wide using area in this field. They have some advantages over traditional QDs, for example, free of heavy metal ions, low toxicity, and excellent biocompatibility [10, 109]. Due to their small molecular mass, carbon nanoparticles easily enter the living cell and allow *in-vivo* monitoring [110]. Huang et al. have developed a sensitive method for the determination of ceftazidime and cefepime in their pharmaceutical forms based on fluorescence quenching of poly(ethylene glycol) (PEG) 2000-capped carbon QDs. The chemical oxidation method was used for preparation of nanocrystals. In this method, sawdust as a carbon source and nitric acid were mixed and heated. Then, pH of the solution was adjusted to neutral by adding NaOH and centrifuged. In the last step, for surface modification, PEG 2000 was added and heated in a microwave oven. Obtained carbon nanoparticles were characterized by TEM, and size of them was found in between 5 and 8 nm. Developed QDs were used for determination of drugs and method was sensitive, selective, and with high recovery value [10].

Functionalized semiconductor QDs have been used as fluorescence labels for biological detection and imaging. For example, avidin, highly positively charged tetramer, and functionalized CdSe/ZnS QDs were used in the detection of biotin [111]. Similarly, different sizes CdSe/ZnS QDs conjugated with different antibodies have been applied for simultaneous detection of four toxins (Shiga-like toxin 1, staphylococcal enterotoxin B, cholera toxin, and ricin) [112]. In another example, determination of 17β-estradiol has been done by using biotin-labeled antirabbit IgG and streptavidin conjugated by QDs [113]. As mentioned above, carbon-based QDs have low toxicity and biocompatibility. Li et al. have developed glucose sensor based on combining electrostatic attraction between anionic fluorescent carbon QDs that bear polar carboxy and hydroxy groups and cationic boronic acid–substituted bipyridinium salt. The interaction between them results in the formation of a ground state complex leading to a decrease in the fluorescence intensity. When glucose is added to the medium, the tetrahedral anionic glucoboranate esters are formed which effectively neutralize the net charge of the cationic bipyridinium and recover the fluorescence intensity of QDs [114].

#### **3.2. Fluorescence resonance energy transfer (FRET)**

Fluorescence resonance energy transfer (FRET) is a powerful technique describing energy transfer between two light-sensitive molecules. In here, an exited donor chromophore group transfers energy to an acceptor chromophore through the nonradiative coupling. The efficiency of this energy transfer depends on the distance between both fluorophores, inversely proportional to the sixth power of the distance between acceptor and donor; therefore, FRET is more sensitive to small changes in distance [115, 116]. Photoemission properties and high QY of QDs allow efficient energy transfer when compared with the organic dyes. In addition, distinguishing the emission of the donor from acceptor is much easier due to narrow and symmetric emission spectrum of QDs. This technique is a useful tool to analyze biomolecules such as proteins and DNA. For this purpose, a FRET-based bioassay was developed by using QDs (donor) functionalized with a label (i.e., protein, antibody) which recognizes and binds to target. When FRET process occurs, the bioconjugate captures the dye-labeled analog (acceptor), and fluorescence quenching takes place. In addition of target molecule to the medium, analyte competes with its analog and binds to the label. The acceptor is displaced from QD surface; thus, fluorescence enhancement is observed. Besides, different approaches have been developed toward the use of QDs in FRET assays, such as analyte displaces fluorescent ligands, analyte cleaves donor-acceptor linkage, analyte changes the conformation of acceptor-donor linkage, and analyte mediates donor-acceptor binding [117].

carbon-based nanoparticles have found wide using area in this field. They have some advantages over traditional QDs, for example, free of heavy metal ions, low toxicity, and excellent biocompatibility [10, 109]. Due to their small molecular mass, carbon nanoparticles easily enter the living cell and allow *in-vivo* monitoring [110]. Huang et al. have developed a sensitive method for the determination of ceftazidime and cefepime in their pharmaceutical forms based on fluorescence quenching of poly(ethylene glycol) (PEG) 2000-capped carbon QDs. The chemical oxidation method was used for preparation of nanocrystals. In this method, sawdust as a carbon source and nitric acid were mixed and heated. Then, pH of the solution was adjusted to neutral by adding NaOH and centrifuged. In the last step, for surface modification, PEG 2000 was added and heated in a microwave oven. Obtained carbon nanoparticles were characterized by TEM, and size of them was found in between 5 and 8 nm. Developed QDs were used for determination of

drugs and method was sensitive, selective, and with high recovery value [10].

QDs [114].

**3.2. Fluorescence resonance energy transfer (FRET)**

152 Spectroscopic Analyses - Developments and Applications

Functionalized semiconductor QDs have been used as fluorescence labels for biological detection and imaging. For example, avidin, highly positively charged tetramer, and functionalized CdSe/ZnS QDs were used in the detection of biotin [111]. Similarly, different sizes CdSe/ZnS QDs conjugated with different antibodies have been applied for simultaneous detection of four toxins (Shiga-like toxin 1, staphylococcal enterotoxin B, cholera toxin, and ricin) [112]. In another example, determination of 17β-estradiol has been done by using biotin-labeled antirabbit IgG and streptavidin conjugated by QDs [113]. As mentioned above, carbon-based QDs have low toxicity and biocompatibility. Li et al. have developed glucose sensor based on combining electrostatic attraction between anionic fluorescent carbon QDs that bear polar carboxy and hydroxy groups and cationic boronic acid–substituted bipyridinium salt. The interaction between them results in the formation of a ground state complex leading to a decrease in the fluorescence intensity. When glucose is added to the medium, the tetrahedral anionic glucoboranate esters are formed which effectively neutralize the net charge of the cationic bipyridinium and recover the fluorescence intensity of

Fluorescence resonance energy transfer (FRET) is a powerful technique describing energy transfer between two light-sensitive molecules. In here, an exited donor chromophore group transfers energy to an acceptor chromophore through the nonradiative coupling. The efficiency of this energy transfer depends on the distance between both fluorophores, inversely proportional to the sixth power of the distance between acceptor and donor; therefore, FRET is more sensitive to small changes in distance [115, 116]. Photoemission properties and high QY of QDs allow efficient energy transfer when compared with the organic dyes. In addition, distinguishing the emission of the donor from acceptor is much easier due to narrow and symmetric emission spectrum of QDs. This technique is a useful tool to analyze biomolecules such as proteins and DNA. For this purpose, a FRET-based bioassay was developed by using QDs (donor) functionalized with a label (i.e., protein, antibody) which recognizes and binds to target. When FRET process occurs, the bioconjugate captures the dye-labeled Several studies can be found that develop FRET-based assays for the detection of pharmaceuticals and biomolecules (**Table 3**). Generally, QDs and organic dye are used as donor and acceptor, respectively. However, the opposite situation, in which dye acted as a donor and QDs as acceptors, has been reported. Briefly, QD as a donor in an exited state transfers its excitation energy to an acceptor non-fluorescent dye in a nonradiative fashion. When the analyte introduces the medium, analyte replaces the dye, and fluorescence emission is recovered (**Figure 4**).

Similarly in this approach, amantadine has been determined in pharmaceutical form by using FRET mechanism. The optical sensor was designed by using water-soluble β-cyclodextrin (CD)-functionalized CdTe QDs and Rhodamine B (RB). The interior of the β-CD is not hydrophobic but considerably less hydrophilic than the aqueous environment and thus able to host other hydrophobic molecules. Therefore, RB could enter the cavity of β-CD by hydrophobic interaction, and the FRET process occurred between QDs (donor) and RB (acceptor). When amantadine introduced the system, it replaced RB in the cavity; the process of FRET was switched off. The authors also have used the developed sensor for *in-vivo* imaging. For this purpose, functionalized QDs with amantadine in the cavity were incubated with HepG2 cells and observed in the cytoplasm by fluorescence microscope [118].


**Table 3.** FRET-based fluorescent probes for determination of pharmaceuticals.

**Figure 4.** Schematic diagram of the quantum-dot based FRET sensor. QDs (donor) and non-fluorescent organic dye (acceptor).

Antony et al. [119] also used β-CD-conjugated CdSe/silica nanoparticles for determination of atrovastatin and linezolid. The FRET system occurred between CdSe/SiO<sup>2</sup> nanoparticles and the drugs encapsulated in the CD cavity. Coating and conjugation of prepared QDs were identified by FT-IR. FTIR spectra of CdSe and CdSe/SiO<sup>2</sup> -β-CD complex were recorded and vibration bands at 1031.92 and 1117.29 cm−1 appeared due to Si─O─Si bond. The Fröster distance between the encapsulated drugs and the CdSe nanoparticles was calculated and found below 3 nm.

More simple FRET method has been developed for analysis of Vitamin B12 in human serum, urine, and pharmaceutical forms. Herein, the MPA functionalized CdS QDs synthesized from cadmium chloride and sodium sulfide in aqueous media by a chemical method. FRET-based quenching mechanism was due to photoinduced charge transfer from QDs to drug. For investigation, the quenching mechanism, UV-vis absorption, and fluorescence spectra of QDs in the absence and presence of vitamin B12 were examined. Obtained results show that energy transfer from CdS QDs to vitamin B12 could occur with high probability resulting in the fluorescence quenching of QDs. Under the optimized conditions, the relationship between the fluorescence intensity of QDs and concentration of vitamin B12 was linear, and limit of detection was found as 6.91 μg mL−1 [120].

Zhang et al. [121] has developed a method for detection of DNA using commercially available streptavidin-coated QDs. In this method, nanoparticle and cyanine dye were donor and acceptor, respectively. Cyanine-labeled DNA was assembled onto the QDs surface by specific streptavidin-biotin binding. The binding of molecules to QDs resulted in the formation of QD/DNA/Dye complexes. FRET was occurred between QDs and dye by excitation with the appropriate wavelength.

The use of QDs as energy acceptors in FRET-based techniques is not so common. QDs were inadequate acceptors when compared with molecular dyes because of a longer lifetime of QDs [95]. In addition to this, the donor used has to emit luminescence at a wavelength shorter than that of the QDs to allow the FRET process. A method based on this technique has been developed by Geissler et al. Herein, FRET process was realized between visible-emitting lanthanide complexes of europium and terbium, streptavidin labeled (as a donor) to CdSe/ZnS biotin-coated QDs (as acceptor). Developed method has been used for determination of five biomarkers [122]. Similarly, determination of estradiol was examined by using luminescent energy transfer between protein-coupled CdTe QDs and lanthanide (III), europium and terbium, chelate [123].

#### **3.3. Chemiluminescence**

Antony et al. [119] also used β-CD-conjugated CdSe/silica nanoparticles for determination of

**Figure 4.** Schematic diagram of the quantum-dot based FRET sensor. QDs (donor) and non-fluorescent organic dye

drugs encapsulated in the CD cavity. Coating and conjugation of prepared QDs were identi-

bands at 1031.92 and 1117.29 cm−1 appeared due to Si─O─Si bond. The Fröster distance between the encapsulated drugs and the CdSe nanoparticles was calculated and found below 3 nm.

More simple FRET method has been developed for analysis of Vitamin B12 in human serum, urine, and pharmaceutical forms. Herein, the MPA functionalized CdS QDs synthesized from cadmium chloride and sodium sulfide in aqueous media by a chemical method. FRET-based quenching mechanism was due to photoinduced charge transfer from QDs to drug. For investigation, the quenching mechanism, UV-vis absorption, and fluorescence spectra of QDs in the absence and presence of vitamin B12 were examined. Obtained results show that energy transfer from CdS QDs to vitamin B12 could occur with high probability resulting in the fluorescence quenching of QDs. Under the optimized conditions, the relationship between the fluorescence intensity of QDs and concentration of vitamin B12 was linear, and limit of

Zhang et al. [121] has developed a method for detection of DNA using commercially available streptavidin-coated QDs. In this method, nanoparticle and cyanine dye were donor and acceptor, respectively. Cyanine-labeled DNA was assembled onto the QDs surface by specific streptavidin-biotin binding. The binding of molecules to QDs resulted in the formation of QD/DNA/Dye complexes. FRET was occurred between QDs and dye by excitation with the

The use of QDs as energy acceptors in FRET-based techniques is not so common. QDs were inadequate acceptors when compared with molecular dyes because of a longer lifetime of QDs [95]. In addition to this, the donor used has to emit luminescence at a wavelength shorter than that of the QDs to allow the FRET process. A method based on this technique has been developed by Geissler et al. Herein, FRET process was realized between visible-emitting lanthanide complexes of europium and terbium, streptavidin labeled (as a donor) to CdSe/ZnS biotin-coated QDs (as acceptor). Developed method has been used for determination of five biomarkers [122]. Similarly, determination of estradiol was examined by using luminescent energy transfer between protein-coupled CdTe QDs and lanthanide (III), europium and ter-

nanoparticles and the


atrovastatin and linezolid. The FRET system occurred between CdSe/SiO<sup>2</sup>

fied by FT-IR. FTIR spectra of CdSe and CdSe/SiO<sup>2</sup>

154 Spectroscopic Analyses - Developments and Applications

detection was found as 6.91 μg mL−1 [120].

appropriate wavelength.

(acceptor).

bium, chelate [123].

Chemiluminescence (CL) is typically defined as the emission of light, as the result of a chemical reaction. Generally, chemiluminescent reactions show weak luminescence due to low QY. Therefore, it is necessary to enhance the CL intensity for analytical applications. For this reason, QDs have attracted great attention due to their properties as mentioned before such as brightness and reactivity. In addition, the use of QDs as chemiluminescent probe can give an advantage such as the emission at wide range wavelengths without light source [47, 124]. Nowadays, high-quality semiconductor QDs (core or core-shell) can be easily synthesized and have been used in CL systems such as CdTe, CdSe, and CdSe/CdS. Besides, doped QDs are also used in CL assays because of their catalytic features. The advances of using QDs in CL not only expand conventional usage of them but also give an opportunity to develop new nanomaterials.

There are three possible mechanisms that could be explained for the enhancement of CL by QDs as explained by Frigerio et al. [47]: (i) as emitter species after direct oxidation; direct oxidation happens when QDs is an only luminescent compound in the system; (ii) as a catalyst of a reaction involving others luminophores; when more than one luminophores exist in the system, the final emitter is the luminophores due to the catalytic effect of QDs; and (iii) as emitter species after chemiluminescence resonance energy transfer (CRET); the difference from catalytic effect, the final emitter is QDs.

Chen et al. have used MPA-capped CdTe QDs in H<sup>2</sup> O2 -HCO<sup>3</sup> CL system and applied for the determination of ascorbic acid in serum [125]. The chemical process followed; peroxymonocarbonate (HCO<sup>4</sup> − ) was formed by reaction of hydrogen peroxide and sodium hydrogen carbonate. This unstable compound decomposed and caused to form superoxide ion radical (·O<sup>2</sup> − ) and finally singlet oxygen molecules with emission after several chemical steps. Radical scavenger, ascorbic acid, was used to study the emitting species. The proposed reaction mechanism based on the presence of four emitters: <sup>1</sup> O2 , (O<sup>2</sup> ) 2 \*, (CO<sup>2</sup> )2 \*, and CdTe\* in the system. Authors also explained that the CL emission intensity depended on sizes of QDs, bigger nanoparticles decreased CL intensity.

In another work, Khateee et al. [126] used a flow-injection analysis system to investigate KMnO<sup>4</sup> -morin sensitized with CdS QDs and applied it to environmental water samples and pharmaceutical forms for determination of nalidixic acid. In addition, luminescence intensity was enhanced not only by adding l-cysteine–capped CdS QDs but also nalidixic acid. Possible CL mechanism was based on oxidation of morin and CdS by KMnO<sup>4</sup> in acidic media. Moreover, obtained UV-vis and luminescence spectrum showed that transmission of the energy of excited morin to CdS QDs can occur. According to the spectral knowledge, the addition of nalidixic acid to KMnO<sup>4</sup> -morin-CdS QDs system cannot generate new luminophore species. The final emitter species in the mentioned CL system is exited CdS QDs.

The same group also used a similar QDs system for the baclofen analysis in water samples and pharmaceutical forms. Various oxidants in basic and acidic aqueous medium were examined, and the best results were obtained with KMnO<sup>4</sup> in acidic media. In addition, Na<sup>2</sup> S2 O3 significantly enhanced the CL intensity of KMnO<sup>4</sup> l-cysteine–caped CdS QDs, while adding of baclofen caused inhibition of intensity. There are two emissions bands observed, attributed to CdS QDs (at around 520 nm) and exited manganese (at around 725 nm). The process of CL is that (i) KMnO<sup>4</sup> oxidizes the l-cysteine to produce excited l-cysteine, (ii) excited l-cysteine transforms its energy to CdS QDs, and (iii) excited QDs produce the emission. Furthermore, the inhibition effect of baclofen was explained by incorporation of baclofen and KMnO<sup>4</sup> . The consumption of KMnO<sup>4</sup> by baclofen leads to decrease in the amount of excited CdS QDs and then CL emission [127].

QDs can be used in CL system as a catalyst, due to the redox properties of both conduction and valence bands. Imani-Nabiyyi and Sorouraddin showed that the CL emission was enhanced by combination of cysteine-capped CdTe QDs and luminol in the presence of KIO<sup>4</sup> . The amplified CL was effectively quenched in the presence of naphazoline. According to spectroscopic and chemical investigations, weak CL emission was observed with the reaction between periodate and luminol in alkaline conditions; however, adding of QDs caused increasing of the CL emission. Based on these data, this phenomenon was explained by author that QDs could interact with the reactants catalytically and caused to form reactive oxygen species which reacts with luminol in order to give emission [128].

#### **3.4. Chemiluminescence resonance energy transfer (CRET)**

CRET is a nonradiative transfer of energy between chemiluminescent donors to a fluorophore acceptor. An essential condition is that there should be an overlap between CL emission spectrum and the absorption spectrum of the fluorescent acceptor. QDs are well-suited fluorescent acceptors due to their broad excitation spectra. In CRET, QDs are the final emitters, which can be confirmed by the emitted spectra. However, sometimes, it is also possible that direct oxidation and CRET take place simultaneously; thus with CRET, it is difficult to define that the excited forms of QDs are formed by a resonance energy transfer process or a redox process.

The water-soluble MPA-capped CdTe QDs as sensitizers are used for the chemiluminometric determination of the anti-diabetic drugs gliclazide and glipizide in their pharmaceutical formulations. Both glipizide and gliclazide quenched the CL emission of the Ce(IV)–SO<sup>3</sup> 2−-CdTe QD system, probably due to radical scavenging activity [129].

Golub et al. demonstrated CRET system for highly sensitive detection of DNA by the labeling of the probe-analyte complex with a hemin/G-quadruplex nanostructure [130]. The emission of CdS QDs was observed by stimulation with hemin/G-quadruplex-catalyzed luminol-H<sup>2</sup> O2 system. The detection limit for DNA is 2 nmol L−1.

