Interindividual Variability In Drug Response Research Articles

The Frequency of UGT2B7*2 (802C>T) Allele among Healthy Unrelated Jordanian Volunteers

The UDP-Glucuronesyl Transferase (UGT) 2B7*2 802C>T is the most common functional genetic variant on UGT2B7 gene with reported influence on drug response. Objective: To determine the frequency of UGT2B7*2 (802C>T) genetic variant among Jordanian population. Methods: The DNA samples from 90 healthy Jordanian volunteers were analyzed by polymerase chain reaction followed by restriction fragment length polymorphism assays (PCR-RFLP) to determine the UGT2B7*2 allele. Results: The frequency (95% confidence interval) of UGT2B7*2 802C allele was 0.59 (0.52 to 0.66) and for UGT2B7*2 802T was 0.41 (0.34 to 0.48), which was similar to the Caucasian but different than African ethnic populations. The UGT2B7 genotype frequency among Jordanians was 0.31 (0.22 to 0.4) for wild, 0.57(0.47 to 0.67) for heterozygote and 0.12 (0.06 to 0.18) for homozygote UGT2B7*2 genotype. Conclusion: This study reported for the first time the UGT2B7*2 frequency and genotype profile among Jordanians. The findings of this study will increase our understanding in explaining the inter-individual variation in drug response among Jordanian population.

Genetics of resistant hypertension: a novel pharmacogenomics phenotype.

Resistant hypertension (RHTN), defined as an uncontrolled blood pressure despite the use of multiple antihypertensive medications, is an increasing clinical problem associated with increased cardiovascular (CV) risk, including stroke and target organ damage. Genetic variability in blood pressure (BP)-regulating genes and pathways may, in part, account for the variability in BP response to antihypertensive agents, when taken alone or in combination, and may contribute to the RHTN phenotype. Pharmacogenomics focuses on the identification of genetic factors responsible for inter-individual variability in drug response. Expanding pharmacogenomics research to include patients with RHTN taking multiple BP-lowering medications may identify genetic markers associated with RHTN. To date, the available evidence surrounding pharmacogenomics in RHTN is limited and primarily focused on candidate genes. In this review, we summarize the most current data in RHTN pharmacogenomics and offer some recommendations on how to advance the field.

CYP2B6*6 allele and age substantially reduce steady-state ketamine clearance in chronic pain patients: impact on adverse effects.

Ketamine analgesia is limited by low intrinsic efficacy compounded by large interindividual variability in drug responses, possibly due to the heterogeneity in drug concentration. The CYP2B6*6 allele is associated with substantially reduced ketamine metabolism in vitro and, therefore, may affect ketamine clearance. Our aims were to examine the impact of the CYP2B6*6 allele on ketamine plasma clearance and on adverse effects in chronic pain patients. CYP2B6 genotypes were identified in 49 chronic pain patients who received 24 h continuous subcutaneous infusions of ketamine. Steady-state plasma concentrations of ketamine (Css,k ) and norketamine (Css,nk ) were determined using HPLC. The median plasma clearance of ketamine after 100 mg 24 h(-1) dose was significantly lower in patients with the CYP2B6*6/*6 (21.6 l h(-1) ) and CYP2B6*1/*6 (40.6 l h(-1) ) genotypes compared with patients with the CYP2B6*1/*1 genotype (68.1 l h(-1) , P < 0.001). The ketamine : norketamine plasma metabolic ratio was significantly higher in patients with the CYP2B6*6/*6 genotype than in those with the CYP2B6*1/*6 and the CYP2B6*1/*1 genotypes (P < 0.001). Patients who experienced adverse effects had lower plasma clearance (45.6 l h(-1) ) than those who did not (52.6 l h(-1) , P = 0.04). The CYP2B6*6 genotype and age, and their combined impact explained 40%, 30% and 60% of the variation in Css,k , respectively. Similar results were observed after higher doses. The CYP2B6*6 allele is associated with a substantial decrease in steady-state ketamine plasma clearance in chronic pain patients. The decreased clearance and resultant higher plasma concentrations may be associated with a higher incidence of ketamine adverse effects.

