**3. Cell based assays**

Cell-based assays in HTS method are classified under following classes: [6].

#### **3.1 Second messenger assays**

The Second messenger assays are used to efficiently measure fast, transient fluorescent signals occurring in matter of seconds or milliseconds. It monitors signal transduction from activated cell-surface receptors. Many fluorescent molecules are known to respond to changes in intracellular.

Calcium ion concentration, membrane potential and various other parameters, hence they are The second messenger assays are made of fluorescent molecules as these molecules are known to respond to changes in intracellular Calcium ion concentration, membrane potential, and various other parameters, So, the fluorescent molecules are used in second messenger assays for receptor stimulation and ion-channel activation. The development of hydrophobic voltage-sensitive probes and FRET-compatible microplate instrumentation has helped the advancement of the screening technique for ionchannel drug discovery [15].

#### **3.2 Reporter gene assays**

The reporter gene assays monitors cellular responses at translation levels. It is responsible for indicating the absence or presence of gene products and in turn reflecting changes in a signal transduction pathway. The quantifications of reporters are generally performed by various bio-chemical methods i.e., by measuring enzymatic activities. Typically, plasmids are used as reporter genes [15].

#### **3.3 Cell proliferation assays**

Cell proliferation assays are responsible for monitoring the overall growth or no growth responses of the cell to external stimuli. Cell proliferation assays can be quickly and easily employed for automation [15].

#### **3.4 Statistics**

It is essential to achieve quality hits with high degree of confidence in drug discovery process. Errors occur or issues arise when analytical method for hit selection is repeated under similar conditions. In real case scenarios obtained results differ from each other and there occurs variability in the system under studies. Using statistical tools in analyzing screening experiments is the correct approach for the interpretation of screening data, and hence supporting making right decisions [15].

#### **4. Breakthrough technologies**

#### **4.1 Automation and robotics**

In the high-throughput screening process, large numbers of samples are screened, microplates having up to 3456 wells are generally used to hold the samples. Primarily, automation plays an essential role in the high-throughput screening process enabling millions of compounds to be rapidly screened in shorter time periods, as opposed to laboratory benchtop investigation of compounds by researchers in the same period [2, 17].

However, there are various challenges faced in automation. For instance, the reagents quantity added to each well of a microplate has to be minimized in order for the potential compounds screening experiment to be designed within the constraints presented by automation. Other challenges include limiting the adjustments that can be made to compounds through the screening process. The means that only one single injection of compound is applicable to target samples. Hence, further adjustments cannot be made to how compounds are added to samples as the experimental design is would no longer be suitable for automation process [2].

Automation is generally categorized into three common modes namely, batch, semi-automated, and integrated. These three modes differ in functions such as walk away capabilities, flexibility, complexity and numbers of tasks. For example, in the batch mode, scientist still need to load stacks of plates, which are further limited to fewer steps in the process. On the other hand, Integrated automation, is a more sophisticated process, which is capable out of performing multiple scheduled steps facilitated by a robotic mover, further allowing non-manual operation for long periods [2, 18].

Often the automated solution requires the operator to be well skilled with the automation process. If not so, specialized training are provided from the equipment. Batch automation are often performed with little specialized training of the operators. Today automation has evolved and become more democratized as compared to the scenario ten years ago. This trend reduces the need for specialized training of the operators in the future and further making such solutions commercially available [2].

A further process involved in high-throughput screening is a robotic configuration. Often a robotic system is incorporated into high-throughput screening platforms to accelerate the time by which data is acquired [2].

The system essentially would be able to perform multiple functions such as adding reagents, transferring microplates, mixing samples, and incubating samples at specific temperatures. This enables both experimental times to be reduced and the elimination of any error that could potentially be brought about if the process was carried out manually [2].