Similar nanostructure was modified with glucose oxidase and conjugated to CdSe/ZnS QDs for the CL detection of glucose. The glucose oxidase catalyzed the oxidation of glucose to compose gluconic acid and H2 O2 . Then, in the presence of luminol catalyzed by hemin/Gquadruplex generated strong CL, which initiated a CRET process to the CdSe/ZnS QDs. Quantitative determination of glucose can be realized from the luminescence intensity of the QDs. The detection limit of glucose was calculated to 5 mmol L−1 [131].

#### **3.5. Phosphorescence**

of baclofen caused inhibition of intensity. There are two emissions bands observed, attributed to CdS QDs (at around 520 nm) and exited manganese (at around 725 nm). The process of CL

transforms its energy to CdS QDs, and (iii) excited QDs produce the emission. Furthermore, the inhibition effect of baclofen was explained by incorporation of baclofen and KMnO<sup>4</sup>

QDs can be used in CL system as a catalyst, due to the redox properties of both conduction and valence bands. Imani-Nabiyyi and Sorouraddin showed that the CL emission was enhanced by combination of cysteine-capped CdTe QDs and luminol in the presence of KIO<sup>4</sup>

The amplified CL was effectively quenched in the presence of naphazoline. According to spectroscopic and chemical investigations, weak CL emission was observed with the reaction between periodate and luminol in alkaline conditions; however, adding of QDs caused increasing of the CL emission. Based on these data, this phenomenon was explained by author that QDs could interact with the reactants catalytically and caused to form reactive oxygen

CRET is a nonradiative transfer of energy between chemiluminescent donors to a fluorophore acceptor. An essential condition is that there should be an overlap between CL emission spectrum and the absorption spectrum of the fluorescent acceptor. QDs are well-suited fluorescent acceptors due to their broad excitation spectra. In CRET, QDs are the final emitters, which can be confirmed by the emitted spectra. However, sometimes, it is also possible that direct oxidation and CRET take place simultaneously; thus with CRET, it is difficult to define that the excited forms of QDs are formed by a resonance energy transfer process or a

The water-soluble MPA-capped CdTe QDs as sensitizers are used for the chemiluminometric determination of the anti-diabetic drugs gliclazide and glipizide in their pharmaceutical for-

Golub et al. demonstrated CRET system for highly sensitive detection of DNA by the labeling of the probe-analyte complex with a hemin/G-quadruplex nanostructure [130]. The emission of CdS QDs was observed by stimulation with hemin/G-quadruplex-catalyzed luminol-H<sup>2</sup>

Similar nanostructure was modified with glucose oxidase and conjugated to CdSe/ZnS QDs for the CL detection of glucose. The glucose oxidase catalyzed the oxidation of glucose to

quadruplex generated strong CL, which initiated a CRET process to the CdSe/ZnS QDs. Quantitative determination of glucose can be realized from the luminescence intensity of the

. Then, in the presence of luminol catalyzed by hemin/G-

mulations. Both glipizide and gliclazide quenched the CL emission of the Ce(IV)–SO<sup>3</sup>

species which reacts with luminol in order to give emission [128].

**3.4. Chemiluminescence resonance energy transfer (CRET)**

QD system, probably due to radical scavenging activity [129].

O2

QDs. The detection limit of glucose was calculated to 5 mmol L−1 [131].

system. The detection limit for DNA is 2 nmol L−1.

compose gluconic acid and H2

oxidizes the l-cysteine to produce excited l-cysteine, (ii) excited l-cysteine

by baclofen leads to decrease in the amount of excited CdS QDs and

. The

.

2−-CdTe

O2

is that (i) KMnO<sup>4</sup>

redox process.

consumption of KMnO<sup>4</sup>

156 Spectroscopic Analyses - Developments and Applications

then CL emission [127].

Phosphorescence is the radiative transition from the lowest excited triplet state, T1 , to the (singlet) ground state, S<sup>0</sup> . On the contrary to fluorescence (singlet-singlet transition), phosphorescence is a spin-forbidden process [100]. In order to obtain phosphorescence, the phosphorophore is excited by electromagnetic radiation of the appropriate wavelength. If S energy levels and T energy levels are close, some of the excited molecules can drop into the T state through an intersystem crossing. The intersystem crossing quantum efficiency can be enhanced by different approaches such as cryogenic conditions, micelle, and heavy atom effect. Phosphorescence techniques have advantages over the fluorescence methods such as selectivity, sensitivity, longer emission lifetime, and a wider gap between excitation and emission spectra. The longer lifetime of the triplet excited state allows using an appropriate delay time so that possible spectral interferences coming from system and light scattering can be avoided [132].

The optical, electrical, and magnetic character of QDs can be modified by using different types of dopants. Compared with traditional QDs such as CdSe, ZnS is a more attractive host nanoparticle for doping to form new type of QDs. Doping Mn2+ into ZnS QDs provides unique phosphorescence properties. Mn-doped ZnS QDs exhibit phosphorescence emission, which is produced by the energy transfer from the band gap of ZnS to Mn2+ dopant and the subsequent transition from the triplet state to the ground state of the Mn2+ involved in the ZnS host lattice [133]. Similar to fluorescent methods, mechanism of the system is quenching of phosphorescence emission of QDs. Adding quencher to QDs solution causes decrease of phosphorescence intensity due to adsorption onto the surface of QDs. When added, analyte interacts with the quencher, the new complex molecule is formed, and phosphorescence intensity is recovered due to removal of quencher from the surface. This type of QDs has been used in the phosphorescent sensing of drugs and biomolecules without any sample pretreatment [12].

General synthesis process of Mn-doped ZnS was explained by He et al. [134]. Briefly, capping agent such as l-cysteine and MPA, ZnSO<sup>4</sup> , and MnCl<sup>2</sup> were added to a flask. pH of the mixture was adjusted to 11 with NaOH. Then, after air was removed with argon purging at room temperature, Na2 S was quickly added to the solution. The mixture was stirred, and then, the solution was aged at 50°C under open air to form capped Mn-doped ZnS QDs. The heating step is vital for synthesis. For example, the phosphorescence spectrum of l-cysteine–capped Mn-doped ZnS QDs exhibited a maximum phosphorescence emission peak at 590 nm when excited at 290 nm. This peak was not observed without the aging step; however, after aging step, the peak appeared [39].

He et al. report Mn-doped ZnS QDs for the RTP detection of enoxacin in biological fluids. The fluorescence spectra of the Mn-doped ZnS QDs show two emission bands, at 435 and 590 nm, while the phosphorescence spectra exhibit only a single-emission peak at 590 nm. The emission at 590 nm presents typical characteristics of an RTP and shows a long decay time of 2 ms because of intersystem crossing. Reported Mn-doped ZnS QDs-based RTP method was not need the using of oxygen scavenger and other inducers and allowed the detection of enoxacin in biological fluids without interference from autofluorescence and the scattering light of the matrix [134].

In phosphorescence study, not only uncapped but also capped QDs are used. For this purpose, widely used capping agents are MPA and l-cysteine. For example, MPA-capped Mn-doped ZnS QDs/CTAB nanohybrids were prepared through electrostatic self-assembly and applied to detection of rutin [135]. Cetyltrimethyl ammonium bromide (CTAB) is a cationic surfactant and has high stability to chemicals, heat, light, pressure, and pH; therefore, CTAB-based nanohybrid also shows highly stable features. Besides, adding of CTAB to QDs causes enhancement of phosphorescence intensity. Quantitative determination of rutin was done by using of linearity of RTP quenching value of QDs and rutin concentration.

N-acetyl-l-cysteine (NAC) and l-cysteine–capped Mn-doped ZnS QDs (NAC-Mn/ZnS QDs and l-cysteine-Mn/ZnS QDs) were prepared by hydrothermal methods and used for determination of l-ascorbic in the human serum sample. The characterization of QDs was made by TEM. Both NAC and l-cysteine–capped QDs were of spherical shape with size 8–10 nm. FT-IR spectra of NAC-capped QDs showed that the band of sulfhydryl group disappeared, and the band of carboxyl group was shifted. When it comes to l-cysteine spectra, their S─H vibration band disappeared. These results indicated that NAC and l-cysteine capped the QDs successfully. The proposed method was selective and sensitive. The Stern-Volmer plot and phosphorescence decay of nanohybrid QDs indicated the dynamic quenching mechanism [136].

Similar QDs system was applied to the investigation of the interaction of anticancer drug and DNA. Herein, l-cysteine capped Mn-doped ZnS QDs/idarubicin (IDA) nanohybrid was used as a phosphorescent probe. IDA was adsorbed on the surface of Mn-doped ZnS QDs and quenched of phosphorescence signal. With the addition of ds-DNA, IDA interacts with DNA, desorbed from the surface of the QDs, and the phosphorescence signal is increased. The quenching mechanism of phosphorescence of QDs by IDA was a combined dynamic and static quenching [12].

Same mechanism was used to investigate anticancer drug sanguinarine and DNA interaction [53]. Sanguinarine can adsorb on the surface of Mn-doped QDs and quench the phosphorescence emission. When the G-quadruplex-sanguinarine complex formed, the phosphorescence intensities of the QDs sensors would be restored.

The macromolecules such as DNA and ATP are also used for capping agents. An ultrasonicassisted approach was developed for the synthesis of adenosine triphosphate (ATP)–capped Mn-doped ZnS QDs. The prepared QDs were combined Mg2+-ATP-arginine ternary system and used a phosphorescent probe to detect arginine and methylated arginine [137]. The supramolecular interactions of Mg2+ and arginine with ATP have been investigated. Arginine and Mg2+ acted as a cofactor, interacted specifically, and catalyzed the hydrolysis of ATP. The binding of ATP-capped Mn-doped ZnS QDs to arginine in the presence of Mg2+ caused to quenching of the phosphorescence intensity of the QDs, which allowed detection of arginine with a detection limit of 0.23 mM.

Phosphorescent QDs have been used as a probe in numerous bioanalysis such as for nucleic acid or protein detection. Gong et al. developed riboflavin (RF)-modulated MPA-capped Mn-doped ZnS QDs and utilized as RTP sensor for DNA detection. As an electron acceptor, RF could quench the RTP emission of QDs via photo-induced electron transfer (PIET) and form Mn-doped ZnS QDs/RF nanohybrids by electrostatic attraction. RF also effectively interacted with DNA in groove-binding mode. In Mn-doped ZnS QDs/RF nanohybrids system, adding of DNA to medium caused the removal of RF from the surface of QDs due to interaction with DNA double helix. Therefore, releasing the RTP of Mn-doped ZnS QDs was observed. The degree of recovery of Mn-doped ZnS QDs depended on DNA concentration. The developed QD-based RTP sensor acted in a turn-on mode and offered high sensitivity to DNA [138].

Another study for detecting DNA is based on self-assembly of nanohybrids from octa(3-aminopropyl) octasilsequioxane octahydrochloride (OA-POSS) and MPA-capped Mn-doped ZnS QDs (MPA-1) [139]. OA-POSS has eight quaternary ammonium groups on each corner and acts as cubic linkers between MPA-1 through electrostatic interaction. MPA-1 and OA-POSS form spherical nanohybrids (1/OA-POSS) in aqueous solution with these linkers. DNA possesses negative charge in phosphate groups and competes with MPA-1 for forming complexes with OA-POSS. This competition led to the decrease of the emission intensity of 1/OAPOSS nanohybrids and allows developing a method for quantitative determination of DNA.

#### **4. Conclusions**

in biological fluids without interference from autofluorescence and the scattering light of the

In phosphorescence study, not only uncapped but also capped QDs are used. For this purpose, widely used capping agents are MPA and l-cysteine. For example, MPA-capped Mn-doped ZnS QDs/CTAB nanohybrids were prepared through electrostatic self-assembly and applied to detection of rutin [135]. Cetyltrimethyl ammonium bromide (CTAB) is a cationic surfactant and has high stability to chemicals, heat, light, pressure, and pH; therefore, CTAB-based nanohybrid also shows highly stable features. Besides, adding of CTAB to QDs causes enhancement of phosphorescence intensity. Quantitative determination of rutin was done by using of linear-

N-acetyl-l-cysteine (NAC) and l-cysteine–capped Mn-doped ZnS QDs (NAC-Mn/ZnS QDs and l-cysteine-Mn/ZnS QDs) were prepared by hydrothermal methods and used for determination of l-ascorbic in the human serum sample. The characterization of QDs was made by TEM. Both NAC and l-cysteine–capped QDs were of spherical shape with size 8–10 nm. FT-IR spectra of NAC-capped QDs showed that the band of sulfhydryl group disappeared, and the band of carboxyl group was shifted. When it comes to l-cysteine spectra, their S─H vibration band disappeared. These results indicated that NAC and l-cysteine capped the QDs successfully. The proposed method was selective and sensitive. The Stern-Volmer plot and phosphorescence decay of nanohybrid QDs indicated the dynamic quenching mechanism

Similar QDs system was applied to the investigation of the interaction of anticancer drug and DNA. Herein, l-cysteine capped Mn-doped ZnS QDs/idarubicin (IDA) nanohybrid was used as a phosphorescent probe. IDA was adsorbed on the surface of Mn-doped ZnS QDs and quenched of phosphorescence signal. With the addition of ds-DNA, IDA interacts with DNA, desorbed from the surface of the QDs, and the phosphorescence signal is increased. The quenching mechanism of phosphorescence of QDs by IDA was a combined dynamic and

Same mechanism was used to investigate anticancer drug sanguinarine and DNA interaction [53]. Sanguinarine can adsorb on the surface of Mn-doped QDs and quench the phosphorescence emission. When the G-quadruplex-sanguinarine complex formed, the phosphorescence

The macromolecules such as DNA and ATP are also used for capping agents. An ultrasonicassisted approach was developed for the synthesis of adenosine triphosphate (ATP)–capped Mn-doped ZnS QDs. The prepared QDs were combined Mg2+-ATP-arginine ternary system and used a phosphorescent probe to detect arginine and methylated arginine [137]. The supramolecular interactions of Mg2+ and arginine with ATP have been investigated. Arginine and Mg2+ acted as a cofactor, interacted specifically, and catalyzed the hydrolysis of ATP. The binding of ATP-capped Mn-doped ZnS QDs to arginine in the presence of Mg2+ caused to quenching of the phosphorescence intensity of the QDs, which allowed detection of arginine

ity of RTP quenching value of QDs and rutin concentration.

matrix [134].

158 Spectroscopic Analyses - Developments and Applications

[136].

static quenching [12].

intensities of the QDs sensors would be restored.

with a detection limit of 0.23 mM.

A pervasive trend in the pharmaceutical and biomedical analysis is the development of ultrasensitive and high-throughput technologies for the rapid detection and quantification of drugs, proteins, and nucleic acid. QDs have an important role in this field. QDs have unique structural and surface properties such as stability, tunable size, wide spectrum band, and large surface-to-volume ratio that have enabled a new avenue of research to be opened. QD-based nanotechnology will be constantly expanding its applications due to their continued development of specialized nanoparticles. Chemical-surface modifications of the QDs allow enhancing the selectivity of the systems and to profit from their favorable emission features. Moreover, different approaches such as the combination of the nanoparticles with energy-transfer processes and phosphorescence detection are helping to open new research areas. These intelligent, multifunctional, low-toxic or nontoxic nanoparticles are achievements for the future.

#### **Author details**

Hayriye Eda Şatana Kara\* and Nusret Ertaş \*Address all correspondence to: eda@gazi.edu.tr Department of Analytical Chemistry, Faculty of Pharmacy, Gazi University, Ankara, Turkey

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**Applications of Spectrophotometric Methods in Pharmaceutical and Biomedical Analyses**

## **Ion-Pair Spectrophotometry in Pharmaceutical and Biomedical Analysis: Challenges and Perspectives**

Marinela Florea and Mihaela Ilie

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.69778

#### **Abstract**

Experimental and theoretical studies of the mechanisms that underlay ion-pair formation, their properties and applications in various fields have been and still are focused by researchers since the introduction of the concept in 1926, by Bjerrum. Ion pairs are distinct chemical entities, electrically neutral, formed between ions of opposite charge and held together by Coulomb forces, without formation of a covalent bond. Investigation methods used are various, from classical conductometric measurements to up-to-date methods, such as spectrophotometry, chromatography and capillary electrophoresis. In the pharmaceutical field, ion pairs were used to develop methods of separation, identification and assay for the active substances in complex matrices, to obtain pharmaceutical formulations with controlled release and to explain the mechanisms of transport and action for certain drugs. The chapter is an attempt to describe new trends in the spectrophotometry of ion pairs and their applications in the pharmaceutical field. The development of the concept and types of ion pairs are first presented; further, examples of applications using molecular absorption, fluorimetry and resonance light scattering spectrophotometry are presented. Based on the literature data and the authors' experience in the field, challenges and perspectives in the ion-pair spectrophotometry are also considered.

**Keywords:** ion-pair spectrophotometry, pharmaceuticals, UV-Vis absorption, fluorescence, resonance light scattering, resonance Rayleigh scattering

#### **1. Introduction**

Ion-pair spectrophotometry refers to analysis methods based on the optical properties of the ion pairs. Infrared, nuclear magnetic resonance and Raman spectrometry are the methods generally used to investigate the structure of the ion pairs and molecular and atomic absorption, fluorimetry and resonance light scattering are used as assay methods.

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Known also as *ionic associations* or *ionic association complexes*, ion pairs are pairs of oppositely charged ions held together by Coulomb attraction without formation of a covalent bond [1]. The lifetime of an ion pair was determined to be of at least 10−5 seconds, equivalent to about 10<sup>8</sup> molecular vibrations, demonstrating that ion pairs can be considered as independent species [2].

The inclusion of a substance in an ionic association causes changes in its physical-chemical properties without changing its structure, because an ion pair is electrically neutral and has increased lipophilicity compared with the free ions in its composition [3]. The optimum experimental conditions for a quantitative ion-pair equilibrium (solvent, pH, ionic strength) are easily settled. The selectivity of the methods can be increased by selecting the optimum reagent (counterion, ion-pair forming reagent) and the subsequent extraction of the ion pair in an organic phase.

The significant number of the scientific papers published indicates the appropriateness of ion pairing in solving important issues in the pharmaceutical field, especially in analytical chemistry, biochemistry and pharmaceutical technology. Ion pairs are used for the development of new pharmaceutical forms with controlled release, especially for peptides [3–5]. In this case, one of the main advantages is the unmodified pharmaco-toxicological profile of the active substance after ion pairing, because it does not suffer structural changes. The stability [6] and bioavailability [7, 8] of the drugs can be improved. A series of kinetic studies proposed the ion-pair formation as an absorption mechanism for the pharmaceutical substances [9, 10]. Investigations on DNA stability in various matrices [11], protein determination [12] and synthesis of ion-pair receptors based on biological models [13] are important applications of ion-pair equilibrium in biochemistry. Ion-pair–based assay methods are proficient in both isolation, identification and quantification of certain substances of biomedical interest [14]. Over time, titrimetric [15, 16], gravimetric [17, 18], electrometric [19, 20], spectrophotometric [21, 22] and chromatographic [23, 24] methods based on the ion-pair formation were developed.