Clinical implications of neuropharmacogenetics

IntroductionPharmacogenetics aims to identify the underlying genetic factors participating in the variability of drug response. Indeed, genetic variability at the DNA or RNA levels can directly or indirectly modify the pharmacokinetic or the pharmacodynamic parameters of a drug. The ultimate aim of pharmacogenetics is to move towards a personalised medicine by predicting responders and non-responders, adjusting the dose of the treatment, and identifying individuals at risk of adverse drug effects. MethodsA literature research was performed in which we reviewed all pharmacogenetic studies in neurological disorders including neurodegenerative diseases, multiple sclerosis, stroke and epilepsy. ResultsSeveral pharmacogenetic studies have been performed in neurology, bringing insights into the inter-individual drug response variability and in the pathophysiology of neurological diseases. The principal implications of these studies for the management of patients in clinical practice are discussed. Conclusion/discussionAlthough several genetic factors have been identified in the modification of drug response in neurological disorders, most of them have a marginal predictive effect at the single gene level, suggesting mutagenic interactions as well as other factors related to drug interaction and disease subtypes. Most pharmacogenetic studies deserve further replication in independent populations and, ideally, in pharmacogenetic clinical trials to demonstrate their relevance in clinical practice.

Pharmacogenetic-guided algorithms to estimate personalized dose or individual responses to anti-thrombotic drugs

Abstract Purpose Genotyping seems to be regarded as less useful than expected for predicting the inter-individual variation in drug response. We aim to improve the predictive accuracy of genotyping by developing models that also incorporate certain non-genetic factors. Study selection and results The anti-coagulant warfarin is widely used to prevent venous thromboembolic events. Although frequent monitoring of the prothrombin time international normalized ratio (PT-INR) allows an appropriate maintenance dose to be obtained for most individuals, there are some individuals for whom it is difficult to achieve the target PT-INR even when warfarin dose is increased. The anti-platelet drug clopidogrel is typically used with aspirin to prevent cardiovascular events following percutaneous coronary intervention. However, the existence of clopidogrel resistance is a major concern in Asian populations owing to the high prevalence of deficient allele of the CYP2C19 gene, which encodes a major enzyme that produces the active metabolite. Individual response to these anti-thrombotic drugs cannot be accurately predicted based on genetic factors alone. We have constructed two algorithms, one that predicts the maintenance dose of warfarin and one that estimates individual responses to clopidogrel in outpatients without a device-based platelet function test. We applied Akaike's Information Criterion to evaluate the validity of these algorithms. Conclusions In addition to genotyping data, inter-individual variation in non-genetic factors, such as clinical laboratory data, should be considered to predict drug response more accurately in each individual.

AB121. NAT2 sequence polymorphisms and acetylation profiles in Indians

Evolutionary study of genes and genomes are helpful in decoding the role played by various evolutionary forces including footprints of natural selection. These forces change the architecture of genes for their best adaption in a particular environment. Inter-individual variations in drug response are responsible for adverse drug reactions, therapeutic drug failure and susceptibility to other diseases, thus understanding the genetic basis of drug metabolization serves as a key to inter-individual drug responses. To this respect, human N-acetyltransferase 2 (NAT2) is a drug metabolizing gene that helps in the metabolism of wide variety of drugs used for treating different diseases. The effective metabolization of exogenous chemicals by NAT2 gene classifies individuals into two acetylator phenotypes; fast (rapid) acetylator and slow acetylator. In order to determine which of the two acetylation phenotypes are prevalent in Indian population, we sequenced NAT2 873 bp coding region in 250 Indian populations collected from six geographical zones (North India, West India, South India, Central India, East India and North East India) and three tribal populations residing in Odisha (East India). On the basis of seven common NAT2 SNPs found in worldwide population, the individuals can be categorized as fast acetylator and slow acetylator. Thus, evolutionary analysis of drug metabolizing gene helps in understanding the metabolism of different therapeutic drugs and exogenous chemicals present in diet. Furthermore, the polymorphisms present in NAT2 gene will be used to understand how the variability of gene has evolved and how it affects the drug response mechanism in Indian populations.

