**1. Introduction**

Pharmacogenetics is a component of precision medicine in which patient-specific genes are used to optimize the medical care of patients, which serves to achieve an optimal drug response in terms of efficacy and toxicity [1]. Observations related to the dependence of drug effects on the genetic constitution of the recipient can be traced back to the 1950s, when reports of primaquine-caused hemolysis were seen in individuals who were glucose-6-phosphate (G6PD)-deficient [2]. Researchers examined why different people had such diverse responses to the same medication. In 1957, Arno Motulsky, a pioneer of medical genetics, published a paper titled "Drug Reactions, Enzymes, and Biochemical Genetics." Freidrich Vogel, a German geneticist, is credited with coining the term "pharmacogenetics" in 1959 to explain the influence of inherited genetic characteristics on clinical responses to xenobiotics. Werner Kalow, a German clinical pharmacologist, created the framework of pharmacogenetics in his book *Pharmacogenetics: Heredity and Drug Response*, which collected known research at the time, including his personal findings on genetic variation and ethnicity [3].

Between 1977 and 1988, an increasing number of different genetic variants and their corresponding enzymatic functions were reported [4]. In 1999, the National Institutes of Health (NIH) announced a mission "to enable the formation of a series of multi-disciplinary research groups funded to conduct studies addressing research problems in pharmacogenetics" [5]. The Pharmacogenetics Research Network (PGRN) was created in 2000, with a mission "to catalyze and lead research in precision medicine for the discovery and translation of genomic variation influencing therapeutic and adverse drug effects" [6]. In the same year, the Pharmacogenomics Knowledge Base (PharmGKB) was released, which is a searchable referenced database of clinically actionable gene-drug associations and the relationships between genotypes and their produced phenotypes [7].

Reports focused on specific genes have been implicated in medication response for many years; single-nucleotide polymorphisms (SNPs) are the most frequently encountered genetic variants. High-density maps of SNPs also make them the most technically accessible class of genetic variants. By correlating SNPs and drug response data, one will have gained an ability to predict drug efficacy or toxicity within reasonable limits for any individual [8]. With the completion of the human genome sequencing project in 2001, a cutting-edge information technology capable of processing tens of thousands of raw sequence data became accessible [9]. Several population-based programs were launched in subsequent years. The term "pharmacogenomics" has emerged to refer to a better knowledge of the influence genetic diversity has, in many genes, on medication pharmacology. Currently, research institutes, companies, and government laboratories are rapidly moving on toward acquiring pharmacogenomic database management systems (DBMS), which are meant to combine public and proprietary genomic databases, clinical data sets, and results from high-throughput screening technologies [10].

Drug safety is the evaluation and study of the pharmacological effects of a potential drug that are unrelated to the desired therapeutic effect [11]. It is an essential element throughout the spectrum of drug discovery and development. A focus on variation related to genes involved in a drug's pharmacokinetics (PK), which is the complex interplay of absorption, distribution, metabolism, and excretion, can be helpful for the prevention and treatment of patients experiencing with adverse drug reaction (ADR) [12]. Consequently, it can assist in choosing the appropriate and safe drug and dosage for each patient [13]. The term "population pharmacokinetic" (PPK) was first used by Sheiner in 1977 for investigating the typical PK of a drug in a large target population using available data. The PPK approach aims to quantitate the effects of various physiologic factors on drug PK with the overall goal of explaining as much variability as possible [14]. Mathematical models are developed to estimate the population-specific pharmacokinetic model parameters for a given drug. For example, parameters can be used to quantify the relationship, e.g., of clearance to individual physiology, such as the function of the liver, kidney, or heart [15]. A dose regimen can then be adjusted to achieve a specific clinical goal, such as drug exposure, within the therapeutic concentration window in the whole population or, if necessary, for special subpopulations characterized by their individual physiology. It must be considered that the significant variability of genetic information is transmitted from one generation to the other and is not always unaltered, creating a further degree of variability with great potential clinical relevance [16]. Pharmacogenomics accounts for ≈80% of the variability in drug efficacy and safety. Over 400 genes are clinically relevant in drug metabolism, and ≈200 pharmagenes are associated ADRs. The main role of pharmacogenetics is to translate genetic information into everyday clinical practice and lower the impact of ADRs, both for patients and for the healthcare system. The Food and Drug Administration (FDA) recently approved a safety labeling change for multiple drugs, guiding clinicians to identify individuals who may be "more susceptible" to ADR [17]. This labeling change does not constitute a requirement for testing prior to drug use but represents a step toward the establishment of such testing as a standard of practice.

#### *Interplay between Pharmacokinetics and Pharmacogenomics DOI: http://dx.doi.org/10.5772/intechopen.108407*

The development of diagnostic tests for clinically significant disorders should be the emphasis of pharmacogenomics research [18]. Not every association results in a potentially valuable pharmacogenetic test, and financial and technological resources may be squandered if the significance of more easily quantifiable values is not initially ruled out [19]. For example, 5-hydroxytryptamine-3 receptor antagonists, which are used to treat nausea and vomiting, are known to be metabolized by the cytochrome P450 2D6 (CYP2D6) enzyme. Kim et al. discovered genotype-dependent pharmacokinetics for tropisetron in healthy volunteers [20], indicating that cancer patients who are ultrarapid metabolizers (UM) are undertreated by a standard dose of tropisetron. This idea was tested in 270 cancer patients by Kaiser and colleagues. There were more nausea and vomiting episodes in patients with a significant number of functioning CYP2D6 alleles. Patients given 4 mg of ondansetron to prevent postoperative nausea and vomiting had a similar outcome [21]. The impact of the UM phenotype on the pharmacokinetics and therapeutic efficacy of 5-hydroxytryptamine 3 receptor antagonists is clearly demonstrated by these studies. The "number needed to genotype" (i.e., the number of individuals needed to genotype to prevent one patient from experiencing needless nausea and vomiting) appeared to be 50 due to the low frequency of the UM genotype in persons of northern European origin [22]. This number is likely too high to incorporate pharmacogenetic testing into normal clinical practice and, more significantly, simpler options for preventing nausea, such as dosage titration or the use of an alternate antiemetic regimen, are currently available [23].

The molecular biology background of pharmacogenetics describes variations seen in drugs' pharmacokinetic phases and/or pharmacodynamics, where drug receptors and other targets may be different from one patient to another [24]. This chapter focuses on the interplay between pharmacokinetics and pharmacogenomics.