Classical and modern as well, ion-pair–based spectrophotometric methods had a dynamic evolution over the time. On the one hand, this is due to the elucidation of the mechanisms underlying the formation of ion pairs, and thus, the setting of the experimental conditions, which allow the obtaining of ion pairs for all types of substances, is easier; in this regard, computational chemistry is a very useful tool. On the other hand, the synthesis of new pharmacologically active molecules at very low concentrations requires sensitive analysis methods. Among them, less used spectrophotometric techniques, such as resonance light scattering, have found interesting applications when ion pairing was taken into account.

#### **2. Fundamentals of ion pair**

#### **2.1. History of the ion-pair concept**

The ion-pair equilibrium has been first considered for inorganic ions, being an important step in the study of the electrolyte solutions. The history of the ion-pair concept starts in 1887 with Arrhenius, who structured the theory of electrolytic dissociation. Debye and Hückel defined in 1923 the activity coefficients and deduced the homonym equation that allows the assessment of those coefficients in aqueous solutions of electrolytes [25]. In 1926, Bjerrum introduced an association constant in the Debye-Hückel equation and demonstrated that ionpair equilibrium is dependent on the dielectric constant of the solvent, on the temperature and on the size of the ions. For his theory, he considered spherical, nonpolarizable interacting ions [26]. Thus, the existence of ion pairs was accepted in low dielectric constant solvents. Subsequently, studies were performed in order to elucidate the existence of solvent molecules in the ion-pair structure [27]. Most of the experimental data used to confirm theoretical studies on ion pairing were conductivity measurements.

Known also as *ionic associations* or *ionic association complexes*, ion pairs are pairs of oppositely charged ions held together by Coulomb attraction without formation of a covalent bond [1]. The lifetime of an ion pair was determined to be of at least 10−5 seconds, equivalent to about 10<sup>8</sup> molecular vibrations, demonstrating that ion pairs can be considered as independent species [2]. The inclusion of a substance in an ionic association causes changes in its physical-chemical properties without changing its structure, because an ion pair is electrically neutral and has increased lipophilicity compared with the free ions in its composition [3]. The optimum experimental conditions for a quantitative ion-pair equilibrium (solvent, pH, ionic strength) are easily settled. The selectivity of the methods can be increased by selecting the optimum reagent (counterion, ion-pair forming reagent) and the subsequent extraction of the ion pair

The significant number of the scientific papers published indicates the appropriateness of ion pairing in solving important issues in the pharmaceutical field, especially in analytical chemistry, biochemistry and pharmaceutical technology. Ion pairs are used for the development of new pharmaceutical forms with controlled release, especially for peptides [3–5]. In this case, one of the main advantages is the unmodified pharmaco-toxicological profile of the active substance after ion pairing, because it does not suffer structural changes. The stability [6] and bioavailability [7, 8] of the drugs can be improved. A series of kinetic studies proposed the ion-pair formation as an absorption mechanism for the pharmaceutical substances [9, 10]. Investigations on DNA stability in various matrices [11], protein determination [12] and synthesis of ion-pair receptors based on biological models [13] are important applications of ion-pair equilibrium in biochemistry. Ion-pair–based assay methods are proficient in both isolation, identification and quantification of certain substances of biomedical interest [14]. Over time, titrimetric [15, 16], gravimetric [17, 18], electrometric [19, 20], spectrophotometric [21, 22] and chromatographic [23, 24] methods based on the ion-pair formation were developed.

Classical and modern as well, ion-pair–based spectrophotometric methods had a dynamic evolution over the time. On the one hand, this is due to the elucidation of the mechanisms underlying the formation of ion pairs, and thus, the setting of the experimental conditions, which allow the obtaining of ion pairs for all types of substances, is easier; in this regard, computational chemistry is a very useful tool. On the other hand, the synthesis of new pharmacologically active molecules at very low concentrations requires sensitive analysis methods. Among them, less used spectrophotometric techniques, such as resonance light scattering,

The ion-pair equilibrium has been first considered for inorganic ions, being an important step in the study of the electrolyte solutions. The history of the ion-pair concept starts in 1887 with Arrhenius, who structured the theory of electrolytic dissociation. Debye and Hückel

have found interesting applications when ion pairing was taken into account.

**2. Fundamentals of ion pair**

**2.1. History of the ion-pair concept**

in an organic phase.

174 Spectroscopic Analyses - Developments and Applications

The subsequent development of organic synthesis and the physical-chemical study of association of more complex molecules, concomitant with the development of new analysis methods (spectrophotometry, chromatography), indicated that, when forming an ion pair, the interacting ions cannot be considered as rigid and spherical [28]. In 1967, Higuchi et al., considering the volume and charge distribution over the ions, studied how a contact ion pair can be solvated in various solvents. For the ion pairs formed between a large lipophilic cation and a small anion, the high negative charge per unit area, lead to the solvation with electrophilic molecules, such as chloroform, phenols and alcohols. The high negative charge on the surface of the ion pairs formed between a small cation and a large lipophilic anion induce the solvation with nucleophilic molecules, such as ethers, ketones, amides and phosphate esters. For the ion pairs formed between two large ions, no significant solvation was observed [29].

Hydrophobic interaction, typical for large unhydrated (hydrophobic) univalent ions, was proposed as a mechanism of ion-pair formation in aqueous solution by Diamond [30]. The driving force for the ion pairing is the water molecule preference to interact with itself by hydrogen bonding. The equilibrium is named *water structure-enforced ion pairing* and the complexes formed accordingly—*water structure-enforced ion pairs*. Thus, starting from this point, the existence of the ion pairs in water became an accepted fact.

When the interaction between the oppositely charged ions is strictly electrostatic, no new electronic bands appear in the absorption spectrum [28]. Spectral changes reported in the studies indicate that, for the ion pairs formed by organic ions, additional interactions (aromatic stacking, charge transfer, hydrogen bonding) might exist.

Aromatic stacking is indicated by a hypochromic effect in the absorption spectra and was demonstrated by thermodynamic studies for the interaction between organic species containing aromatic structures [31]. Considered to be a result of a non-classical hydrophobic effect, the *stacking* of the *aromatic* rings is determined by the interaction between the partial charges (positive and negative) that exists on the atoms situated in adjacent aromatic rings.

The redistribution of the charge between the ions (charge transfer) is identified spectrophotometrically by a hypsochromic (blue shift) or bathochromic (red shift) effect in the UV-Vis region, depending on the medium polarity. This type of interaction can be predicted by theoretical calculations, based on charge density and molecular orbital theory [32, 33]. The ionic associations based on such interaction have been named *ion-pair charge*-*transfer complexes* [32].

Similarly, it was proved that ion pairs can be formed also by the interaction between an acid and a base by *proton transfer* [34].

Thus, nowadays, it is generally accepted that electrostatic interactions, hydrophobic interactions and proton transfer are the main mechanisms involved in the ion-pair formation and that the ion pair stability depend on the structure and size of the ions, on their acid-base and hydrophobic properties and on the solvent nature as well.

The methods currently used for the study of the ion-pair equilibrium are spectrophotometry (molecular absorption, resonance light scattering and fluorescence), conductometry [35], chromatography [23, 24, 36] and capillary electrophoresis [37].

The development of computational chemistry makes possible simulation of associations between complex molecules. Thus, in silico investigations became a valuable tool in the study of the ionic association equilibrium. Such studies can explain the formation of a certain complex, or predict it, and are commonly validated by spectrophotometric methods.

#### **2.2. Types of ion pairs**

The formation mechanism and the structure of the ion pairs were established concurrently with the elucidation of the interaction types of the ions in solution. Considering the solvation, ion pairs exist in the *tight* (*contact, intimate*) form (no solvent molecule is involved in the ion pair) and in the *loose* form (one or more solvent molecules are included in the ion pair). Depending on the number of the solvent molecules involved, ion pairs are of *solvent-sharing* type (a single solvent molecule is included) and *solvent-separated* ion pairs (when more than one solvent molecule is involved) [1].

Considering the structure of the ions involved in the ion-pair equilibrium, an overview of the literature published allowed the identification of three categories: (a) inorganic ion pairs (both ions are inorganic), (b) ion pairs formed between an organic molecule in ionized form and an inorganic ion and (c) organic ion pairs (both ions are organic substances in ionized form). The inorganic ions can be included in an ionic association in the free form or as inorganic complex. The organic substances are transformed in the ionic form based on their acid-base properties, by selecting the optimum pH, or after a complexation reaction with an inorganic ion. The inorganic ion pairs are intensively studied by physical chemistry, for the theoretical background of the mechanisms of ion pairing. The ion pairs that contain an organic ion are more used in the pharmaceutical field.

The solubility of the ion pairs in the selected solvent can be also a criterion to classify the ion pairs. Thus, two categories can be discerned: insoluble and soluble ion pairs. Insoluble ion pairs are used in the assay of the pharmaceuticals by gravimetric methods [17, 18, 38] and atomic absorption spectrometry [39, 40] and also in pharmaceutical technology for drug release systems [5]. The applications that rely on the formation of soluble ion pairs are most numerous.

As an ion pair is electrically neutral, the number of ions involved depends on their charge. Frequently encountered in literature are binary ion pairs, formed between ions with the same charge, and ternary ion pairs, which contain one divalent ion and two monovalent counterions.

### **3. Spectrophotometric applications of ion pairing in pharmaceutical analysis**

#### **3.1. Molecular absorption spectrophotometry**

Similarly, it was proved that ion pairs can be formed also by the interaction between an acid

Thus, nowadays, it is generally accepted that electrostatic interactions, hydrophobic interactions and proton transfer are the main mechanisms involved in the ion-pair formation and that the ion pair stability depend on the structure and size of the ions, on their acid-base and

The methods currently used for the study of the ion-pair equilibrium are spectrophotometry (molecular absorption, resonance light scattering and fluorescence), conductometry [35],

The development of computational chemistry makes possible simulation of associations between complex molecules. Thus, in silico investigations became a valuable tool in the study of the ionic association equilibrium. Such studies can explain the formation of a certain com-

The formation mechanism and the structure of the ion pairs were established concurrently with the elucidation of the interaction types of the ions in solution. Considering the solvation, ion pairs exist in the *tight* (*contact, intimate*) form (no solvent molecule is involved in the ion pair) and in the *loose* form (one or more solvent molecules are included in the ion pair). Depending on the number of the solvent molecules involved, ion pairs are of *solvent-sharing* type (a single solvent molecule is included) and *solvent-separated* ion pairs (when more than

Considering the structure of the ions involved in the ion-pair equilibrium, an overview of the literature published allowed the identification of three categories: (a) inorganic ion pairs (both ions are inorganic), (b) ion pairs formed between an organic molecule in ionized form and an inorganic ion and (c) organic ion pairs (both ions are organic substances in ionized form). The inorganic ions can be included in an ionic association in the free form or as inorganic complex. The organic substances are transformed in the ionic form based on their acid-base properties, by selecting the optimum pH, or after a complexation reaction with an inorganic ion. The inorganic ion pairs are intensively studied by physical chemistry, for the theoretical background of the mechanisms of ion pairing. The ion pairs that contain an organic ion are

The solubility of the ion pairs in the selected solvent can be also a criterion to classify the ion pairs. Thus, two categories can be discerned: insoluble and soluble ion pairs. Insoluble ion pairs are used in the assay of the pharmaceuticals by gravimetric methods [17, 18, 38] and atomic absorption spectrometry [39, 40] and also in pharmaceutical technology for drug release systems [5]. The applications that rely on the formation of soluble ion pairs are most numerous.

As an ion pair is electrically neutral, the number of ions involved depends on their charge. Frequently encountered in literature are binary ion pairs, formed between ions with the same charge, and ternary ion pairs, which contain one divalent ion and two monovalent counterions.

plex, or predict it, and are commonly validated by spectrophotometric methods.

and a base by *proton transfer* [34].

176 Spectroscopic Analyses - Developments and Applications

**2.2. Types of ion pairs**

one solvent molecule is involved) [1].

more used in the pharmaceutical field.

hydrophobic properties and on the solvent nature as well.

chromatography [23, 24, 36] and capillary electrophoresis [37].

Most of the ion-pair spectrophotometric assay methods published in pharmaceutical field are based on UV-Vis molecular absorption. These methods are robust, easy to perform, sensitive, accurate and precise. In association with an organic dye, pharmaceutical substances with no characteristic visible spectrum can be detected in this region.

Widely used are the extractive spectrophotometric methods: the ion pairs are extracted in an organic solvent, and the extract is further analyzed. For the quantitative extraction in the selected organic solvent, the optimum pH value, concentration of the reagents and ionic strength must be established.

The selection of the counterion should consider that bulky, univalent and having the charge distributed over the whole ion reagent has the best capacity to form ion pairs. With respect to the geometry of the counterion, planar types of organic dyes are appropriate for developing ion-pair absorption spectrophotometric methods [41]. Computational chemistry is a useful tool to evaluate the volume, geometry and charge density of the studied substances. By correlating these data with the results of the studies on the solvation of different types of ion pairs [29], the selection of the optimum solvent for the extraction is simplified.

The formation of the ion pair can be revealed spectrophotometrically by a shift of the absorption peak of the chromophore. As an example, the spectral changes that appeared at the formation of terbinafine-methyl orange (TBF-MO) ion pair in chloroform were used for the assay of terbinafine by ion-pair absorption spectrophotometry by Florea et al. [42]. MO is a planar dye containing aromatic rings, and the formation of TBF-MO ion pair is accompanied by a blue shift (from 502 to 408 nm) and hypochromic effect for the visible peak of MO (**Figure 1**). These spectral changes indicate the stabilization of the ion pair by aromatic stacking [31].

**Figure 1.** Molecular absorption spectra of TBF (1), MO (2) and TBF-MO ionic association (3) (from Ref. [42], with permission).

Bromocresol purple (BCP) [43] and alizarin red [44] were also used as counterions in the assay of TBF using extraction methods.

As counterions, the chain-type reagents having long alkyl groups are also useful. They are bulky and univalent, but their charge is not distributed over the whole ion. Even so, the main limitation arises mostly from the fact that they are colourless; therefore, they can be used as ion-pair reagents for the assay of coloured substances.

Hexadecyltrimethylammonium bromide (CTAB) was used to develop an extractive spectrophotometric method for the assay of nimesulide (NS) by Florea et al. [45]. As CTAB is a chaintype reagent, with no aromatic rings in the structure and no characteristic spectrum in UV-Vis region, NS in its ionized form is the reagent having a peak in visible range. Therefore, when the ion pair is formed, a red shift and hyperchromic effect appeared (**Figure 2**).

Sulfonephthalein dyes, such as bromocresol green (BCG), bromocresol purple (BCP) and brilliant blue G [46], were also used as counterions in the assay of NS using extraction-free methods. A comparison of the experimental data indicated a larger linearity range for the method based on the ion pair formed with CTAB.

Because extraction is a laborious procedure, the trends are to develop non-extractive (extraction-free) ion-pair–based spectrophotometric methods in nonaqueous or aqueous solutions. Generally, by dissolving the substances in the organic solvents, the ion pairs are formed mainly by a proton transfer mechanism.

Limitations in the development of non-extractive methods arise mainly from the physicalchemical properties of the reagents, namely, their solubility in the appropriate solvents.

Literature data generally resulted in narrower linearity ranges for the non-extractive methods compared with the extractive ones. Some examples are presented in **Table 1**.

**Figure 2.** Molecular absorption spectra of CTAB (1), NS (2) and CTAB-NS (3) (from Ref. [45], with permission).


**Table 1.** Examples of extractive (E) and non-extractive (NE) ion-pair spectrophotometric methods for the assay of pharmaceutical substances.

#### **3.2. Fluorescence spectroscopy**

Bromocresol purple (BCP) [43] and alizarin red [44] were also used as counterions in the assay

As counterions, the chain-type reagents having long alkyl groups are also useful. They are bulky and univalent, but their charge is not distributed over the whole ion. Even so, the main limitation arises mostly from the fact that they are colourless; therefore, they can be used as

Hexadecyltrimethylammonium bromide (CTAB) was used to develop an extractive spectrophotometric method for the assay of nimesulide (NS) by Florea et al. [45]. As CTAB is a chaintype reagent, with no aromatic rings in the structure and no characteristic spectrum in UV-Vis region, NS in its ionized form is the reagent having a peak in visible range. Therefore, when

Sulfonephthalein dyes, such as bromocresol green (BCG), bromocresol purple (BCP) and brilliant blue G [46], were also used as counterions in the assay of NS using extraction-free methods. A comparison of the experimental data indicated a larger linearity range for the method

Because extraction is a laborious procedure, the trends are to develop non-extractive (extraction-free) ion-pair–based spectrophotometric methods in nonaqueous or aqueous solutions. Generally, by dissolving the substances in the organic solvents, the ion pairs are formed

Limitations in the development of non-extractive methods arise mainly from the physicalchemical properties of the reagents, namely, their solubility in the appropriate solvents.

Literature data generally resulted in narrower linearity ranges for the non-extractive methods

**Figure 2.** Molecular absorption spectra of CTAB (1), NS (2) and CTAB-NS (3) (from Ref. [45], with permission).

compared with the extractive ones. Some examples are presented in **Table 1**.

the ion pair is formed, a red shift and hyperchromic effect appeared (**Figure 2**).

of TBF using extraction methods.

178 Spectroscopic Analyses - Developments and Applications

ion-pair reagents for the assay of coloured substances.

based on the ion pair formed with CTAB.

mainly by a proton transfer mechanism.

Among spectrophotometric methods, fluorimetry distinguishes itself by high sensitivity and specificity. In pharmaceutical sciences, fluorescence spectroscopy is an irreplaceable tool in the study of biochemical processes occurring at the cellular level. Substances having intrinsic fluorescence, named *fluorophores*, have characteristic structural features (rigid, plane structure with conjugated double bounds) and exhibit specific excitation (absorption) and emission (fluorescence) wavelengths, thus explaining the high specificity of the method [56]. Various interactions of the fluorophore with the surroundings can lead to a decrease of the fluorescence intensity. This effect is called quenching and can be used for quantification purposes, primarily for the determination of anions [57]. Molecular mechanisms such as the interaction with electron-deficient molecules (quenchers) in the excited state of the fluorophore (collisional quenching) or in the ground state (formation of non-fluorescent complexes with quenchers), together with different non-molecular effects, can be involved in the quenching process [56].

Ion-pair fluorescence assay methods are generally based on quenching. In the ion-pair structure, if one of the ions is a fluorophore, the counterion can act as a quencher. For a certain concentration range, the decrease of the fluorescence intensity is proportional with the analyte concentration. The development of these methods takes into consideration the same experimental conditions presented at Section 3.1, to obtain a quantitative ion-pair equilibrium (pH, ionic strength, solvent), but it is conditioned by the selection of an optimum fluorophore. Organic substances with native fluorescence that can be used as counterions are few; therefore, there are not many published applications. Literature data on ion-pair fluorescence methods for the assay of pharmaceutical substances are summarized in **Table 2**.


**Table 2.** Examples of extractive and non-extractive ion-pair fluorescence methods for the assay of pharmaceutical substances.