Parsing interindividual drug variability: an emerging role for systems pharmacology.

There is notable interindividual heterogeneity in drug response, affecting both drug efficacy and toxicity, resulting in patient harm and the inefficient utilization of limited healthcare resources. Pharmacogenomics is at the forefront of research to understand interindividual drug response variability, but although many genotype-drug response associations have been identified, translation of pharmacogenomic associations into clinical practice has been hampered by inconsistent findings and inadequate predictive values. These limitations are in part due to the complex interplay between drug-specific, human body and environmental factors influencing drug response and therefore pharmacogenomics, whilst intrinsically necessary, is by itself unlikely to adequately parse drug variability. The emergent, interdisciplinary and rapidly developing field of systems pharmacology, which incorporates but goes beyond pharmacogenomics, holds significant potential to further parse interindividual drug variability. Systems pharmacology broadly encompasses two distinct research efforts, pharmacologically-orientated systems biology and pharmacometrics. Pharmacologically-orientated systems biology utilizes high throughput omics technologies, including next-generation sequencing, transcriptomics and proteomics, to identify factors associated with differential drug response within the different levels of biological organization in the hierarchical human body. Increasingly complex pharmacometric models are being developed that quantitatively integrate factors associated with drug response. Although distinct, these research areas complement one another and continual development can be facilitated by iterating between dynamic experimental and computational findings. Ultimately, quantitative data-derived models of sufficient detail will be required to help realize the goal of precision medicine. WIREs Syst Biol Med 2015, 7:221–241. doi: 10.1002/wsbm.1302

Can Pharmacometabolomics and LC-HRMS develop a new Concept for Therapeutic Drug Monitoring?

Therapeutic drug monitoring (TDM) is a concept for individualized drug dosing that was developed into clinical routine as a consequence of research findings on variable drug effects and analytical technology developments made in the 1950th and onwards, and founded the clinical pharmacology discipline (1,2). TDM in practice is about measuring a specific drug concentration in blood, serum or plasma, but may also include pharmacogenetic and pharmacodynamic investigations (3). For some time big hopes were put on pharmacogenetics to help explain inter-individual variability in drug response. It is now realized that variability may occur over time and relate to influences from both inborn as well as environmental factors, and that a more multifactorial approach is needed for complex biological systems (4). Examples of important use of TDM comprise treatment of epilepsy, infection, psychiatric disease and immunosuppression after transplantation (1,5,6). Analytical methods for TDM were using immunochemical, HPLC and GC techniques for long time, but this has recently, but slowly, been challenged by LC-MS techniques (7). One good example of this is methods for the immunosuppressive drugs tacrolimus, ciclosporin, sirolimus and everolimus (8,9). LC-MS methods have offered significant improvements in the quality of analytical method performance. It has been demonstrated that LC-MS offer improvement in accuracy, precision and cost-effectiveness, and also can be made robust. With the use of LC-MS in LC-tandem MS SRM mode multi-component methods can be constructed with unique combination of selectivity and sensitivity. Analytical method demands in TDM are set by the requirements of accuracy, cost-effectiveness, rapid reporting and robustness in a routine laboratory environment.

Pharmacogenetic prediction of individual variability in drug response based on CYP2D6, CYP2C9 and CYP2C19 genetic polymorphisms.