#### **4.2 Miniaturization**

Today researchers aim to reduce the cost the process even more than current high-throughput screening technology. Miniaturization is a technology where smaller or lesser sample quantities are utilized to provide results, in the aim to reduce cost of using more samples. However, smaller quantities must provide reliable results. Development in miniaturization introduces higher sensitivity microplates for high-throughput screening, which can reliably measure signals from small sample sizes and overcoming the challenges of the initial miniaturization technology [2].

However, it is predicted that in the further miniaturization of the screening process can be achieved in future, thus reducing costs of the process even more than current high-throughput screening technology [2].

Most of the steps in HTS lead discovery are influenced by miniaturization. First step in miniaturization is increasing the density of plate well to more than a 96-well standard. Target densities of about 384, 1536, and 3854 wells per plate are available. Hence, higher throughput screening (HTS) achieved through this method of

*Design and Implementation of High Throughput Screening Assays for Drug Discoveries DOI: http://dx.doi.org/10.5772/intechopen.98733*

miniaturization majorly reduces the reagent costs as reaction volumes decreases from 10 to 20 mL in the well of a 384-well plate down to <2 mL in the well of a 1536-well plate [2, 19].

It is quite challenging to handle fluids in miniaturized assays, nevertheless it is a crucial parameter for performance. It is difficult to dispense compounds that are stored or solubilized in organic solvents, in a fast, controllable, and accurate manner. Additional issues include effective mixing, clogging, and evaporation that need to be resolved. Ebner states that "One of the most common problems that high-throughput labs have to address is spatial or edge effects." When poor cellular growth occurs at the perimeter of the wells as compared to growth of the cells in the rest of the plate, the phenomena is called as edge effect. As a consequence, these challenges tend to restrict the plate density to about 384-wells. Microfluidic technology, is a more extreme form of miniaturization, helps to addresses some of these known fluid handling challenges. Microfluidic chips replaces the liquid handling mechanics with channels connected to liquid reservoirs while providing the benefits of reduced volumes. In most cases, the devices comprise of integrated tools including electrodes built-in and combines multiple operational steps [7, 20].

Microfluidic devices are also capable of isolating single cellsthat can be further cultured on the chips. This ability of microfluidic devices eliminates cellular heterogeneity on cancer cell populations as an example. Traditional drug screening methods see response information from an average of all cells. The microfluidic solution allows analysis of a single cell's antidrug response. In addition to this cell-on-chip model, recent advances have led to tissue-on-chip and organ-on-chip models which are still early in development [21]. Someday, these chip models may provide an alternative to animal models [22]. Because they are early in development, they are not high- throughput solutions today. But they show great promise to speed determination of drug activity, optimal combinatorial drug screening and toxicity testing in the future [2].

#### **4.3 Artificial intelligence**

Artificial intelligence (AI) has found great applications in medicinal chemistry for designing compounds and the discovery of drugs since the 1960s. A wellknown Machine-learning tool like quantitative structure–activity relationship modeling has played a very important role to help in the identification of various useful target molecules from millions of compounds. Today, the application of Artificial intelligence has expanded onto drug discovery and tasks including image analysis, robotics control, and logistics. Artificial intelligence has also expanded its application in the process of drug discoveries namely hit identification, target selection, lead optimization, efficiently helping in preclinical and clinical trial studies [2, 23–25].

New applications of Artificial intelligence in drug discovery process now lets the researchers and scientists supervise the system as opposed to driving the system manually. Moreover, Artificial intelligence combined with robotic systems provides automation of the design, build, test, and learn (DBTL) cycle, resulting in a system for designing experiments, executing it, data analysis, hence, the optimization and execution of experiments iteratively. Consequently the application of artificial intelligence decreases the number of experiments to be performed and helps to generate the best possible optimization. In practice such systems have been developed and demonstrated at the University of Illinois. The new fully-automated system outperformed traditional screening methods by 77% and evaluated less than 1% of possible variants [2, 26].

Following are the advantageous features of Artificial intelligence in drug discovery applications [2, 4].