Berberine, an isoquinoline alkaloid, is a pharmacologically active fluorophore, with potential therapeutic effect in various diseases (Alzheimer's disease, cancer, viral infections, etc.). In order to get deeper insights into the details of its biological activity, the effect of the ion pairing on its fluorescence properties was studied using chloride and perchlorates anions [68]. Nanoparticles containing berberine-tetraphenylborate ion pair were prepared, and their ability to cross the cell membrane of cancer cells was studied by Soulié et al. [69].

Lately, the research in nanoscience opened an even wider pathway in fluorescence studies involving ion pairing. Quantum dots (QDs) are prone to exchange electrons with their complementary partners (acceptors or donors) upon excitation that can be transduced into detectable fluorescent signals [70]. Thus, sensitive assay methods can be developed by using QDs capped with different ligands in ionized form. An example is the determination method developed for albendazole, using glutathione-capped cadmium telluride QDs (GSH-CdTe QDs). Ion-pair equilibrium takes place between albendazole in cationic form and anionic sites at the QD surface, and the effect was a decrease of the fluorescence intensity of capped CdTe QDs [70].

Various applications based on ion-pair equilibrium with fluorescence properties were developed along the time for the characterization of biomolecules in complex biological matrices by flow cytometry [71] and also for kinetic studies using fluorescence microscopy [72].

#### **3.3. Light scattering spectrometry**

Berberine, an isoquinoline alkaloid, is a pharmacologically active fluorophore, with potential therapeutic effect in various diseases (Alzheimer's disease, cancer, viral infections, etc.). In order to get deeper insights into the details of its biological activity, the effect of the ion pairing on its fluorescence properties was studied using chloride and perchlorates anions [68]. Nanoparticles containing berberine-tetraphenylborate ion pair were prepared, and their abil-

**Table 2.** Examples of extractive and non-extractive ion-pair fluorescence methods for the assay of pharmaceutical

**Fluorescent reagent Analyte Reference**

Erythrosine B Erythromycin [58] 9,10-Dimethoxyanthracene-2-sulphonate Imipramine [59] Desipramine Amitriptyline Nortriptyline Clomipramine Doxepin

Eosine Astemizole, terfenadine, flunarizine as chelates with Pb2+ [60] Amitriptyline

Eosine (as chelate with Pd2+) Ciprofloxacin [65]

Safranin T Meloxicam [66] 4,5-Dibromofluorescein Ceftazidime [67]

Norfloxacin

Ceftriaxone Cefoperazone

Clomipramine [61] Rosiglitazone [62] Pioglitazone [63] Albendazole [64]

**Extractive methods**

180 Spectroscopic Analyses - Developments and Applications

**Nonextractive methods**

substances.

Lately, the research in nanoscience opened an even wider pathway in fluorescence studies involving ion pairing. Quantum dots (QDs) are prone to exchange electrons with their complementary partners (acceptors or donors) upon excitation that can be transduced into detectable fluorescent signals [70]. Thus, sensitive assay methods can be developed by using QDs capped with different ligands in ionized form. An example is the determination method developed for albendazole, using glutathione-capped cadmium telluride QDs (GSH-CdTe QDs).

ity to cross the cell membrane of cancer cells was studied by Soulié et al. [69].

Light scattering was observed by the Irish physicist John Tyndall in the late 1860s. The eminent British physicist Lord Rayleigh (John Strutt) developed the theoretical basis of electromagnetic wave interaction with particles smaller than the wavelength in the following decades (1870–1899). Now, the scattering of light by particles in a suspension is accepted to be elastic (without change in the wavelength of the incident light) and inelastic (the incident wavelength and the scattered one are different). Rayleigh scattering theory was developed for wavelengths much higher than the dimensions of the scattering particles.

Light scattering is widely used since the 1950s in chemical analysis; turbidimetric and nephelometric methods were developed for the analysis of polydisperse systems. Also, ion-pair–based turbidimetric methods were developed [73–75]. With the development of laser technology, first Raman scattering was separated and developed as an independent technique, allowing the analysis of vibrational and rotational states of a molecule.

Resonance light scattering, also known as resonance Rayleigh scattering (RLS), or enhanced Rayleigh scattering, is a simple, rapid and sensitive method for the study of aggregation of molecules. It was first predicted by Placzek in the mid-1930s and later studied as resonanceenhanced Rayleigh scattering (RERS) for diphenylpolyenes [76], for a series of coumarin dyes [77] and for aggregates containing porphyrins [78].

Starting with the 2000s, a series of studies underlined the utility of the method in the assay of pharmaceuticals as ion pairs with organic dyes [79–81] or using a counterion attached to nanoparticles [82, 83] but also for unravelling of their interaction mechanisms with macromolecules of biological interest (transport proteins, DNA) [84–86]. Recent studies have highlighted the potential of this technique to elucidate the action mechanisms of pharmaceutical substances at the molecular level: the mechanism of interaction of oridonin (natural substance with anticancer effect) with DNA macromolecule was revealed [87]; also, the molecular mechanism by which quercetol affects the bioavailability of propranolol was explained [88].

The ion-pair–based assay methods were developed according to the technique proposed by Pasternack et al. [78]. The RLS spectra are registered using a steady-state spectrofluorometer through synchronous scanning of both monochromators. Near or within the range of the absorption band, an enhancement of the scattered signal is observed, which no longer obeys Rayleigh's law. The effect was largely attributed to a scattering-absorption-re-scattering process. For a certain concentration range, increments in the scattering intensity are directly proportional to the concentration of the analyte.

The majority of the substances determined are hydrophilic organic molecules, largely hydrated in water. The ion pairs are formed mostly by an experimentally conducted hydrophobic ion pairing. An increased ionic strength determines the chemical species involved in the ion pairing to become more hydrophobic because the solvent molecules in their hydration shell are attracted in competitive solvation equilibria of the inorganic ions. Generally, the optimum pH and increased ionic strength are obtained using Britton-Robinson buffer. Molecular absorption spectra are used as a previous step in developing RLS methods. By monitoring changes in the absorption spectra, the optimum counterion is selected, and the experimental conditions for quantitative ionic association equilibrium (pH, ionic strength, reaction time) are established. For example, in the case of streptomycin (STR) assay in ionic association with Congo red (CR) [89], for the Britton-Robinson buffer (pH value 5.5), a maximum blue shift (from 497 to 487 nm) and hypochromic effect were obtained, indicating the quantitative formation of the STR-CR ion pair. In these experimental conditions, maximum scattering intensity was obtained (**Figure 3**).

Resonance light scattering methods have many advantages such as great sensitivity and selectivity, simple experimental procedure and the use of accessible equipment (classical spectrofluorimeter) [90], but no validated methods have been published yet. RLS signals suffer from fluctuations caused by many variable factors such as environmental conditions in the reaction medium (pH, ionic strength, temperature and polarity), reagent concentration and the incident light intensity [91].

The challenge for the analysts is to improve the technique in order to obtain reproducible results. Resonance light scattering ratiometry was proposed and applied to the study of the interaction between porphyrins and heparin, in order to solve the problems correlated with the single wavelength measurement. The method provides precise data by taking the intensity ratio at two suitable wavelengths [91].

**Figure 3.** RLS spectra of CR (1), STR (2) and STR-CR ion pair (3) (from Ref. [89], with permission).

From our experience, slight variations of the ionic strength cause changes in the RLS signal intensity. In routine analysis, it is difficult to obtain identical values of this parameter, and therefore it is difficult to obtain reproducible results. A favourable effect on ion pairing may be obtained by adding small quantities of methanol or ethanol. They have strong waterstructuring effect [92, 93], so the hydrophobic interactions for the ion pair can be enforced by engaging water and alcohol molecules in hydrogen bonds, thus dehydrating the substances of interest.

#### **3.4. Challenges and perspectives in IP spectrophotometry**

Among the permanent challenges in ion-pair spectrophotometry applied in the pharmaceutical field, one can number the increase of the sensitivity, enabling a more comprehensive study of the mechanisms underlying biochemical processes based on ion-pair equilibrium and finding appropriate conditions to obtain ion pairs for novel pharmacologically active substances.

In terms of increasing the sensitivity of the ion-pair–based methods, the best perspectives are offered by the RLS and fluorimetry, especially when the counterions fixed at the surface of QDs (capped QDs) are used. Using post-column ion pairing, RLS method has been incorporated as a detection technique in high-performance liquid chromatography [94] and capillary electrophoresis [95]. Studies are needed to obtain reproducible results of RLS and to validate the assay methods.

Ion pairing is a fundamental interaction in biological systems. Molecular recognition and protein function are biochemical processes based on ion pairing, and obtaining experimental evidence on the dynamics of macromolecules is a challenge. First experimental data on ionpair dynamics at protein-DNA interfaces, obtained using nuclear magnetic resonance spectroscopy, were published by Anderson et al. [96].

Polyphenols, an important group of pharmacologically active substances, have not been characterized in terms of the ability to form pairs. Perspectives are opened by recently published study [97], which evaluates the photodynamic therapeutic effect of the curcumin on breast cancer cells using curcumin-methylene blue ion-pair–based nanoparticles. There are numerous substances in this class to be studied.

#### **4. Conclusions**

The majority of the substances determined are hydrophilic organic molecules, largely hydrated in water. The ion pairs are formed mostly by an experimentally conducted hydrophobic ion pairing. An increased ionic strength determines the chemical species involved in the ion pairing to become more hydrophobic because the solvent molecules in their hydration shell are attracted in competitive solvation equilibria of the inorganic ions. Generally, the optimum pH and increased ionic strength are obtained using Britton-Robinson buffer. Molecular absorption spectra are used as a previous step in developing RLS methods. By monitoring changes in the absorption spectra, the optimum counterion is selected, and the experimental conditions for quantitative ionic association equilibrium (pH, ionic strength, reaction time) are established. For example, in the case of streptomycin (STR) assay in ionic association with Congo red (CR) [89], for the Britton-Robinson buffer (pH value 5.5), a maximum blue shift (from 497 to 487 nm) and hypochromic effect were obtained, indicating the quantitative formation of the STR-CR ion pair. In these experimental conditions, maximum scattering intensity was obtained (**Figure 3**). Resonance light scattering methods have many advantages such as great sensitivity and selectivity, simple experimental procedure and the use of accessible equipment (classical spectrofluorimeter) [90], but no validated methods have been published yet. RLS signals suffer from fluctuations caused by many variable factors such as environmental conditions in the reaction medium (pH, ionic strength, temperature and polarity), reagent concentration and the inci-

The challenge for the analysts is to improve the technique in order to obtain reproducible results. Resonance light scattering ratiometry was proposed and applied to the study of the interaction between porphyrins and heparin, in order to solve the problems correlated with the single wavelength measurement. The method provides precise data by taking the inten-

**Figure 3.** RLS spectra of CR (1), STR (2) and STR-CR ion pair (3) (from Ref. [89], with permission).

dent light intensity [91].

sity ratio at two suitable wavelengths [91].

182 Spectroscopic Analyses - Developments and Applications

The present work underlined the existence of ion-pair spectrophotometry as a distinct group of methods largely used in the pharmaceutical field. Its evolution was dynamic and was correlated with the elucidation of ion-pair formation mechanisms and the development of computational chemistry. In medicines control, ion-pair molecular absorption spectrometry has the most numerous applications. Generally, organic solvents were used as reaction media. With the development of resonance light scattering techniques, the number of the applications of the ion pairs formed in aqueous solution has increased significantly. Fluorimetry, more sensitive, is also used as an assay method but mostly for biochemical purposes.

If one single feature has to be emphasized, the importance of ion-pair spectrophotometric methods in the pharmaceutical field consists in their versatility. Substances with or without characteristic absorption in UV-Vis range or intrinsic fluorescence, hydrophilic or hydrophobic and organic or inorganic, can be determined as ion pairs in bulk or complex matrices using rapid, sensitive and simple procedures.

### **Author details**

Marinela Florea\* and Mihaela Ilie\*

\*Address all correspondence to: florea.marinela@gmail.com; mihaela.ilie@umfcd.ro

Faculty of Pharmacy, Analytical Chemistry Department, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania

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If one single feature has to be emphasized, the importance of ion-pair spectrophotometric methods in the pharmaceutical field consists in their versatility. Substances with or without characteristic absorption in UV-Vis range or intrinsic fluorescence, hydrophilic or hydrophobic and organic or inorganic, can be determined as ion pairs in bulk or complex matrices using

\*Address all correspondence to: florea.marinela@gmail.com; mihaela.ilie@umfcd.ro

https://goldbook.iupac.org/I03231.html [Accessed: 25 February 2017]

Faculty of Pharmacy, Analytical Chemistry Department, "Carol Davila" University of Medicine

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190 Spectroscopic Analyses - Developments and Applications


## **Application of Flow-Injection Spectrophotometry to Pharmaceutical and Biomedical Analyses**

Bruno E.S. Costa, Henrique P. Rezende, Liliam Q. Tavares, Luciana M. Coelho, Nívia M.M. Coelho, Priscila A.R. Sousa and Thais S. Néri

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.70160

#### **Abstract**

The discovery of new drugs, especially when many samples have to be analyzed in the minimum of time, demand the improvement or development of new analytical methods. Various techniques may be employed for this purpose. In this context, this chapter gathers the collection of paper and represents the review of past work on spectrophotometric technique coupled to a continuous flow system to determine low concentrations of several chemical species in different kinds of pharmaceutical and biological samples. A short historical background of the flow-injection analysis technique and a brief discussion of the basic principles and potential are presented. Part of this chapter is devoted to describing the sample preparation techniques, principles, and figures of merit of analytical methods. Representative applications of flow-injection spectrophotometry to pharmaceutical and biomedical analysis are also described.

**Keywords:** pharmaceutical, biomedical samples, flow-injection, spectrophotometry

#### **1. Introduction**

The monitoring of chemical species in pharmaceutical and biomedical samples is a field in which analytical chemistry plays an important role, contributing new procedures of analysis and instrumentation. Many methods have been developed for pharmaceutical and biomedical analysis including chromatographic, electrophoretic, and spectrophotometric methods. However, there are inherent difficulties associated with the types of samples involved. The

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

most practical difficulty encountered is the preservation and integrity of the species during sampling, storage, and sample pretreatment. In the medical area, the main matrices are blood, serum, and urine, while in the pharmaceutical industry, there are many types of samples and variations in their compositions. This hinders the application of analytical techniques for the fast and accurate monitoring of pharmaceutical and biomedical species in real samples.

Spectrophotometry is the technique most commonly employed in chemical analysis, and it provides advantages in terms of the availability of instruments, simplicity of procedures, speed, precision, accuracy, and applicability to a wide range of bio-medically important substances. Due to recent advances, increasing attention is being given to the coupling of a spectrometer to a continuous flow system to determine low concentrations of several chemical species in different kinds of pharmaceutical and biological samples. The flow-injection analysis technique has found wide application, which can be mainly attributed to its versatility, ease of automation, high sampling frequency, and the requirement for minimum sample treatment prior to injection into the system.

This chapter draws attention to some of the important and unique aspects of the applications of flow-injection spectrophotometry, addressed within the context of pharmaceutical and biomedical analysis. A short historical background of the flow-injection analysis technique and a brief discussion of the basic principles and potential are presented.

A notable feature of this chapter is the large number of papers on chemiluminescence discussed herein. In addition, considerable attention is given to sample preparation techniques and the characteristics of analytical methods such as precision, accuracy, and sampling frequency. Representative applications of flow-injection spectrophotometry to pharmaceutical and biomedical analysis are also described.

#### **2. FIA origin and development**

The process of flow-injection analysis (FIA) was initially proposed in the 1970s by Prof. Dr. Jaromir Ruzicka of the Technical University of Denmark and was subsequently consolidated as a state-of-the-art technology for the automation and mechanization of chemical systems. At that time, the cited researcher spent a year in Brazil advising on the installation of the Laboratory of Analytical Chemistry at the Center of Nuclear Energy in Agriculture of the University of São Paulo (CENA/USP), where pioneering work was carried out that led to the FIA process becoming very well established. Since its introduction, more than 20,000 papers have been published reporting the development of advanced instrumentation methods in the context of chemical analysis, which are available for environmental, food, and clinical services involving pharmaceutical and biomedical samples [1, 2].

The FIA process involves the insertion of the sample into a carrier fluid that transports it to a suitable detection system. During this process, the sample can be brought into contact with reagents that are also inserted by propulsion, resulting in a controlled dispersion of the sample. The processes that characterize FIA systems have gained great prominence in contemporary analytical chemistry since several limitations have been overcome in the development of improved analytical procedures.

The origin and development of flow analysis systems was strongly influenced by the work of Skeggs, who proposed an approach called continuous flow analysis (CFA) [3]. For approximately 20 years, it was accepted that segmentation by dividing the flow into small regular compartments separated by air bubbles was the best strategy to avoid contamination and the widening of the discrete zone of the sample along the course, which is known today as dispersion [3–5]. It was only in the mid-1970s that it was widely accepted that segmentation could be omitted following an innovative proposal for a method employing the continuous flow of the samples and reagents with adequate dimensions and flow rates. The system was subsequently simplified, increasing the frequency of samples analyzed per unit of time, referred to as the analytical frequency. Due to the advantage of good reproducibility offered by FIA systems, it has also become possible to quantify the analyte even before the reaction between the sample and the reagent reaches equilibrium since the interval between the injection and detection is the same for the standard solutions and the sample.

most practical difficulty encountered is the preservation and integrity of the species during sampling, storage, and sample pretreatment. In the medical area, the main matrices are blood, serum, and urine, while in the pharmaceutical industry, there are many types of samples and variations in their compositions. This hinders the application of analytical techniques for the fast and accurate monitoring of pharmaceutical and biomedical species in real samples.

Spectrophotometry is the technique most commonly employed in chemical analysis, and it provides advantages in terms of the availability of instruments, simplicity of procedures, speed, precision, accuracy, and applicability to a wide range of bio-medically important substances. Due to recent advances, increasing attention is being given to the coupling of a spectrometer to a continuous flow system to determine low concentrations of several chemical species in different kinds of pharmaceutical and biological samples. The flow-injection analysis technique has found wide application, which can be mainly attributed to its versatility, ease of automation, high sampling frequency, and the requirement for minimum sample treatment prior to injection into the system. This chapter draws attention to some of the important and unique aspects of the applications of flow-injection spectrophotometry, addressed within the context of pharmaceutical and biomedical analysis. A short historical background of the flow-injection analysis technique and a

A notable feature of this chapter is the large number of papers on chemiluminescence discussed herein. In addition, considerable attention is given to sample preparation techniques and the characteristics of analytical methods such as precision, accuracy, and sampling frequency. Representative applications of flow-injection spectrophotometry to pharmaceutical

The process of flow-injection analysis (FIA) was initially proposed in the 1970s by Prof. Dr. Jaromir Ruzicka of the Technical University of Denmark and was subsequently consolidated as a state-of-the-art technology for the automation and mechanization of chemical systems. At that time, the cited researcher spent a year in Brazil advising on the installation of the Laboratory of Analytical Chemistry at the Center of Nuclear Energy in Agriculture of the University of São Paulo (CENA/USP), where pioneering work was carried out that led to the FIA process becoming very well established. Since its introduction, more than 20,000 papers have been published reporting the development of advanced instrumentation methods in the context of chemical analysis, which are available for environmental, food, and

The FIA process involves the insertion of the sample into a carrier fluid that transports it to a suitable detection system. During this process, the sample can be brought into contact with reagents that are also inserted by propulsion, resulting in a controlled dispersion of the sample. The processes that characterize FIA systems have gained great prominence in contemporary analytical chemistry since several limitations have been overcome in the development of

clinical services involving pharmaceutical and biomedical samples [1, 2].

brief discussion of the basic principles and potential are presented.

and biomedical analysis are also described.