Interindividual variability in drug response depends on a number of genetic and environmental factors. The metabolic enzymes are well known for their contribution to this variability due to drug-drug interactions and genetic polymorphisms. The phase I drug metabolism is highly dependent upon the cytochrome P450 mono-oxygenases (CYP) and their genetic polymorphism leads to the variable internal drug exposures. The highly polymorphic CYP2C9, CYP2C19 and CYP2D6 isozymes are responsible for metabolizing a large portion of routinely prescribed drugs and contribute significantly to adverse drug reactions and therapeutic failures. In this review, two attractive and easily implementable approaches are highlighted to recommend drug doses ensuring similar internal exposures in the face of these polymorphisms. The first approach relies on subpopulation-based dose recommendations that consider the original population dose as an average of the doses recommended in genetically polymorphic subpopulations. By using bioequivalence principles and assuming linear gene-dose effect, dose recommendations can be made for different metabolic phenotypes. The second approach relates area under the curve to two characteristic parameters; the contribution ratio (CR), computes for the contribution of the metabolic enzyme and the fractional activity (FA), considers the impact of the genetic polymorphism. This approach provides valid and error free internal drug exposure predictions and can take into consideration genetic polymorphisms and drug interactions and/ or both simultaneously. Despite certain advantages and limitations, both approaches provide a good initial frame-work for devising models to predict internal exposure and individualize drug therapy, one of the promises from human genome project.

Towards curative therapy in gastric cancer: Faraway, so close!

Although recent diagnostic and therapeutic advances have substantially improved the survival of patients with gastric cancer (GC), the overall prognosis is still poor. Surgery is the only curative treatment and should be performed in experienced centers. Due to high relapse following surgery, complementary and systemic treatment aimed at eradicating micrometastasis should be performed in most cases. Cytotoxic treatments are effective in downstaging locally advanced cancer, but different sensitivities and toxicities probably exist in different GC subtypes. Current treatment protocols are based primarily on clinical data and histological features, but molecular biomarkers that would allow for the prediction of treatment responses are urgently needed. Understanding how host factors are responsible for inter-individual variability of drug response or toxicity will also contribute to the development of more effective and less toxic treatments.

Pharmacogenetic Profile of a South Portuguese Population: Results from the Pilot Study of the European Health Examination Survey in Portugal

Background: The genetic inter-individual variability of drug response can lead to therapeutic failure or adverse drug reactions (ADRs). The aims of this study were to assess the pharmacogenetic profile of a South Portuguese population according to established dosing guidelines for commonly prescribed drugs and to compare it with that of previously genotyped populations. Methods: A cross-sectional study was developed in the context of the Portuguese Component of the European Health Examination Survey (EHES). A total of 47 pharmacogenetically relevant variants in 23 different genes were genotyped in 208 participants. Allelic and genotypic frequencies were calculated, and the pharmacogenetic profile of the participants was defined. A comparative analysis was conducted through electronic database search. Pairwise Fst calculations were performed to assess the genetic distance between populations. Results: We found a significant small differentiation between the Portuguese regional populations regarding CYP2C9 rs1057910, CYP2D6 rs3892097, MTHFR rs1801133 and F5 rs6025. When consid-ering 4 HapMap populations, ADH1B rs2066702, ADH1B rs1229984, NAT2 rs1799931 and VKORC1 rs9923231 displayed a significant population differentiation. We found that 18.9% of the participants are intermediate or poor metabolizers for at least 3 drugs simultaneously and that 84.6% of the participants have at least one therapeutic failure or ADR risk allele for the considered drugs. Conclusions: There is a high prevalence of risk alleles associated with an altered drug metabolism regarding drugs largely used by the South Portuguese population. This knowledge contributes to the prediction of their clinical efficacy and/or toxicity, optimizing therapeutic response while improving cost-effectiveness.