An area where artificial intelligence plays an essential role is the field of personalized or "precision" medicine [28]. Precision medicines are basically growing drugs in the industry. In the development process of personalized medicine collections of healthy and diseased human samples are needed [4]. Usually, the samples are sequenced using next-generation sequencing technique, resulting in the generation of massive data. The application of Artificial intelligence and methods of deep learning helps in the efficient analysis of big data sets [25].

#### **5. Conclusions**

The primary goal of high-throughput screening processes is to screen through a library of compounds, and help in the identification of candidates that affect the target in a desired way. This phenomena is referred as "hits" or "leads". Generally, hits are achieved by using various technologies including liquid handling devices, plate readers, robotics, and software for data processing. Today automation and robotics has been widely accepted in the drug discovery process and great progress continues to be made in this area. Automated process provides better process consistency and hence, better data quality. Alternatively, automation not only allows scientists to walk away freely and pursue other tasks, but it also allows trail of traceability if any questions arise. The process of automation minimizes human errors [29].

To sum it up, HTS processes does not particularly helps in the identification of drugs, because HTS cannot assess several properties that are critical for developing new drug. For example, HTS method cannot evaluate properties like bioavailability and toxicity. Instead, the primary role of HTS assays is to help in the identification of "leads" and provide suggestions for their optimization. Hence, the results from HTS assays helps to reveal the initial point for further steps in the drug discovery process, including drug design. HTS assays also helps to understand the interaction or role of a particular biochemical process.

Hence, the HTS method should be accepted as a technology that scans biological library quickly and efficiently excluding compounds showing no effect in the analysis. Various academic institutions and mainly industries use high-throughput screening method to screen large number of compounds on a daily basis. Various detection techniques FCS, NMR, HRTF etc., contribute to the screening of compounds in large number.

#### *Design and Implementation of High Throughput Screening Assays for Drug Discoveries DOI: http://dx.doi.org/10.5772/intechopen.98733*

According to market analysis, the global (HTS) market size was at 15.3 billion USD in 2020 and is projected to reach 26.4 billion USD by 2025, growing at a CAGR of 11.5% in the forecast period. Market growth is driven by factors including improving research and development spent by biotechnological and pharmaceutical companies, advancements in high throughput screening technologies, availability of funding from government, and capital investments from various bodies. As we all are aware of the outbreak of the corona virus, in response to this, various biopharmaceutical, pharmaceutical companies, and small startups have stepped forward to develop solution to this issue. Scientists and researchers were able to find list of molecules that could target COVID-19. As per the latest reports, there are 79 available vaccine candidates, out of which 20 vaccine candidates are in the third stage of clinical trials. Out of the 20 vaccine candidates, eleven of them have been authorized in various countries. Researchers and scientists have taken the initiative to speed drug discovery process by using high throughput screening method and found few promising drugs that can be used against COVID-19 namely Remdesivir, Chloroquine & Hydroxychloroquine, Lopinavir & Ritonavir, and Lopinavir with Ritonavir plus Interferon beta-1a. There has been an increase in drug discovery projects in efforts to treat COVID-19, which is the driving force for the growth of the high-throughput screening products market [30].

Off late, pharmaceutical & biotechnology industries are collaborating with various academic and research institutions to implement drug discovery more efficiently. The industries and the institution works hand in hand as institutions perform target identification and validation of research, while industries carry out high throughput screening assay development and screening campaigns. In this manner the industries and research institutes, benefits from this collaboration [30].

However, there are certain hindrances to the growth of the high throughput screening market. The commercially available assay platforms are applicable for the already established target classes namely G-protein coupled receptors, ionchannels, nucleic acids, and enzymes. However, today there exists addition of target classes such as transmembrane receptors, transporters, signaling pathways, protein–protein interactions, protein-RNA interactions, and protein-DNA interactions leading to numerous complexities (such as protein instability and reagent variability) in the field of assay development & target identification and being a barrier to the growth of the high throughput screening market [30].

Owing to this expansion of new target classes, researchers and scientist must be encouraged to invest their efforts in developing new essay platforms [30].

#### **6. Executive summary**