194 Spectroscopic Analyses - Developments and Applications

**2. FIA origin and development**

improved analytical procedures.

In general, the FIA process consists of fluid propulsion, usually performed by a peristaltic pump that operates at constant flow, sample injection, reaction promoted in a homogenizing mixing coil with suitable geometry and a compatible detection technique, such as molecular spectrometry and atomic, chromatographic, and electroanalytical techniques.

Initially, Ruzicka used a hypodermic syringe to promote the injection of the sample, which gave rise to the name of the process [6]. Since then, other devices have been proposed for the insertion of the sample into the loader fluid, such as the proportional commutator injector and the rotary valve. The FIA systems have thus evolved and independent injections by multicomutation can be performed, enabling binary sampling [7]. In recent years, FIA systems have evolved in ways that have led to the development of sequential injection analysis (SIA) systems. In this case, the injection of the sample and the contact with the reagent flow occur through the selection of the port of a central selector valve in which the mixture is provided with bi-directional movement, alternating the propulsion direction occurring in a single line, in the absence of confluences [2, 8]. Due to these characteristics, SIA systems can be considered as differentiated from conventional FIA systems.

The classification of FIA systems has become necessary considering the variety of analytical procedures available. This can be based on the way in which the sample is introduced (continuous or intermittent) and on the flow characteristic (segmented, monosegmented, nonsegmented). **Figure 1** shows a classification scheme for flow analysis methods.

FIA systems have become commonly used and a number of variations in the configurations have been proposed in order to minimize the consumption of sample and reagents and to enhance the sensitivity of detection and the selectivity and precision of the analytical measurements.

The simplest configuration is the single-line flow diagram, where the loading fluid is the reagent itself, and the mixing occurs exclusively by dispersion. When the ratio between the volumes of the injected sample aliquot and its pathway is inappropriate, the addition of reagents by confluence may provide a more effective reaction where inert solutions, such as carriers, are employed. In order to overcome the excessive waste of reagents, which are continuously consumed, the system of flow injection through coalescing zones was proposed,

**Figure 1.** Schematic diagram of classification of flow analysis procedures.

thus minimizing the amount of waste generated. Since then, FIA systems have proven to be highly versatile and robust, making it possible to obtain strategically various arrangements and configurations that have been satisfactorily employed for extractive, separation, and preconcentration purposes. In addition, there are a number of approaches through which clinical formulation products can be efficiently monitored for the certification of their quality.

### **3. Spectrophotometric flow-injection procedures for pharmaceutical samples**

Spectrophotometric methods are the most commonly used techniques in chemical analysis due to the availability of instruments, simplicity of procedures, precision, and wide applicability. Based on the laws governing absorption and emission phenomena, it is possible to determine the concentrations of compounds in solutions, notably those of biological, chemical, or pharmaceutical interest [9].

Drug analysis, involving the pharmaceutical preparations or the raw materials used for their production, and the determination of drugs together with metabolites in biological samples (serum, plasma, saliva, urine, and some secretions) constitutes a large part of the activities carried out by pharmaceutical and clinical laboratories.

Spectrophotometry is the most commonly used technique for the determination of drugs, and it is based on chromogenic reactions or light absorption by the analyte. Chromogenic reactions for drugs include metal-ion complexes, redox reactions, and the formation of chargetransfer complexes.

Some of the flow-injection spectrophotometry procedures for the quantification of pharmaceutical samples [10–14] are detailed in **Table 1**. An important observation is the choice of carrier, aiming to avoid matrix effects and even clogging of the flow channels due to precipitation [14, 15].

Flow techniques, characterized by great flexibility, versatility, and ease of automation, allow the development and implementation of many analytical systems, which are compatible with a wide range of sample manipulation techniques, under highly reproducible conditions. Some flow-injection procedures are based on oxidation-reduction reactions. For the determination of N-acetyl-L-cysteine [16], this procedure involves the oxidation of the analyte of interest by Fe(III). The Fe(II) produced can be determined using 1,10-phenanthroline, and the chromophore formed is analyzed at 510 nm. On-line oxidation by Ce(IV) in acid medium—a procedure based on oxy-reduction—has been used to determine pyrazine. The colored free radical produced by the reaction was monitored at 510 nm [17].

Other procedures are based on the formation of a colored complex between the analyte of interest and metal-ions. For example, the determination of cimetidine with Cu(II) in acetate buffer (pH 5.9) can be carried out at a wavelength of 330 nm [18] and epinephrine with Fe(II) in amino acetic carbonate buffer (pH 8.3) at a wavelength of 530 nm [19].

A procedure for the determination of paracetamol (4-acetaminophen) has been described by Fatibello-Filho and Vieira [20]. The method is based on paracetamol oxidation by sodium hypochlorite, and the determination of the oxidant using o-toluidine dichloride as the chromogenic reagent at 430 nm. The analytical curve for paracetamol was linear in the concentration range of 8.50 × 10−6 to 2.51 × 10−4 mol L−1 with a detection limit of 5.0 × 10−6 mol L−1. The relative standard deviation was less than 1.2% for a paracetamol solution of 1.20 × 10−4 mol L−1 (*n* = 10).

thus minimizing the amount of waste generated. Since then, FIA systems have proven to be highly versatile and robust, making it possible to obtain strategically various arrangements and configurations that have been satisfactorily employed for extractive, separation, and preconcentration purposes. In addition, there are a number of approaches through which clinical

formulation products can be efficiently monitored for the certification of their quality.

**3. Spectrophotometric flow-injection procedures for pharmaceutical** 

Spectrophotometric methods are the most commonly used techniques in chemical analysis due to the availability of instruments, simplicity of procedures, precision, and wide applicability. Based on the laws governing absorption and emission phenomena, it is possible to determine the concentrations of compounds in solutions, notably those of biological, chemi-

Drug analysis, involving the pharmaceutical preparations or the raw materials used for their production, and the determination of drugs together with metabolites in biological samples (serum, plasma, saliva, urine, and some secretions) constitutes a large part of the activities

Spectrophotometry is the most commonly used technique for the determination of drugs, and it is based on chromogenic reactions or light absorption by the analyte. Chromogenic reactions for drugs include metal-ion complexes, redox reactions, and the formation of charge-

**samples**

cal, or pharmaceutical interest [9].

transfer complexes.

carried out by pharmaceutical and clinical laboratories.

**Figure 1.** Schematic diagram of classification of flow analysis procedures.

196 Spectroscopic Analyses - Developments and Applications


**Table 1.** Flow-injection spectrophotometry procedures for the quantification of pharmaceutical samples.

Many methods for the determination of pharmaceuticals also involve the flow-injection procedure based on homogeneous reactions. For example, the indirect determination of olanzapine from the reaction with hexacyanoferrate (III) in which the measurement of the unreacted


**Table 2.** FIA procedures using based on color-forming reactions.

oxidant is collected at 425 nm [21]. Diclofenac and mefenamic acid can also be oxidized in a flow system by hexacyanoferrate (III) and spectrophotometrically determined [22]. Other analytes that can be determined in homogeneous reactions are shown in **Table 2**.

#### **4. Spectrophotometric flow-injection procedures for biomedical samples**

The FIA technique can be coupled to various detection systems, such as a spectrophotometer, which allows a wide range of analytical devices to be combined [32].

A flow-injection analysis procedure using spectrophotometry was used to determine urea in blood plasma, employing the legume *Cajanus cajan* as a source of urease enzyme, in a minicolumn coupled to the FIA collector. A confidence level of 90% and a relative standard deviation of 1.4% (*n* = 12) were obtained [33]. In another study, the development of a flow analysis procedure for the determination of total protein in a bovine blood plasma was carried out using the Biuret method. Samples of bovine plasma with 12.5 and 100.0 g L−1 of total protein were analyzed, and the analytical range was 2.5–20.0 g L−1. The relative standard deviation of the procedure was 2.8%, and the analytical frequency was 76 determinations per hour. The results were compared with the traditional method of analysis (Biuret), and no statistically significant differences were observed at the 95% confidence level [34].

Sensors based on optical techniques are widely applied in different types of analysis, including biomedical sensing, and when connected to flow-injection analysis, a much faster analysis procedure is obtained [35]. In this context, a multicomutation flow system was used, which incorporates a sol-gel optical sensor (sensor: base catalyzed 4-(2-pyridylazo) resorcinol (PAR)) for the spectrophotometric determination of Cu(II) in urine samples using a photodiode detector with a maximum absorbance at 500 nm. The results were in agreement with those obtained by inductively coupled plasma mass spectrometry (ICP-MS), with a confidence level of 95% [35].

A FIA system was used to determine copper and zinc in water, pharmaceuticals, soils, and human hair samples. The product of the reaction with 2-carboxyl-2-hydroxy-5-sulfoformazylbenzene (Zincon) was introduced into a stream of carrier solution in the flow system. A sequential reaction of Cu(II) and Zn(II) was performed using Zincon, with the formation of two complexes and monitoring at 627 nm [36].

A flow procedure with spectrophotometric detection to determine bromopride in different matrices has been studied [37]. To increase the sensitivity of the reaction, a micellar medium (sodium dodecyl sulfate—SDS) was employed. Factorial planning was carried out to optimize the experimental parameters. The limit of detection was 1.07 × 10−7 mol L−1. The method developed was satisfactorily applied in the determination of bromopride in pharmaceuticals and human urine, and recoveries were in the ranges 99.6–101.2 and 98.6–102.1%, respectively.

The application of a very sensitive and selective on-line flow-injection method for the determination of thorium(IV) after preconcentration in a minicolumn with N-benzoylphenylhydroxylamine-impregnated XAD-4 resin to biological samples has been described [38]. Sample rates of 40 and 11 h−1 were obtained at the 60 and 300 seconds preconcentration times, respectively; the preconcentration factors were 32 and 162, with detection limits of 0.76 and 0.150 μg L−1, respectively [38].

oxidant is collected at 425 nm [21]. Diclofenac and mefenamic acid can also be oxidized in a flow system by hexacyanoferrate (III) and spectrophotometrically determined [22]. Other

**4. Spectrophotometric flow-injection procedures for biomedical samples**

The FIA technique can be coupled to various detection systems, such as a spectrophotometer,

A flow-injection analysis procedure using spectrophotometry was used to determine urea in blood plasma, employing the legume *Cajanus cajan* as a source of urease enzyme, in a minicolumn coupled to the FIA collector. A confidence level of 90% and a relative standard deviation of 1.4% (*n* = 12) were obtained [33]. In another study, the development of a flow analysis procedure for the determination of total protein in a bovine blood plasma was carried out using the Biuret method. Samples of bovine plasma with 12.5 and 100.0 g L−1 of total protein were analyzed, and the analytical range was 2.5–20.0 g L−1. The relative standard deviation of the procedure was 2.8%, and the analytical frequency was 76 determinations per hour. The results were compared with the traditional method of analysis (Biuret), and no statistically

Sensors based on optical techniques are widely applied in different types of analysis, including biomedical sensing, and when connected to flow-injection analysis, a much faster analysis

analytes that can be determined in homogeneous reactions are shown in **Table 2**.

**Analyte Methodology Detection limit** 

Isoproterenol Oxidation by polyphenol oxidase immobilized on controlled-pore silica.

198 Spectroscopic Analyses - Developments and Applications

Dipyrone Reaction with ammonium molybdate to produce molybdenum blue.

(MCR-ALS) algorithm.

**Table 2.** FIA procedures using based on color-forming reactions.

Vitamin B complex (B1, B6, B12, and benfotiamine)

Promethazine and trifluoperazine

Paracetamol Reaction with sodium hypochlorite followed by reaction with sodium salicylate.

Levofloxacin Oxidation with N-bromosuccinimide. 3.0 [23] Benzylpenicillin Derivatization with 4,6-dinitrobenzenofuroxane. 0.14 [24]

> Multicomponent spectrophotometric analysis using Multivariate Curve Resolution Alternating Least Squares

Bead injection spectroscopy-flow injection analysis (BIS-FIA) system and spectrophotometric detection.

Flutamide Detection by electrospray ionization mass spectrometry. 0.001 [30] Lansoprazole Detection by electro spray ionization mass spectrometry. 0.0055 [31]

**(mg L−1)**

13.2 [25]

0.4 [26]

32 [27]

0.0009–0.016 [28]

0.00009–0.00014 [29]

**Ref.**

which allows a wide range of analytical devices to be combined [32].

significant differences were observed at the 95% confidence level [34].

Sarcosine has been investigated as a new marker for prostate cancer. A method for detecting sarcosine in biological samples (urine or blood plasma) has been proposed [39]. Ion exchange liquid chromatography with photometric detection at 570 nm was used as a separation method, which proved insufficient for the detection of sarcosine (70 μM). An off-line approach to the ninhydrin derivatization of the fractions collected was optimized, after which a known amount of ninhydrin was added followed by incubation of the mixture under the optimized temperature and time conditions. FIA system with electrochemical detection was used. In this case, 5 μL of sample was injected through a manual valve with a cell phase flow rate of 1 mL min−1 and spectrophotometric detection in the wavelength range of 450–800 nm. A detection limit of 1.7 μM was obtained for sarcosine [39].

#### **5. On-line sample processing methods for in flow analysis**

Flow analysis systems are widely used in analytical chemistry, contributing to increased reproducibility and accuracy of the methods. They also enable a reduction in the reagent consumption and the development of cleaner methods, meeting the requirements of "green" chemistry.

However, there are still limitations inherent to the procedures involved in preparing the samples, and these need to be suitable for each matrix.

Several procedures for analyzing pharmaceutical and biological samples have been developed where the sample preparation method performed on a laboratory bench is replaced by a flow procedure coupled directly to the instrument (spectrometer, chromatograph, electrophoresis unit, etc.). This increases the reliability of the method since it minimizes the potential for contamination inherent to the analysis, increases the reproducibility of the results, and increases the analytical frequency. These characteristics are due to the automation and processing of samples in closed systems under highly reproducible mixing and timing conditions. One of the factors that contributes to the success of this sample processing procedure carried out in closed systems is the combination of techniques and methodologies, known as hyphenation, which promotes faster analysis that is more efficient with less interference. The pretreatment of pharmaceutical and biological samples in flow is an important step in closed systems. Due to the complexity of these samples, the determination of chemical species presents significant challenges [40]. Thus, different types of procedures can be developed for the preparation of on-line samples for each matrix, according to its characteristics, such as solid phase extraction, solid phase microextraction, liquid-liquid microextraction, and chemical derivatization.

Some articles using on-line processes for the determination of compounds in pharmaceutical and biological samples are shown in **Table 3**. Two on-line procedures have been reported for the determination of ranitidine: chemiluminescence and UV-Vis detection [41, 42]. Several methodologies for the on-line preparation of saliva samples with detection by UV-Vis [43], ICP-OES [44], and AFS [45] are described in the literature.


**Table 3.** On-line treatment procedures for pharmaceutical and biological samples using spectrometric techniques.

The complexity of the matrices of the pharmaceutical and biomedical samples requires an efficient decomposition process, without losing the necessary characteristics for a precise quantification, maintaining the integrity of the analyte. The use of microwave radiation energy was found to be an efficient alternative to conventional sample preparation methods since the processing time is reduced, minimizing problems associated with the loss of the more volatile components. In spite of these advantages, the process requires the manual transfer of volumes, addition of reagents, and excessive dilutions, which are all potential sources of errors, for instance, contamination. The mechanization of the microwave sample preparation processes in a continuous stream decomposition system has contributed to improving the sample processing and, therefore, the analytical performance of the method.

However, there are still limitations inherent to the procedures involved in preparing the sam-

Several procedures for analyzing pharmaceutical and biological samples have been developed where the sample preparation method performed on a laboratory bench is replaced by a flow procedure coupled directly to the instrument (spectrometer, chromatograph, electrophoresis unit, etc.). This increases the reliability of the method since it minimizes the potential for contamination inherent to the analysis, increases the reproducibility of the results, and increases the analytical frequency. These characteristics are due to the automation and processing of samples in closed systems under highly reproducible mixing and timing conditions. One of the factors that contributes to the success of this sample processing procedure carried out in closed systems is the combination of techniques and methodologies, known as hyphenation, which promotes faster analysis that is more efficient with less interference. The pretreatment of pharmaceutical and biological samples in flow is an important step in closed systems. Due to the complexity of these samples, the determination of chemical species presents significant challenges [40]. Thus, different types of procedures can be developed for the preparation of on-line samples for each matrix, according to its characteristics, such as solid phase extraction, solid phase microextraction, liquid-liquid microextraction, and chemical

Some articles using on-line processes for the determination of compounds in pharmaceutical and biological samples are shown in **Table 3**. Two on-line procedures have been reported for the determination of ranitidine: chemiluminescence and UV-Vis detection [41, 42]. Several methodologies for the on-line preparation of saliva samples with detection by UV-Vis [43],

**Sample Detection technique Strategies for analysis Ref.**

For Ru(bipy)<sup>3</sup>

solutions.

Ranitidine UV-Vis Injected samples were analyzed by spectrophotometry

Saliva UV-Vis Analytical procedure involving extraction and

Saliva ICP-OES The analytical procedure involved extraction by

Saliva AFS The flow system was equipped with a microwave and

**Table 3.** On-line treatment procedures for pharmaceutical and biological samples using spectrometric techniques.

2+ chemiluminescence, a sulfuric acid

3+

[41]

[42]

[43]

[44]

[45]

carrier stream was employed into which Ru(bipy)<sup>3</sup>

and sulfuric acid was injected (20 μL), while a second stream delivered the analyte standard and sample

at 313 and at 615 nm after reaction with 3-methyl-2-

benzothiazolinone and ferric chloride.

UV Analytical procedure was solid phase extraction. [46]

preconcentration using 5-BrDMPAP.

sorption and elution of the analytes.

an ultraviolet photo-oxidation system.

ples, and these need to be suitable for each matrix.

200 Spectroscopic Analyses - Developments and Applications

ICP-OES [44], and AFS [45] are described in the literature.

chemiluminescence

FIA-

derivatization.