Psychotropic Medications: Optimal Prescribing Through the Utilization of Genetic Testing

Psychiatric drug treatment is characterized by large interindividual differences in drug response and dosage requirements. Interindividual variability in drug response can be a major clinical problem and may lead to discontinuation of potentially efficacious medications. Research suggests that individual variability in CYP enzyme activity is an important reason for drug therapy failure. The most substantial variability in medication metabolism is due to genetic polymorphisms. The polymorphisms present in most CYP genes, are responsible for a substantial part of this variability. Research has found that four CYP phenotypes can be identified: poor (slow) metabolizers (PM); intermediate metabolizers (IM); extensive metabolizers (EM); and the ultra-rapid metabolizers (UM), who have multiple gene copies. The ultra-rapid metabolizer (UM) phenotype is recognized as a cause of therapeutic inefficacy of antidepressant (due to resulting low serum levels), whereas an increased risk of toxicity and side effects has been reported in poor (slow) metabolizers (PMs) with several psychotropics (desipramine, venlafaxine, amitriptyline, haloperidol). Based on a review of the literature, it is reasonable to assume that some individuals will metabolize relevant drugs too quickly (and perhaps be nonresponders) and others may metabolize medications too slowly and become toxic and symptomatic. These groups perhaps represent individuals who would benefit most from the genetic testing. Despite cost and inconvenience of testing, these individuals may benefit.

Pharmacogenomics of neuropsychiatric disorders: analysis of genetic variability in 162 identified neuroreceptors using 1000 Genomes Project data.

Neuroreceptors are considered to be primary drug targets and their abrupt signaling is a notable cause of interindividual drug response variability and treatment failure for complex neuropsychiatric diseases. In view of recent evidence, it is believed that common genetic risk factors mainly highly polymorphic neuroreceptors are being shared among neuropsychiatric disorders. We identified 162 neuroreceptors from the 639 known receptors in Homo sapiens and investigated 231,683 SNPs using 1000 Genomes Project data and evaluated their biological effect using in silico tools including RegulomeDB, SIFT, PolyPhen-2 and CAROL. Furthermore, data from the 1000 Genomes Project was utilized to retrieve minor allele frequency and calculate pairwise logartithm of the odds score among these SNPs for African, American, Asian and European populations separately as well as when combined together using Haploview v4.2. LRTag was used to identify tagSNPs in populations. A total of 52,381 (22.60%) SNPs were predicted as functionally important genetic variations. We identified sets of 603, 495, 450, 453 and 646 informative tagSNPs for African, American, Asian, European and combined populations, respectively. We propose construction of a 'neuroreceptor variants array' with these informative SNPs for future pharmacogenomic studies of neuropsychiatric disorders. Such an approach might improve genotype-phenotype correlation across different populations and lead to identification of reliable genetic markers and novel drug targets. Integration of these SNPs in literature would further provide evidence relevant to underlying mechanisms of genetics based nosology, pathophysiology and development of new drugs for the treatment of neuropsychiatric disorders.

Implementation and utilization of genetic testing in personalized medicine.

Clinical genetic testing began over 30 years ago with the availability of mutation detection for sickle cell disease diagnosis. Since then, the field has dramatically transformed to include gene sequencing, high-throughput targeted genotyping, prenatal mutation detection, preimplantation genetic diagnosis, population-based carrier screening, and now genome-wide analyses using microarrays and next-generation sequencing. Despite these significant advances in molecular technologies and testing capabilities, clinical genetics laboratories historically have been centered on mutation detection for Mendelian disorders. However, the ongoing identification of deoxyribonucleic acid (DNA) sequence variants associated with common diseases prompted the availability of testing for personal disease risk estimation, and created commercial opportunities for direct-to-consumer genetic testing companies that assay these variants. This germline genetic risk, in conjunction with other clinical, family, and demographic variables, are the key components of the personalized medicine paradigm, which aims to apply personal genomic and other relevant data into a patient’s clinical assessment to more precisely guide medical management. However, genetic testing for disease risk estimation is an ongoing topic of debate, largely due to inconsistencies in the results, concerns over clinical validity and utility, and the variable mode of delivery when returning genetic results to patients in the absence of traditional counseling. A related class of genetic testing with analogous issues of clinical utility and acceptance is pharmacogenetic testing, which interrogates sequence variants implicated in interindividual drug response variability. Although clinical pharmacogenetic testing has not previously been widely adopted, advances in rapid turnaround time genetic testing technology and the recent implementation of preemptive genotyping programs at selected medical centers suggest that personalized medicine through pharmacogenetics is now a reality. This review aims to summarize the current state of implementing genetic testing for personalized medicine, with an emphasis on clinical pharmacogenetic testing.