Ranitidine and salbutamol

Sulfamethoxazole and trimethoprim

The use of flow systems coupled to a microwave oven for the preparation of samples was first proposed by Burguera *et al*. [47], where urine samples were decomposed for further determination of lead. A volume of up to 100 μL of the sample was decomposed using a home microwave oven with a maximum power of 700 W and a 100 μL mixture of 0.4 M HNO<sup>3</sup> and 0.3 M HCl. The application of this system allowed an analytical frequency of 80 samples per hour. Since the first work of exploring the coupling of a microwave oven and a flow system, several systems have been developed and applied to a wide variety of samples, for instance, water, effluents, plants, food and minerals, along with biological fluids and tissues. The analysis of biological fluids is of great importance since it allows the diagnosis of various diseases, nutritional, and metabolic research, therapeutic monitoring involving the biological action of some metals, such as calcium, magnesium, iron, cobalt, zinc, and manganese, and the detection of some drugs (including cocaine and marijuana) [48, 49].

Coelho and collaborators developed an on-line decomposition system for urine samples using a microwave oven prior to the determination of calcium and magnesium by flame atomic absorption spectrometry (FAAS). The decomposition efficiency allowed a rapid treatment of the urine sample with an analytical frequency of 45 samples per hour. The system consisted of three decomposition coils inserted into the cavity of the microwave oven and a valve that allowed the interruption of the passage of the flow and confined the sample to the inside of the oven [50].

The preparation of flow samples in biomedical and pharmaceutical matrices employing spectroscopic techniques remains a challenge, and few studies have been reported in the literature when compared with the chromatographic methods. When spectrometric techniques are subjected to hyphenation, they are promising for the preparation of one or more samples, since the on-line detection systems cited in the literature favor a decrease in the use of batch procedures, thus minimizing the potential for contamination and automating the sample processing procedure.

#### **6. Combination of FIA and other analytical systems**

The advance of laboratory research has enabled the identification and quantification of analytes, individually or simultaneously.

One of the techniques that has contributed to the simultaneous determination of analytes is FIA system combined with other analytical systems, such as high performance liquid chromatography (HPLC), enzymatic reactions, gas chromatography, biosensors, electrophoresis, electrochemical, and immunoassays. According to Saurina [51], in most cases, these combinations enable analysts to detect and quantify up to three compounds simultaneously. The methods required to increase this number may not be compatible with the physical resources used in systems involving flow injection.

The combination of the FIA system with other analytical techniques enables reductions in the analysis time and the reagent/sample consumption and improved accuracy, sensitivity, selectivity, and sampling frequency. In addition, the analyst's contact with the sample is minimized, decreasing the potential for contamination. Thus, by combining the pretreatment (digestion, preconcentration, sample clean-up, and solvent-solvent extraction, etc.) with on-line sample introduction, the FIA system becomes a very efficient and advantageous technique [52–57].

In this context, the possibility of detecting multianalytes using various techniques involving the combination of the FIA system with other traditional analysis systems should be highlighted. Different separation and sample pretreatment procedures can be performed using detection techniques such as fluorescence, spectrophotometry, and electrochemistry, enabling the detection of innumerable analytes, including those present in samples involved in biological applications [58–63].

Several approaches to detection have been used, and electrochemical detectors are prominent in the scientific literature, notably in studies involving conventional amperometric detection coupled to an FIA system. The main characteristics of this combination are increased sensitivity, minimized contamination of the surface of the working electrode, the presence of negligible capacitive current and *in situ* measurement, etc. A limitation associated with this system is the instability of the electrochemical signal during the determination of some compounds, compromising the repeatability of the response and the reproducibility of the results [64].

Another example of combining FIA and an electrochemical system is found in the studies of Chaves *et al.* [65] in which three compounds were determined simultaneously: caffeine, ibuprofen, and paracetamol. The authors report results obtained by combining FIA with multiple pulse amperometry (MPA) using a wall-jet flow cell with a boron-doped diamond electrode. In this analysis, cyclic voltammetry (50 mVs−1) was used.

According to Llorent-Martinez *et al.* [66] and Oliveira *et al.* [67], most of the methods involving detection by UV-Vis using flow procedures offer many advantageous of this combination, being simple, fast and direct methods offering good selectivity and sensitivity in the separation and/or preconcentration steps.

Vidal *et al.* [68] address the simultaneous determination of a mixture of three analytes that are often combined in pharmaceutical formulations: two analgesics (paracetamol and propyphenazone) and a stimulant drug (caffeine). The quantification was performed by separating the three compounds using an FIA system combined with a precolumn containing C18 silica gel to avoid spectral overlap of the compounds under analysis. The detection was conducted with a spectrophotometric detector through UV absorbance measurements. The results were satisfactory, since the compounds were quantified at low concentration ranges, that is, 25–350 μg mL−1 for paracetamol, 5–75 μg mL−1 for caffeine, and 15–150 μg mL−1 for propylphenazone. Also, the proposed method provided low detection limits ranging from 0.65 to 7.5 μg mL−1.

One of the techniques that has contributed to the simultaneous determination of analytes is FIA system combined with other analytical systems, such as high performance liquid chromatography (HPLC), enzymatic reactions, gas chromatography, biosensors, electrophoresis, electrochemical, and immunoassays. According to Saurina [51], in most cases, these combinations enable analysts to detect and quantify up to three compounds simultaneously. The methods required to increase this number may not be compatible with the physical resources

The combination of the FIA system with other analytical techniques enables reductions in the analysis time and the reagent/sample consumption and improved accuracy, sensitivity, selectivity, and sampling frequency. In addition, the analyst's contact with the sample is minimized, decreasing the potential for contamination. Thus, by combining the pretreatment (digestion, preconcentration, sample clean-up, and solvent-solvent extraction, etc.) with on-line sample introduction, the FIA system becomes a very efficient and advantageous technique [52–57].

In this context, the possibility of detecting multianalytes using various techniques involving the combination of the FIA system with other traditional analysis systems should be highlighted. Different separation and sample pretreatment procedures can be performed using detection techniques such as fluorescence, spectrophotometry, and electrochemistry, enabling the detection of innumerable analytes, including those present in samples involved

Several approaches to detection have been used, and electrochemical detectors are prominent in the scientific literature, notably in studies involving conventional amperometric detection coupled to an FIA system. The main characteristics of this combination are increased sensitivity, minimized contamination of the surface of the working electrode, the presence of negligible capacitive current and *in situ* measurement, etc. A limitation associated with this system is the instability of the electrochemical signal during the determination of some compounds, compromising the repeatability of the response and the reproducibility of the results [64].

Another example of combining FIA and an electrochemical system is found in the studies of Chaves *et al.* [65] in which three compounds were determined simultaneously: caffeine, ibuprofen, and paracetamol. The authors report results obtained by combining FIA with multiple pulse amperometry (MPA) using a wall-jet flow cell with a boron-doped diamond electrode.

According to Llorent-Martinez *et al.* [66] and Oliveira *et al.* [67], most of the methods involving detection by UV-Vis using flow procedures offer many advantageous of this combination, being simple, fast and direct methods offering good selectivity and sensitivity in the separa-

Vidal *et al.* [68] address the simultaneous determination of a mixture of three analytes that are often combined in pharmaceutical formulations: two analgesics (paracetamol and propyphenazone) and a stimulant drug (caffeine). The quantification was performed by separating the three compounds using an FIA system combined with a precolumn containing C18 silica gel to avoid spectral overlap of the compounds under analysis. The detection was conducted with a spectrophotometric detector through UV absorbance measurements. The

used in systems involving flow injection.

202 Spectroscopic Analyses - Developments and Applications

in biological applications [58–63].

tion and/or preconcentration steps.

In this analysis, cyclic voltammetry (50 mVs−1) was used.

Pistonesia *et al.* [69] carried out the simultaneous analysis of levodopa and benserazide in tablets of pharmaceutical formulations. The samples were not subjected to pretreatment, and the reaction mixture containing the sample and potassium periodate was directed to a flow cell (8 μL inner volume) inserted in a spectrophotometer with a UV-Vis diode array detector. The concentrations used for the construction of the calibration curves analyzed were 4.1 × 10−4 to 2.03 × 10−3 M for levodopa and 8.5 × 10−5 to 4.25 × 10−4 M for benserazide. During the analysis, the FIA system variables (flow velocity, reactor length, and injected volumes) were optimized and the validation of the method (considering the robustness, repeatability, reproducibility, and accuracy) was studied. The kinetic-spectrophotometric data provided by the diode array detection were treated applying partial least squares (PLS) multidimensional regression. Samples were injected into the HPLC system using preoptimized conditions. The results obtained using the HPLC analysis (197 and 49 for levodopa and benserazide, respectively) and the FIA/PLS system (200 and 48 for levodopa and benserazide, respectively) showed no discrepancy. Thus, a simple, fast, and direct method was obtained through the implementation of a flow-injection system coupled to UV-visible diode spectrophotometry.

Regarding the analysis of biological samples, Reis and Luca [70] described a procedure for the determination of total protein in bovine blood plasma using a FIA system. The use of the FIA system enabled the in-line dilution of bovine plasma samples containing between 12.5 and 100.0 g L−1 total protein. The conditions for the flow analysis were optimized and the results, when compared to those obtained with the traditional method (Biuret), did not indicate significant statistical differences (*t*-paired test) at the 95% confidence level. The proposed method provided fast results, low reagent consumption, and minimization of the sample handling, as well as an analytical frequency of 76 determinations per hour.

In addition to the combination of the FIA system with innumerous detectors, the coupling of flow analysis with pretreatment and separation systems has been employed in some studies, especially FIA combined with capillary electrophoresis (CE). The first studies involving this coupling were described in 1997 by Kuban *et al.* [71] and Fang *et al.* [72]. They described this as an advantageous combination, capable of overcoming certain limitations presented by CE, such as low sensitivity, precision, and analytical frequency. An important feature is that the sample pretreatment step in the FIA-CE system is performed online, minimizing the potential for sample contamination.

Numerous studies involving FIA-CE have been reported in the literature notably: Kuban and Karlberg [73] carried out the determination of small anions through dialysis; Chen and Fang [74] performed the preconcentration of samples; Arce *et al.* [75] determined cations and anions; Chen and Fang [74] monitored multi-components in drugs; Kuban *et al.* [76] determined trimethoprim and sulfamethoxazole in drug samples; and Kuban and Karlberg [77] determined pseudoephedrine in human plasma.

An example of an FIA-CE system is also described in a paper by Liu *et al.* [78], which proposes a method developed through the combination of flow injection and CE for the separation and determination of paracetamol (Par), pseudoephedrine hydrochloride (Pse), dextromethorphan, potassium bromide (Dex), and chlorphenamine hydrogen maleate (Chl) using uncoated fused silica capillaries. Detection was performed on a UV detector at 214 nm. During the analysis, a flow-injection analyzer was used to transport the background electrolytes and the samples. The system consisted of a double piston, a 16-way automatic switching valve with three sample loops, and a peristaltic pump. The limits of detection (LOD) values were 0.22, 0.29, 0.42, and 0.70 μg ml−1 for the compounds Dex, Chl, Pse, Par, respectively. The low LOD values, the separation of the baseline of the peak of each analyte and the low cost of this FIA-CE system are characteristics that indicate that the proposed system is suitable for the identification and quantification of the compounds investigated.

Kuban *et al.* [76] described the determination of small inorganic cations (K+ , Na+ , Mg2+, and Ca2+) in blood, milk, or plasma samples by electrokinetic injection using an FIA-CE system. Since the undesirable adsorption of proteins onto the capillary wall during electrophoresis was inhibited, pretreatment of the samples was not necessary, and they could be injected directly into the system. In the initial stage, two injection modes were tested for all electrolyte and standard solutions: electrokinetic (EK) and prehydrodynamic (HD). The results indicated that EK injection was the better option because it showed high sensitivity and low matrix effects, with good repeatability of the cation migration times, mainly in the case of human plasma samples. In addition, a better performance was observed for the FIA-CE system when compared to the commercial CE system.

Other researchers have reported the determination of multianalytes using the FIA system combined with other systems of separation, identification, or quantification (detectors). These include the following: an immunoassay system using detection by chemiluminescence [79]; an electrochemiluminescence immunosensor for the detection of tumor markers [80]; biosensors with the use of enzymes [81]; the quantification of carbohydrates with amperometric biosensors [82]; and the analysis of pharmaceutical formulations combining FIA with HPLC or CE [83]. Thus, it is clear that FIA coupling with other analytical techniques allows the detection/quantification of multianalytes in pharmaceutical and biological samples, etc., either for the development of methods in laboratory research or in routine analysis.

Tzanavaras and Themelis published a review on the application of flow injection to pharmaceutical analysis that covers the topics of spectrophotometric determination of active pharmaceutical ingredients [84]. According to Tzanavaras and Themelis [84], the discovery of new drugs, especially when many samples have to be analyzed in the minimum of time, demand the improvement or development of new analytical methods.

#### **7. Conclusions and future prospects**

Many methods aimed at the monitoring of chemical species in pharmaceutical and biomedical samples have been developed and investigated in recent decades. This is a field in which analytical chemistry plays an important role, contributing new analysis procedures and instrumentation. However, methods for the determination and monitoring of pharmaceuticals are still scarce.

Although some progress has been made in the development of methodologies for the monitoring of chemical species in pharmaceutical and biomedical samples, some important points still need to be addressed, such as the sample pretreatment.

In this context, a further challenge has emerged for scientists, which is the development of new clean environmentally acceptable technologies with commercial feasibility. Thus, laboratory researchers need to improve the techniques for the identification and quantification of analytes, individually or simultaneously, with a focus on this challenge.

#### **Acknowledgements**

An example of an FIA-CE system is also described in a paper by Liu *et al.* [78], which proposes a method developed through the combination of flow injection and CE for the separation and determination of paracetamol (Par), pseudoephedrine hydrochloride (Pse), dextromethorphan, potassium bromide (Dex), and chlorphenamine hydrogen maleate (Chl) using uncoated fused silica capillaries. Detection was performed on a UV detector at 214 nm. During the analysis, a flow-injection analyzer was used to transport the background electrolytes and the samples. The system consisted of a double piston, a 16-way automatic switching valve with three sample loops, and a peristaltic pump. The limits of detection (LOD) values were 0.22, 0.29, 0.42, and 0.70 μg ml−1 for the compounds Dex, Chl, Pse, Par, respectively. The low LOD values, the separation of the baseline of the peak of each analyte and the low cost of this FIA-CE system are characteristics that indicate that the proposed system is suitable for the

Ca2+) in blood, milk, or plasma samples by electrokinetic injection using an FIA-CE system. Since the undesirable adsorption of proteins onto the capillary wall during electrophoresis was inhibited, pretreatment of the samples was not necessary, and they could be injected directly into the system. In the initial stage, two injection modes were tested for all electrolyte and standard solutions: electrokinetic (EK) and prehydrodynamic (HD). The results indicated that EK injection was the better option because it showed high sensitivity and low matrix effects, with good repeatability of the cation migration times, mainly in the case of human plasma samples. In addition, a better performance was observed for the FIA-CE system when

Other researchers have reported the determination of multianalytes using the FIA system combined with other systems of separation, identification, or quantification (detectors). These include the following: an immunoassay system using detection by chemiluminescence [79]; an electrochemiluminescence immunosensor for the detection of tumor markers [80]; biosensors with the use of enzymes [81]; the quantification of carbohydrates with amperometric biosensors [82]; and the analysis of pharmaceutical formulations combining FIA with HPLC or CE [83]. Thus, it is clear that FIA coupling with other analytical techniques allows the detection/quantification of multianalytes in pharmaceutical and biological samples, etc., either for

Tzanavaras and Themelis published a review on the application of flow injection to pharmaceutical analysis that covers the topics of spectrophotometric determination of active pharmaceutical ingredients [84]. According to Tzanavaras and Themelis [84], the discovery of new drugs, especially when many samples have to be analyzed in the minimum of time, demand

Many methods aimed at the monitoring of chemical species in pharmaceutical and biomedical samples have been developed and investigated in recent decades. This is a field in which analytical

, Na+

, Mg2+, and

identification and quantification of the compounds investigated.

compared to the commercial CE system.

204 Spectroscopic Analyses - Developments and Applications

Kuban *et al.* [76] described the determination of small inorganic cations (K+

the development of methods in laboratory research or in routine analysis.

the improvement or development of new analytical methods.

**7. Conclusions and future prospects**

The authors are grateful for financial support from the Brazilian governmental agencies Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), the MG state government agency Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG), and the GO state government agency Fundação de Amparo á Pesquisa do Estado de Goiás (FAPEG).

#### **Abbreviations**


USP University of São Paulo UV Ultraviolet Vis Visible

#### **Author details**

Bruno E.S. Costa1 , Henrique P. Rezende<sup>1</sup> , Liliam Q. Tavares<sup>2</sup> , Luciana M. Coelho2 , Nívia M.M. Coelho1 \*, Priscila A.R. Sousa2 and Thais S. Néri1

\*Address all correspondence to: nmmcoelho@ufu.br

1 Institute of Chemistry, Federal University of Uberlândia, Uberlândia, Brazil

2 Department of Chemistry, Federal University of Goiás, Catalão, Brazil

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206 Spectroscopic Analyses - Developments and Applications

\*, Priscila A.R. Sousa2

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## **Factorial Design and Machine Learning Strategies: Impacts on Pharmaceutical Analysis**

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Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.69891

#### **Abstract**

Pharmaceutical analysis is going through an expeditious progress as the perception of 'multivariate data analysis' (MVA) becomes gradually more assimilated. Pharmaceutical analysis comprises a range of processes that covers both chemical and physical assessment of drugs and their formulations employing different analytical techniques. With the revolution in instrumental analysis and the huge amount of information produced, there must be an up-to-date data processing tool. The role of chemometrics then comes up. Multivariate analysis (MVA) has the capability of effectively drawing a complete picture of the investigated process. Moreover, MVA reproduces the arithmetic influence of variables and their interactions through a smaller number of trials, keeping both efforts and capitals. Spectrophotometry is among the most extensively used techniques in pharmaceutical analysis either direct (single component) or derivative (multicomponent). In addition to these recognized benefits, using chemometrics in conjunction with spectrophotometry affects three vital characteristics: accuracy, precision and robustness. The impact of hyphenation of spectrophotometric analytical techniques to chemometrics (experimental design and support vector machines) on analytical laboratory will be revealed. A theoretical background on the different factorial designs and their relevance is provided. Readers will be able to use this chapter as a guide to select the appropriate design for a problem.

**Keywords:** chemometrics, experimental design, machine learning strategies, support vector machines, pharmaceutical analysis, spectrophotometry

#### **1. Introduction**

Nowadays, an enormous amount of information is being generated by the state-of-the art analytical instrumentations, an issue that necessitates the presence of a potent data processing approach. Chemometry, a division of science that has seen a major progress in the past

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

few decades, depends on eliciting data and the development of a mathematical model that describes the relationship between the response signal and the process variables [1–3]. In simple words, chemometrics is the term that is used to describe the case when chemistry, biology and other branches of science meet with mathematics and computer science [4]. As a multidisciplinary science, chemometrics can be used to resolve many problems beyond the boundaries of chemistry, including medicine, pharmacy, environment and other domains of natural and applied sciences [5, 6].

Chemometric techniques, including both multivariate data analysis (MVA) and factorial designs, play a vital role in analysing systems that are both large and multidimensional, an issue that adds to the power of this methodology. Moreover, the growing in complexity from the conventional univariate data analysis (one-variable and a single response at a time) to multivariate data analysis (more than one factor and a single or multiple responses) is greatly reflected on the imperative analytical outcomes, for example, sensitivity and selectivity [7, 8]. Additionally, being a versatile approach, application of chemometry can offer several more advantages. At the simple level (first order, vector data), samples that cannot be signalled using the existent calibration setting can now be effectively modelled. At more sophisticated levels (second- or higher orders), and in addition to the accurate determination of the calibrated analyte, not only new sample constituents can be identified but also their impact on the entire response can be adequately modelled.

Pharmaceutical analysis is experiencing an expeditious growth as the concept of 'multivariate data analysis' becomes progressively integrated. As being known, pharmaceutical analysis encompasses both chemical and physical evaluation of drugs and their dosage forms using different analytical strategies. Yet, the common routine in most of analytical laboratories is to meditate only one-variable and one response at time. Measuring the impact of this variable on the analytical signal is the only source of any generated data [1]. Nevertheless, quality of collected information would be significantly improved if the impact of more than one-variable, their linear, second- and third-order interactions on a single or multiple responses was defined through an arithmetic model [9].

Incorporation of 'design of experiments' (DOE) in any (or all) of the phases of drug development would be of a great effect, not only on the quality of data produced, but also on the analytical process itself in terms of better understanding and usage of generated data, as well as resources preservation.

This chapter focuses on the impact of using hyphenated chemometric-spectroscopic techniques in pharmaceutical analysis. Experimental designs as well as machine learning strategies, as essential parts of chemometrics, will be the main topic of the chapter. The reader does not need to be familiar with the complicated mathematical concepts. Rather, and for practicality and reader's advantageousness, a brief on the simple hypotheses needed to get DOE straightforward will be revealed.

Distinctive application of chemometrics in the field of drug analysis will be shown as we go forward. Material presented throughout the chapter will be of interest to students, chemometricians, drug manufacturers, quality control chemists and pharmacists.

### **2. Experimental design**

few decades, depends on eliciting data and the development of a mathematical model that describes the relationship between the response signal and the process variables [1–3]. In simple words, chemometrics is the term that is used to describe the case when chemistry, biology and other branches of science meet with mathematics and computer science [4]. As a multidisciplinary science, chemometrics can be used to resolve many problems beyond the boundaries of chemistry, including medicine, pharmacy, environment and other domains of

Chemometric techniques, including both multivariate data analysis (MVA) and factorial designs, play a vital role in analysing systems that are both large and multidimensional, an issue that adds to the power of this methodology. Moreover, the growing in complexity from the conventional univariate data analysis (one-variable and a single response at a time) to multivariate data analysis (more than one factor and a single or multiple responses) is greatly reflected on the imperative analytical outcomes, for example, sensitivity and selectivity [7, 8]. Additionally, being a versatile approach, application of chemometry can offer several more advantages. At the simple level (first order, vector data), samples that cannot be signalled using the existent calibration setting can now be effectively modelled. At more sophisticated levels (second- or higher orders), and in addition to the accurate determination of the calibrated analyte, not only new sample constituents can be identified but also their impact on

Pharmaceutical analysis is experiencing an expeditious growth as the concept of 'multivariate data analysis' becomes progressively integrated. As being known, pharmaceutical analysis encompasses both chemical and physical evaluation of drugs and their dosage forms using different analytical strategies. Yet, the common routine in most of analytical laboratories is to meditate only one-variable and one response at time. Measuring the impact of this variable on the analytical signal is the only source of any generated data [1]. Nevertheless, quality of collected information would be significantly improved if the impact of more than one-variable, their linear, second- and third-order interactions on a single or multiple responses was

Incorporation of 'design of experiments' (DOE) in any (or all) of the phases of drug development would be of a great effect, not only on the quality of data produced, but also on the analytical process itself in terms of better understanding and usage of generated data, as well

This chapter focuses on the impact of using hyphenated chemometric-spectroscopic techniques in pharmaceutical analysis. Experimental designs as well as machine learning strategies, as essential parts of chemometrics, will be the main topic of the chapter. The reader does not need to be familiar with the complicated mathematical concepts. Rather, and for practicality and reader's advantageousness, a brief on the simple hypotheses needed to get DOE

Distinctive application of chemometrics in the field of drug analysis will be shown as we go forward. Material presented throughout the chapter will be of interest to students, chemome-

tricians, drug manufacturers, quality control chemists and pharmacists.

natural and applied sciences [5, 6].

214 Spectroscopic Analyses - Developments and Applications

the entire response can be adequately modelled.

defined through an arithmetic model [9].

as resources preservation.

straightforward will be revealed.

Design of experiments (DOE) is a fundamental part of multivariate analysis techniques. However, DOE is comprehended to deal with a limited number of factors (determined according to the design used) in comparison to the other multivariate techniques.

Moreover, multivariate methods either bilinear such as partial least squares (PLS) and principal component analysis (PCA), or multi-way models such as Tucker-3 and parallel factor analysis (PFA), are commonly deemed as supplementary methodologies to DOE. Factors that were not considered in the initial set-up of DOE, as well as their effect, can now be recognized by the subsequent multivariate techniques [6, 10–12].

The typical scenario for setting DOE starts with deciding upon the experimental objective as well as the number of factors to be investigated. The most common objectives can be summarized as follows [13–16]:


**Table 1** recaps the rules for selecting a design based on the number of factors and the envisioned goal of the experiment.

Up to now, the conventional approach for investigating the influence of several factors on a response depends on fixing the levels of all factors except the one to be investigated. This approach is known as one-variable at a time (OVAT). Although still being applied for analytical method development, OVAT usually confronts several difficulties.

One of the main limitations accompanying this rehearsal is the need for a big number of trials. Nevertheless, the resulting delineation of 'ideal conditions' and hereafter the system execution cannot be handled with a high extent of certainty. One reason for that is the absence of an evaluation for the variable-variable interactions in the paradigms premeditated using OVAT.


**Table 1.** Design selection rubric.

Multivariate data analysis (MVA) and its advantages mentioned earlier has the ability to replicate the arithmetical influence of the discrete factors and similarly their interactions through a reduced number of experimentations, saving both efforts and resources [16, 17].

The set-up of experimental design then can be viewed as 2–3 phases depending on the number of factors to be investigated and the objective of investigation: *screening*, *optimization* and *verification*.

#### **2.1. Screening**

Usually, a consecutive investigation process starts with testing a relatively large number of prospective variables. Screening designs then are factorial designs that can be used to get the few utmost substantial variables affecting the response, **Table 1**. Several designs can be used for this purpose, which are mentioned the following section.

#### *2.1.1. Two-level full factorial design (2k -FFD)*

This design can be used when the number of variables (*k*) is between 2 and 15. Each variable is set at two levels: low (−1) and high (+1). Therefore, for three factors, for example, eight runs will be conducted excluding the central points and replicates. **Table 2** presents the design table when three factors X<sup>1</sup> , X<sup>2</sup> , and X<sup>3</sup> are investigated using the proposed two-level full factorial design (FFD). **Figure 1** shows the pattern of experiments in a design for three factors, arrows illustrate the direction of increase of the factors.

#### *2.1.2. Two-level fractional factorial design (2k-p)*

Even when the number of factors is small, many runs are needed if an FFD is to be used. For example, for five factors, 2<sup>5</sup> = 32 experiments are needed in the base run only. In case replicates are needed and central points are added, the number of runs becomes large and the objective of using the DOE to save time and efforts becomes meaningless. The only way out for such a


**Table 2.** A two-level, full factorial design table for three factors.

Factorial Design and Machine Learning Strategies: Impacts on Pharmaceutical Analysis http://dx.doi.org/10.5772/intechopen.69891 217

**Figure 1.** Pattern of experiments in a 2<sup>3</sup> FFD.

Multivariate data analysis (MVA) and its advantages mentioned earlier has the ability to replicate the arithmetical influence of the discrete factors and similarly their interactions through

The set-up of experimental design then can be viewed as 2–3 phases depending on the number of factors to be investigated and the objective of investigation: *screening*, *optimization* and

Usually, a consecutive investigation process starts with testing a relatively large number of prospective variables. Screening designs then are factorial designs that can be used to get the few utmost substantial variables affecting the response, **Table 1**. Several designs can be used

This design can be used when the number of variables (*k*) is between 2 and 15. Each variable is set at two levels: low (−1) and high (+1). Therefore, for three factors, for example, eight runs will be conducted excluding the central points and replicates. **Table 2** presents the design

torial design (FFD). **Figure 1** shows the pattern of experiments in a design for three factors,

Even when the number of factors is small, many runs are needed if an FFD is to be used. For

are needed and central points are added, the number of runs becomes large and the objective of using the DOE to save time and efforts becomes meaningless. The only way out for such a

are investigated using the proposed two-level full fac-

= 32 experiments are needed in the base run only. In case replicates

a reduced number of experimentations, saving both efforts and resources [16, 17].

for this purpose, which are mentioned the following section.

, X<sup>2</sup>

arrows illustrate the direction of increase of the factors.

*2.1.2. Two-level fractional factorial design (2k-p)*

, and X<sup>3</sup>

**Run order X1 X2 X3** 1 −1 −1 −1 2 1 −1 −1 3 −1 1 −1 4 1 1 −1 5 −1 −1 1 6 1 −1 1 7 −1 1 1 8 1 1 1

*-FFD)*

*2.1.1. Two-level full factorial design (2k*

216 Spectroscopic Analyses - Developments and Applications

table when three factors X<sup>1</sup>

example, for five factors, 2<sup>5</sup>

Note: Runs are shown in standard order.

**Table 2.** A two-level, full factorial design table for three factors.

*verification*.

**2.1. Screening**

case is to cautiously select a fraction (*p)* of the original runs proposed by the two-level FFD. For the previous example (3 factors), instead of performing 16 experiments (8 × 2 replicates) and by using a ½ fraction, only 8 runs will be performed in the 2 replicates.

**Figure 2** shows a comparison between a full (2*<sup>k</sup>* ) and a fractional (2*k-p*) factorial designs used to investigate three factors. While eight runs are needed in the first set-up, only four runs will be performed in the second arrangement, where main effects are confounded with the two-way interactions.

#### *2.1.3. Plackett-Burman design (PBD)*

This design has run numbers that are multiple of 4. Using this design allows performing a number of trials *N* = 4*n* in order to investigate a number of factors *f* = 4 (*n* – 1). PBD is an efficient approach when only main or large effects are of interest. In other words, this design can detect the most imperative factors affecting the experiment from a comparatively large number of factors (2–47) and without putting any concerns on interactions and non-linear effects. Minitab®, a commonly used software for this purpose, can generate a PBD for up to 47 factors.

PBD, in specific, is one of the commonly used approaches in robustness tests used in method validation compared to fractional factorial design, for example. The main reason for selecting PBD as a robustness test is that this design focuses only on the main effects, while factor-factor interactions are highly confounded with the large main effects, as previously mentioned [18–21].

**Figure 2.** A 23 full factorial (left pane) and a 23-1 fractional factorial designs (right pane) for three factors.

It is noteworthy to mention that, for any of the designs, identification of significant factors can be achieved using several tools. Pareto chart of standardized effects, normal and half-normal probability plots are among these tools.

#### **2.2. Optimization**

After selection of the most important factors from the previous screening process, levels of these factors need to be adjusted 'tuned' to identify the most suitable variable settings for optimizing a response. It is noteworthy to mention that significant factors can be also identified based on a former knowledge with the process under consideration. Another objective for this process is to assess the variable-variable linear interactions as well as the quadratic effects. This estimation gives an indication on how the response surface looks like. This approach is hence known as '*response surface methodology (RSM) designs*' [13].

Following the application of a response surface design, graphical representation of the developed polynomial mathematical model is assembled. Contour plots (2D) or response surface plots (3D) are used to graphically envisage the model.

#### *2.2.1. Box-Behnken (BB) design*

As a response surface design, BB design can capably determine the first- and second-order constants. BB design is simple, and independent with no contribution from a preceding factorial or fractional factorial design. Three levels for each factor are proposed; however, runs where all variables at their upper domains or all at lower domains are not included [22]. BB design is an economic choice since it involves less design points and hence a fewer number of runs compared to other RSM designs.

#### *2.2.2. Central composite (CC) design*

Unlike the BB design, CC designs usually contain in-built points from the factorial or fractional factorial designs (2*<sup>f</sup>* trials) with added centre points that are enhanced with a group of axial points (2*<sup>f</sup>* trials), **Figure 3**. Thus to scrutinize a number of factors = *f*, a number of experiments *N* = 2*f* + 2*f +* 1 will be conducted. The design in such a configuration allows the estimation of data curvature. Furthermore, due to inclusion of data points from a prior screening design, CC design can be used in a consecutive experimental set-up. Classification of CC designs depends on the value of alpha (α) or the distance between the axial points and the centre. Three types of CC design then exist: *circumscribed (CCC)*, *inscribed (CCI)* and *face-centred (CCF)* [1, 13, 23–26].

#### **2.3. Statistical validation**

Following the last step, generated models can be statistically assessed using conventional approaches such as 'analysis of variance' (ANOVA). In this approach, variances are used to decide whether the means are different. For ANOVA to be properly conducted, the response variable has to be continuous and at least one of the investigated variables is categorical. For a factor to be significant, the *p*-value is usually less than α of 0.05 [1, 23–26].

Factorial Design and Machine Learning Strategies: Impacts on Pharmaceutical Analysis http://dx.doi.org/10.5772/intechopen.69891 219

**Figure 3.** Central composite (CC) design for two factors.

It is noteworthy to mention that, for any of the designs, identification of significant factors can be achieved using several tools. Pareto chart of standardized effects, normal and half-normal

After selection of the most important factors from the previous screening process, levels of these factors need to be adjusted 'tuned' to identify the most suitable variable settings for optimizing a response. It is noteworthy to mention that significant factors can be also identified based on a former knowledge with the process under consideration. Another objective for this process is to assess the variable-variable linear interactions as well as the quadratic effects. This estimation gives an indication on how the response surface looks like. This approach is

Following the application of a response surface design, graphical representation of the developed polynomial mathematical model is assembled. Contour plots (2D) or response surface

As a response surface design, BB design can capably determine the first- and second-order constants. BB design is simple, and independent with no contribution from a preceding factorial or fractional factorial design. Three levels for each factor are proposed; however, runs where all variables at their upper domains or all at lower domains are not included [22]. BB design is an economic choice since it involves less design points and hence a fewer number of

Unlike the BB design, CC designs usually contain in-built points from the factorial or fractional

*N* = 2*f* + 2*f +* 1 will be conducted. The design in such a configuration allows the estimation of data curvature. Furthermore, due to inclusion of data points from a prior screening design, CC design can be used in a consecutive experimental set-up. Classification of CC designs depends on the value of alpha (α) or the distance between the axial points and the centre. Three types of CC design then exist: *circumscribed (CCC)*, *inscribed (CCI)* and *face-centred (CCF)* [1, 13, 23–26].

Following the last step, generated models can be statistically assessed using conventional approaches such as 'analysis of variance' (ANOVA). In this approach, variances are used to decide whether the means are different. For ANOVA to be properly conducted, the response variable has to be continuous and at least one of the investigated variables is categorical. For

a factor to be significant, the *p*-value is usually less than α of 0.05 [1, 23–26].

trials), **Figure 3**. Thus to scrutinize a number of factors = *f*, a number of experiments

trials) with added centre points that are enhanced with a group of axial

hence known as '*response surface methodology (RSM) designs*' [13].

plots (3D) are used to graphically envisage the model.

*2.2.1. Box-Behnken (BB) design*

runs compared to other RSM designs.

*2.2.2. Central composite (CC) design*

factorial designs (2*<sup>f</sup>*

**2.3. Statistical validation**

points (2*<sup>f</sup>*

probability plots are among these tools.

218 Spectroscopic Analyses - Developments and Applications

**2.2. Optimization**

Another model-fitting approach is the residual analysis. Residual plots are generally used to scrutinize the goodness of fit in regression and ANOVA. Examples of residual plots given by Minitab® include normal probability plots, residual versus fits, histograms and residuals versus order plots.

#### **3. Support vector machines (SVMs)**

SVM is a prevalent classification tool which was proposed by Vapnik [27]. As a kernel-based technique, support vector machines (SVMs) have seen a major development in the past few years. During such a short period, SVMs have found several applications in pharmacy, medicine and drug development industry. For example, SVMs have been used in finding the relation between drug structure and its activity 'structure-activity relationships (SAR)'. Moreover, SVMs with a capability of differentiating various drug substrates and classifying them as drugs or non-drugs are widely applied in drug design [28]. Fields of applications of SVMs extend to chemometrics, biosensors, computational biology and industrial modelling processes. Though being famous for the treatment of non-linear data, their application in handling linear models is still conceivable [27–32].

#### **4. Pharmaceutical analysis and chemometrics**

As mentioned earlier in this chapter, drug analysis covers all features related to both in- and after process (quality control) assay of drug substances. Details of these aspects include processes starting with drug synthesis, testing of physico-chemical properties, SAR and mechanism of drug action [28, 33, 34]. Quality control assays include stability testing of both raw and formulated drug materials, content homogeneity, solubility and dissolution properties. Nonetheless, drug assays are not circumscribed to the pure materials and the dosage forms, but the practice extends to include all complicated matrices (biological, foods, drinks, etc.). Moreover, analyses do not consider the active constituents only, but also look for the additives, degradation products and the impurities.

Different analytical techniques have been proposed for the determination of drugs (pure form, pharmaceutical formulations, biological fluids, etc.). For established drugs, standard analytical techniques can be obtained from compilations such as pharmacopoeias. The presence of almost daily new produces, however, requires constructing an appropriate analytical design. This design should inaugurate sufficient data on the analytical process and the product of concern. Data obtained should also be valid throughout the entire process of drug development and the procedure itself needs to be robust and applicable, when needed, in different laboratories.

These specifications do not mean that there is a need for a sophisticated technique such as chromatography. Yet, spectrophotometry might be an equivalent choice in the case being linked to an arithmetic backbone [16, 35–39]. Both single and multicomponent analyses (derivative spectrophotometry (DS)) can be readily linked to chemometry. Furthermore, analysis of a single response (e.g. absorbance) or multiple responses (at different wavelengths) can be better controlled using mathematical modelling [35–42].

Many challenges face the pharmaceutical analyst especially when trying to develop a new analytical method, inaugurate a drug stability study and establish automation into the laboratory. Handling these challenges using chemometrics will be revealed in the coming subsections.