Application of routine electronic health record databases for pharmacogenetic research

Inter-individual variability in drug responses is a common problem in pharmacotherapy. Several factors (non-genetic and genetic) influence drug responses in patients. When aiming to obtain an optimal benefit-risk ratio of medicines and with the emergence of genotyping technology, pharmacogenetic studies are important for providing recommendations on drug treatments. Advances in electronic healthcare information systems can contribute to increasing the quality and efficiency of such studies. This review describes the definition of pharmacogenetics, gene selection and study design for pharmacogenetic research. It also summarizes the potential of linking pharmacoepidemiology and pharmacogenetics (along with its strengths and limitations) and provides examples of pharmacogenetic studies utilizing electronic health record databases.

Testing cardiovascular drug safety and efficacy in randomized trials.

Randomized trials provide the gold standard evidence on which rests the decision to approve novel therapeutics for clinical use. They are large and expensive and provide average but unbiased estimates of efficacy and risk. Concern has been expressed about how unrepresentative populations and conditions that pertain in randomized trials might be of the real world, including concerns about the homogeneity of the biomedical and adherence characteristics of volunteers entered into such trials, the dose and constancy of drug administration and the mixture of additional medications that are restricted in such trials but might influence outcome in practice. A distinction has been drawn between trials that establish efficacy and those that demonstrate effectiveness, drugs that patients actually consume in the real world for clinical benefit. However, randomized controlled trials remain the gold standard for establishing efficacy and the testing of effectiveness with less rigorous approaches is a secondary, albeit important consideration. Despite this, there is an appreciation that average results may conceal considerable interindividual variation in drug response, leading to a failure to appreciate clinical value or risk in subsets of patients. Thus, attempts are now being made to individualize risk estimates by modulating those derived from large randomized trials with the individual baseline risk estimates based on demographic and biological criteria-the individual Numbers Needed to Treat to obtain a benefit, such as a life saved. Here, I will consider some reasons why large phase 3 trials-by far the most expensive element of drug development-may fail to address the unmet medical needs, which should justify such effort and investment.

Genetic polymorphisms associated with antiepileptic metabolism.

Several factors, including pharmacogenetics, contribute to inter-individual variability in drug response. Many antiepileptic drugs (AEDs) are metabolized by a variety of enzymatic reactions, and the cytochrome P450 (CYP) family has attracted considerable attention. Some of the CYPs exist as genetic (allelic) variants, which may also affect the plasma concentrations or drug exposure. Regarding the metabolism of AEDs, the polymorphic CYP2C9 and CYP2C19 are of particular interest. There have been recent advances in discovering factors such as these, especially those underlying the risk of medication toxicity. This review summarizes the evidence about whether such polymorphisms affect the clinical action of AEDs to facilitate future studies on the pharmacogenetics of epilepsy. We performed Key Words searches in the public databases PubMed, Medscape, and Rxlisty, Pharm GKB for genetic polymorphisms and the NCBI website for the nomenclature of alleles of CYP450, finding that CYP2D6, CYP2C9, CYP3A4, and CYP2D19 were involved in the metabolism of most antiepileptic drugs, given the allele frequency in the population and the associated variability in the clinical response.

Association of polymorphisms of CYP2C9, CYP2C19, and ABCB1, and activity of P-glycoprotein with response to anti-epileptic drugs.

Epilepsy, the most common neurological disorder, has treatment failure rate of 20 to 25%. Inter-individual variability in drug response can be attributed to genetic polymorphism in genes encoding different drug metabolizing enzymes, drug transporters (P-gp), and enzymes involved in sodium channel biosynthesis. The present study attempted to evaluate association of polymorphisms of CYP2C9, CYP2C19, and ABCB1, and P-gp activity with treatment response in patients with epilepsy. Patients with epilepsy on phenytoin and/or phenobarbital and/or carbamazepine were categorized into responders and non-responders as per the International League Against Epilepsy. Plasma drug concentration was estimated by high-performance liquid chromatography. P-gp activity was measured by flow cytometry using rhodamine efflux. The polymerase chain reaction (PCR-RFLP) was used to study polymorphisms of ABCB1 (C3435T), CYP2C9 (416 C > T, and 1061 A > T), and CYP2C19 (681 G > A and 636 G > A). Of total 117 patients enrolled in this study, genotype data was available for 115 patients. P-gp activity was higher in non-responders (n = 68) compared to responders (n = 47) (P<0.001). No association of 416 C > T and 1061 A > T in CYP2C9 or 681 G > A and 636 G > A in CYP2C19 was observed with response phenotype in genotypic analysis. Significant genotypic (odds ratio, OR = 4.5; 95% CI, 1.04 to 20.99) and allelic association (OR = 1.73; 95% CI, 1.02 to 2.95) was observed with ABCB1 C3435T and response phenotype. The response to antiepileptics seems to be modulated by C3435T in ABCB1 or P-gp activity. At present, role of other genetic factors in treatment responsiveness in epilepsy appears limited, warranting analysis in a larger cohort.

An insight of genetic polymorphism and the commonly studied polymorphisms associated with oral cancer

Oral and pharyngeal cancers are some of the most common cancers worldwide. The risk of developing oral cancer is modified by environment, lifestyle, genetics, and a combination of these factors. Both environmental carcinogens and polymorphisms together or individually play an important role in the pathogenesis of oral and pharyngeal cancer. Various genes show polymorphisms, which are thought to play a major role in interindividual variability in drug response, and in susceptibility to chemical induced diseases, like several types of cancers. The objective of this review is to discuss in detail about the various polymorphism, molecular functions and the polymorphic association of various genes.

Pharmacogenomics and pharmacoepigenomics in pediatric medicine.

In the past several years, human genetics studies have progressed from monogenic to complex and common diseases because of the advancement in technologies. There is increased knowledge of the pharmacokinetics and pharmacogenomics of the drugs in adults as well as in children. These technological developments provided new diagnostic, prognostic, and therapeutic opportunities. We are now in a position to address many additional ambitious questions. For instance, in clinical medicine, interindividual variation in drug response is a major problem. Some of the heterogeneity of drug safety and efficacy among individuals can be explained by pharmacogenomics. It has also the potential to improve the treatment in both adults and children. In pediatrics however, there is ontogeny and metabolic capacity in children is different compared to adults. Several specific developmental changes may underlie some of the variability in drug response seen in children. They may also be responsible for adverse drug reactions (ADRs). Therefore, much of the diversity in drug effects cannot be explained by studying the genomic diversity alone. It is necessary to include the effect of growth (involves variations in gene expression) along with genetic differences when explaining the variability in treatment response. In this respect epigenomics may expand the scope of pharmacogenomics towards optimization of drug therapy. Future studies must focus on periods of maturation of the drug-metabolizing enzymes and polymorphisms in their genes by using candidate gene approach, gene expression analysis, genome-wide haplotype mapping, and proteomics. The integration of genetic data and clinical phenotypes along with the role of other factors is necessary to evaluate both efficacy and ADRs of any drug. It may require extensive genetic epidemiological studies spanning over many years.