Spectroscopic techniques have been used for long in pharmaceutical analysis. Ultraviolet and visible (UV-vis), infrared (IR), spectrofluorometry and near infrared (NIR) spectroscopy are among the most popular techniques in this concern. The application of techniques such as spectrophotometry in pharmaceutical analysis, though being simple, rapid, cost-effective and suitable for routine analysis, confronts many problems. A major problem that hinders the applicability of this technique is the lack of selectivity. Even in the analysis of a mixture of two or more components, the inability to select the most appropriate wavelength would have a negative impact on sensitivity, selectivity and reproducibility as well. Chromatography, though being a well-developed modern technique that is widely used in pharmaceutical analysis, suffers also from similar glitches. Inappropriate chemical deviations such as peaks from the matrix, alterations of mobile phase concentrations, baseline drift and shifts in retention times would greatly influence the cogency of the obtained results.

In both cases (and probably for other analytical techniques), the application of chemometrics to interpret the obtained data would be an ideal solution if the approach is able to account for all variations in the obtained data as well as get quantitative data from the tested samples. In addition, the used approach should be able to reduce the effects of these variations on the anticipated response.

In the coming subsections, we will consider the impacts of linking chemometry on pharmaceutical analytical techniques. More details will be given in the recent advances that have been made in this field and how spectrophotometry in specific has been affected.

#### **4.1. Spectrophotometry**

**4. Pharmaceutical analysis and chemometrics**

220 Spectroscopic Analyses - Developments and Applications

tives, degradation products and the impurities.

ter controlled using mathematical modelling [35–42].

times would greatly influence the cogency of the obtained results.

different laboratories.

subsections.

As mentioned earlier in this chapter, drug analysis covers all features related to both in- and after process (quality control) assay of drug substances. Details of these aspects include processes starting with drug synthesis, testing of physico-chemical properties, SAR and mechanism of drug action [28, 33, 34]. Quality control assays include stability testing of both raw and formulated drug materials, content homogeneity, solubility and dissolution properties. Nonetheless, drug assays are not circumscribed to the pure materials and the dosage forms, but the practice extends to include all complicated matrices (biological, foods, drinks, etc.). Moreover, analyses do not consider the active constituents only, but also look for the addi-

Different analytical techniques have been proposed for the determination of drugs (pure form, pharmaceutical formulations, biological fluids, etc.). For established drugs, standard analytical techniques can be obtained from compilations such as pharmacopoeias. The presence of almost daily new produces, however, requires constructing an appropriate analytical design. This design should inaugurate sufficient data on the analytical process and the product of concern. Data obtained should also be valid throughout the entire process of drug development and the procedure itself needs to be robust and applicable, when needed, in

These specifications do not mean that there is a need for a sophisticated technique such as chromatography. Yet, spectrophotometry might be an equivalent choice in the case being linked to an arithmetic backbone [16, 35–39]. Both single and multicomponent analyses (derivative spectrophotometry (DS)) can be readily linked to chemometry. Furthermore, analysis of a single response (e.g. absorbance) or multiple responses (at different wavelengths) can be bet-

Many challenges face the pharmaceutical analyst especially when trying to develop a new analytical method, inaugurate a drug stability study and establish automation into the laboratory. Handling these challenges using chemometrics will be revealed in the coming

Spectroscopic techniques have been used for long in pharmaceutical analysis. Ultraviolet and visible (UV-vis), infrared (IR), spectrofluorometry and near infrared (NIR) spectroscopy are among the most popular techniques in this concern. The application of techniques such as spectrophotometry in pharmaceutical analysis, though being simple, rapid, cost-effective and suitable for routine analysis, confronts many problems. A major problem that hinders the applicability of this technique is the lack of selectivity. Even in the analysis of a mixture of two or more components, the inability to select the most appropriate wavelength would have a negative impact on sensitivity, selectivity and reproducibility as well. Chromatography, though being a well-developed modern technique that is widely used in pharmaceutical analysis, suffers also from similar glitches. Inappropriate chemical deviations such as peaks from the matrix, alterations of mobile phase concentrations, baseline drift and shifts in retention Spectrophotometric techniques are, as mentioned before, among the most widely used approaches in pharmaceutical analysis. Direct application of spectrophotometric analysis is only possible if the selected wavelength is not affected by another concomitant analyte. As an approach, application of spectrophotometry entails a study of a variety of factors affecting a single response or multiple responses [37–39].

With the advent of chemometrics, data processing programs and user-friendly software, the outdated OVAT approach is being gradually replaced with MVA in the analytical laboratories. In general, in addition to the known advantages of using chemometrics in conjunction with spectrophotometry, three crucial performance features are usually assessed with this hyphenation; accuracy, precision and robustness.

DOE and SVM are among the widely used chemometric approaches in spectrophotometric analysis of drugs and formulations. The main idea behind implementing these chemometric techniques is to establish the concept of thinking before doing, arrange and perform a controlled experiment, interpret the obtained results, and hence maximize the efficiency of used technique and obtained data. Generally, preservation of resources and conducting the fewest number of experiments are taken into consideration. This comprehensive knowledge and control of the running process are represented by a multi-aspect assembly of input variables together with method parameters, in other words, the 'design space'. The outcome of application of 'design space' is reflected on a pledge of quality as defined by International Conference on Harmonisation (ICH) tripartite rules [43].

As we mentioned earlier, DOE can be used in many stages of the pharmaceutical industry. For example, while screening designs can be used at the early stages of method development, optimization and testing of robustness are used just before the discharge of the finalized product [44].

Several other examples exist in the literature showing the application of DOE and SVM in the pharmaceutical industry. For instance, a two-level full factorial design (2<sup>3</sup> -FFD) was used to decide upon the most substantial factors in the formulation of ascorbic acid tablets that are resistant to oxidative degradation using hydrophilic polymers. Measured responses were the tensile strength, disintegration time and the release features of these tablets [45]. In another application, Plackett-Burman design was employed to investigate the impact of seven factors on the release of theophylline from hydrophilic vehicles. According to the proposed model, 12 experiments were performed and a polynomial model was generated. Out of the seven variables, only two were proved to be significant [46].

In many cases of drug analysis, chemical pre-treatment of the analyte(s) prior to measurement of the anticipated response is sometimes needed. Usually, this preceding treatment would serve to correct for lack of sensitivity and selectivity encountered using direct spectrophotometry. Practices that are now ordinarily used in this concern are condensation, ion-pairing, charge transfer complexation, metal ion chelation, diazotization and redox reactions. With this pre-treatment, the process becomes technically more complicated and requires an investigation of a larger number of factors. A compelling solution in this case is provided by chemometrics. The literature now shows a huge amount of records on the hyphenation of factorial designs to spectrophotometric drug analysis, compared to the situation earlier.

For example, the Hantzsch condensation reaction was used for the derivatization of sodium alendronate, an inhibitor of bone resorption that is commonly used for management of osteoporosis, and which does not have any chromophore. Analysis of sodium alendronate was done both in its pure form and in oral solutions. Plackett-Burman screening design was used to investigate the effect of seven factors on the absorbance of the resulting condensation product. Only four factors were proved to be important and this finding was verified by ANOVA testing. Tuning of factors' levels was done using a circumscribed central composite design (CCCD). Moreover, data obtained from the CCCD including both variables and responses were treated with Statsoft® software employing artificial neuron network (ANN). A network of the multi-layer perceptron type (MLP) that has three hidden layer neurons gave the best results. Similarly, data from the CCCD were processed using different SVM kernels. Best results were obtained using a radial-basis function (RBF) kernel [37].

Chemical derivatization of midodrine hydrochloride both as per se and in formulations (tablets and oral drops) was performed using the Hantzsch reaction accompanied by a two-level 24 -FFD. Variables proved to be significant (*p* < 0.05) were warily attuned utilizing a response surface methodology (RSM) with a face-centred central composite design. The suggested model represented a perfect example for probing the efficiency of factorial designs in optimizing the reaction conditions and maximizing the output [38]. Statistical validation of the proposed technique was performed by using ANOVA in two successive steps. Moreover, D-optimality design was chosen to minimalize the variance in the regression coefficients of the fitted model. **Table 3** shows the screened factors and the response domains employing the proposed screening design.

A suitable approach in finding the most significant variables for screening designs and the optimal locations following an optimization design is usually the graphical representation of the data or the generated model. This feature is usually implemented in chemometrics' software such as Statsoft® and Minitab®. The outcome of screening designs is customarily represented by the Pareto chart of standardized effects, where factors passing the reference line are considered significant. Similar conclusions can be drawn using normal and half-normal probability plots. **Figure 4** shows a Pareto chart showing the significant factors obtained after screening of all factors affecting the formation of a charge transfer complex between *p-*synephrine and *p-*chloranil employing a full factorial design.


12 experiments were performed and a polynomial model was generated. Out of the seven

In many cases of drug analysis, chemical pre-treatment of the analyte(s) prior to measurement of the anticipated response is sometimes needed. Usually, this preceding treatment would serve to correct for lack of sensitivity and selectivity encountered using direct spectrophotometry. Practices that are now ordinarily used in this concern are condensation, ion-pairing, charge transfer complexation, metal ion chelation, diazotization and redox reactions. With this pre-treatment, the process becomes technically more complicated and requires an investigation of a larger number of factors. A compelling solution in this case is provided by chemometrics. The literature now shows a huge amount of records on the hyphenation of factorial

For example, the Hantzsch condensation reaction was used for the derivatization of sodium alendronate, an inhibitor of bone resorption that is commonly used for management of osteoporosis, and which does not have any chromophore. Analysis of sodium alendronate was done both in its pure form and in oral solutions. Plackett-Burman screening design was used to investigate the effect of seven factors on the absorbance of the resulting condensation product. Only four factors were proved to be important and this finding was verified by ANOVA testing. Tuning of factors' levels was done using a circumscribed central composite design (CCCD). Moreover, data obtained from the CCCD including both variables and responses were treated with Statsoft® software employing artificial neuron network (ANN). A network of the multi-layer perceptron type (MLP) that has three hidden layer neurons gave the best results. Similarly, data from the CCCD were processed using different SVM kernels. Best

Chemical derivatization of midodrine hydrochloride both as per se and in formulations (tablets and oral drops) was performed using the Hantzsch reaction accompanied by a two-level


A suitable approach in finding the most significant variables for screening designs and the optimal locations following an optimization design is usually the graphical representation of the data or the generated model. This feature is usually implemented in chemometrics' software such as Statsoft® and Minitab®. The outcome of screening designs is customarily represented by the Pareto chart of standardized effects, where factors passing the reference line are considered significant. Similar conclusions can be drawn using normal and half-normal probability plots. **Figure 4** shows a Pareto chart showing the significant factors obtained after screening of all factors affecting the formation of a charge transfer complex between *p-*syn-

designs to spectrophotometric drug analysis, compared to the situation earlier.

results were obtained using a radial-basis function (RBF) kernel [37].

ephrine and *p-*chloranil employing a full factorial design.

24

proposed screening design.

variables, only two were proved to be significant [46].

222 Spectroscopic Analyses - Developments and Applications

**Table 3.** Screened factors and response domains for a two-level (2<sup>4</sup> ) full factorial design (FFD) premeditated for Hantzsch reaction (reproduced from author's own work [38] with permission from the Royal Society of Chemistry).

**Figure 4.** Pareto chart of standardized effects (reproduced from author's own work [39] with permission from the Royal Society of Chemistry).

Two types of graphs are commonly used to 'pinpoint' the optimal conditions; the response surface (3D) and contour (2D) plots. As shown in **Figure 5** [39], contour lines are produced when points that have the same absorbance are connected. On the other hand, 3D surface plots (figure is not shown) provide a stronger idea on interactions compared to contour plots. Both representations reveal a good matching with the obtained results, employing the polynomial equation.

Analysing one response is a simple task where analysis of each paradigm would merely identify zones of anticipated results. Conversely, concurrent optimization of two or more responses as a function of *n* variables is not that plausible. Different strategies are usually followed for this purpose; overlaid contour plots and global desirability function are among the commonly used approaches [39].

Overlaid contour plots are executed only if few responses are of concern (usually two responses). Simply, higher and lower bounds for each response are outlined. Contours for response boundaries versus variables under analysis are then displayed. A region that ensures both responses is recognized as the 'feasible' area [47, 48]. The plot usually shows the feasible regions where compromised optimum values for both responses meet. However, when more than one factor is involved and considering more than one response, a large number of graphs are requested, an issue that makes the procedure of pictorial observation tiresome.

**Figure 5.** Two-dimensional contour plots for FCCD showing Y1 and Y2 as a function of different variable interactions (reproduced from author's own work [39] with permission from the Royal Society of Chemistry).

Additionally, the overlaying process is not that practicable as the best regions for each response are a bit far from each other.

Derringer function is another approach that can be used in this case. Individual desirability for each response is used to calculate the global desirability employing the following function:

$$D = \langle d\_1^{\prime 1} \, d\_2^{\prime 2} ... d\_m^{\prime m} \rangle^{\prime \prime\_{\mathbb{Z}\mathbb{Z}}} = \left( \prod\_{i=1}^{\mathbb{N}} d\_1^{\prime i} \right)^{\frac{1}{\sum\_i}} \tag{1}$$

where *D* is the overall desirability, *d* is the single desirability, *r* is the significance of each response compared to the other and *m* is the number of responses to be optimized [49, 50]. In general, as the value of *D* gets closer to 1.0000, the desirability of this variable arrangement on the proposed response gets higher. **Figure 6** shows the desirability function plot following the optimization employing an FCCD approach. The horizontal dashed lines represent current response values. The vertical solid lines show the optimal value for each variable.

A serious drawback that hinders drawing useful data, either assessable or qualitative, from spectrophotometry is the overlapping of absorption bands. This overlapping might be arising

**Figure 6.** Desirability function plot for the FCC design (reproduced from author's own work [39] with permission from the Royal Society of Chemistry).

**Figure 5.** Two-dimensional contour plots for FCCD showing Y1 and Y2 as a function of different variable interactions

(reproduced from author's own work [39] with permission from the Royal Society of Chemistry).

224 Spectroscopic Analyses - Developments and Applications

from the presence of drug or non-drug impurity, the presence of more than one component in the target formulation or due to the presence of degradation products. The presence of these components in one formulation at unequal concentration levels augments the problem. A compulsive solution to this problem is using derivative spectrophotometry (DS). This approach depends on differentiation of the regular absorption spectrum using arithmetical transformation into a first-order derivative or a higher order derivative. Several advantages are achieved using DS including but not limited to an improvement in resolution, reduction of noise level, elimination of interferences, augmentation of sensitivity and selectivity, and accordingly an improvement in separation efficiency [51–54].

The situation is not complicated if no chemical interaction among the components, and their spectra are only partially overlapped. In such a case, an acceptable resolution can be achieved employing first derivative spectra. Depending on the spectral characteristics of components to be analysed and the nature of interventions in multicomponent samples, chemometric algorithms have been proved to be a powerful tool in resolving binary (or more) mixture. Approaches such as principal component regression (PCR) and partial least squares (PLSs) have been widely applied both for zero- or higher- order spectra. A combination of MVA and derivative spectral data is highly beneficial where features such as easiness of application and reliability of obtained results are greatly improved [55–58].

#### **5. Conclusion**

Pharmaceutical analysis involves generation of a large amount of data. A pharmaceutical analyst then has an apparently intimidating task and needs to choose from a plethora of methods for handling the obtained data.

Chemometry has started to realize its potential. Assimilation of chemometric modelling (experimental design, artificial neuron networking, support vector machines, principal component analysis, etc.) to different analytical methods (spectrophotometry, chromatography, etc.) with the purpose of optimizing the analytical objectives is the novel trend followed by researchers nowadays. For every analytical process, the principal role of the analyst is to optimally obtain informative data. Unfortunately, best usage of data cannot be accomplished using the traditional univariate analysis. Multivariate analysis, in contrary, would be the golden solution, where a reasonable amount of information would be obtained through a fewer number of experiments, reduced effort and smaller amount of chemicals. As such, application of 'design of experiments (DOE)' becomes a need, and integration of DOE in any analytical procedure would be a must.

#### **Author details**

Marwa S. Elazazy

Address all correspondence to: marwasaid@qu.edu.qa

Department of Chemistry and Earth Sciences, College of Arts and Sciences, Qatar University, Doha, Qatar

#### **References**

from the presence of drug or non-drug impurity, the presence of more than one component in the target formulation or due to the presence of degradation products. The presence of these components in one formulation at unequal concentration levels augments the problem. A compulsive solution to this problem is using derivative spectrophotometry (DS). This approach depends on differentiation of the regular absorption spectrum using arithmetical transformation into a first-order derivative or a higher order derivative. Several advantages are achieved using DS including but not limited to an improvement in resolution, reduction of noise level, elimination of interferences, augmentation of sensitivity and selectivity, and

The situation is not complicated if no chemical interaction among the components, and their spectra are only partially overlapped. In such a case, an acceptable resolution can be achieved employing first derivative spectra. Depending on the spectral characteristics of components to be analysed and the nature of interventions in multicomponent samples, chemometric algorithms have been proved to be a powerful tool in resolving binary (or more) mixture. Approaches such as principal component regression (PCR) and partial least squares (PLSs) have been widely applied both for zero- or higher- order spectra. A combination of MVA and derivative spectral data is highly beneficial where features such as easiness of application and

Pharmaceutical analysis involves generation of a large amount of data. A pharmaceutical analyst then has an apparently intimidating task and needs to choose from a plethora of methods

Chemometry has started to realize its potential. Assimilation of chemometric modelling (experimental design, artificial neuron networking, support vector machines, principal component analysis, etc.) to different analytical methods (spectrophotometry, chromatography, etc.) with the purpose of optimizing the analytical objectives is the novel trend followed by researchers nowadays. For every analytical process, the principal role of the analyst is to optimally obtain informative data. Unfortunately, best usage of data cannot be accomplished using the traditional univariate analysis. Multivariate analysis, in contrary, would be the golden solution, where a reasonable amount of information would be obtained through a fewer number of experiments, reduced effort and smaller amount of chemicals. As such, application of 'design of experiments (DOE)' becomes a need, and integration of DOE in any analytical procedure would be a must.

Department of Chemistry and Earth Sciences, College of Arts and Sciences, Qatar University,

accordingly an improvement in separation efficiency [51–54].

226 Spectroscopic Analyses - Developments and Applications

reliability of obtained results are greatly improved [55–58].

Address all correspondence to: marwasaid@qu.edu.qa

**5. Conclusion**

**Author details**

Marwa S. Elazazy

Doha, Qatar

for handling the obtained data.


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## *Edited by Eram Sharmin and Fahmina Zafar*

The book presents developments and applications of these methods, such as NMR, mass, and others, including their applications in pharmaceutical and biomedical analyses. The book is divided into two sections. The first section covers spectroscopic methods, their applications, and their significance as characterization tools; the second section is dedicated to the applications of spectrophotometric methods in pharmaceutical and biomedical analyses. This book would be useful for students, scholars, and scientists engaged in synthesis, analyses, and applications of materials/polymers.

Spectroscopic Analyses - Developments and Applications

Spectroscopic Analyses

Developments and Applications

*Edited by Eram Sharmin and Fahmina Zafar*

Photo by Iscatel57 / iStock