Pharmacogenomics in the assessment of therapeutic risks versus benefits: inside the United States Food and Drug Administration

Genetic Diversity of CYP3A5 and ABCB1 Variants in East-Central and South European Populations

BACKGROUND

CYP3A5 enzyme encoded by CYP3A5 is important for drug metabolism in gut and liver, whereas P-glycoprotein by ABCB1, is an ATP-dependent drug efflux pump which exports endo- and exogenous substances outside the cell. Aim: The study was to assess the prevalence of CYP3A5 alleles: *1, *2, *3, *4, *6 and *7, and C and T of ABCB1 in Poles, Belarusians and Bosnians and to compare it with the data reported from other European populations. Subjects and methods: Overall, 511 unrelated healthy subjects from Poland (n = 239), Belarus (n = 104) and Bosnia and Herzegovina (n = 168) were included in this study. Allele frequencies and statistical parameters (AMOVA version 2.9.3) were determined. Results: In Poles, Belarusians and Bosnians the *3 allele of CYP3A5 was the most common, and wild-type allele *1, were: 5.8%, 1.6% and 2.1%, respectively. Allele *2 was very rare, and alleles *4, *6 and *7 were not detected. For the populations mentioned above, the ABCB1 allele C was: 48.1%, 51.4%, 52.4%, respectively.

CONCLUSION

In compared populations, the distribution of CYP3A5 variants but not ABCB1, differed significantly. Alleles *4, *6 and *7 of CYP3A5 did not occur or occurred rarely.

Pharmacogenetics of Drugs Used in the Treatment of Cancers

Pharmacogenomics is based on the understanding of the individual differences in drug use, the response to drug therapy (efficacy and toxicity), and the mechanisms underlying variable drug responses. The identification of DNA variants which markedly contribute to inter-individual variations in drug responses would improve the efficacy of treatments and decrease the rate of the adverse side effects of drugs. This review focuses only on the impact of polymorphisms within drug-metabolizing enzymes on drug responses. Anticancer drugs usually have a very narrow therapeutic index; therefore, it is very important to use appropriate doses in order to achieve the maximum benefits without putting the patient at risk of life-threatening toxicities. However, the adjustment of the appropriate dose is not so easy, due to the inheritance of specific polymorphisms in the genes encoding the target proteins and drug-metabolizing enzymes. This review presents just a few examples of such polymorphisms and their impact on the response to therapy.

Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions

Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.

Therapeutic Drug Monitoring and Pharmacogenetic Testing in Northern China

Background: Therapeutic drug monitoring (TDM) and pharmacogenetic (PGx) testing are widely used as approaches to improve individualized (personalized) pharmacotherapy. Little is known about TDM and PGx testing services in China. This study is aimed to describe the TDM and PGx testing services in northern China, and to lay the foundation for improving these services.

Methods: We developed an electronic survey using online software and disseminated it to 32 public hospitals in northern China from May to July 2019. The data were analyzed using the Statistical Package for Social Sciences (SPSS) program (Ver.27.0).

Results: We collected 29 of the 32 questionnaires (90.6% response rate) from public hospitals in seven provinces of northern China. Twenty-two public hospitals (76%) utilized TDM; immune suppressants, antiepileptic drugs and anti-infective drugs were the main drugs monitored. The hospitals that did not provide TDM service were traditional Chinese medicine hospitals and hospitals with a smaller number of hospital beds. Seventeen public hospitals (58.6%) had PGx testing programs. The hospitals that did not offer PGx testing service had a smaller number of hospital beds and had fewer daily outpatients.

Conclusion: TDM is available in the vast majority of public hospitals in northern China, although mainly in tertiary hospitals. PGx testing, a newer approach, is less widely available. We recommend that more hospitals be encouraged to provide TDM and PGx testing services and more efforts be directed toward quality control, delivery of results and counseling of patients based on those results.

Establishment of predicting equation for individual sufentanil dosage postoperatively based on gene polymorphisms

BACKGROUND

Postoperative analgesia is widely used for patients undergoing major surgeries. Individual differences in genetic polymorphisms may be obstructive factors for accurately anesthetics using. However, the equation for predicting sufentanil dosage postoperatively based on genetic design has been established yet. Our aim was to establish sufentanil dosage postoperatively prediction equation based on patients' genetic polymorphisms.

METHODS

One hundred forty patients with total gastrectomy and radical resection of pulmonary carcinoma were included. To establish sufentanil dosage postoperatively for patients with gastric cancer, we collected patients' basic information and CYP3A4*1G, COMTVal158Met, OPRM1A118G, and ABCB1C3435T gene sequencing results. To verify this equation, we put patients' with lung cancer surgeries information into it.

RESULTS

The sufentanil dosage prediction equation postoperatively was y = 4.104 - 0.222 × (gender) + 0.021 × (OPRM1A118G) + 0.249 × (ABCB1C3435T). Patients' with lung cancer surgeries information were substituted into it. The results showed no significant differences between predicted and actual sufentanil dosage (p > 0.05).

CONCLUSION

We established the prediction equation for individual sufentanil dosage postoperatively based on gene polymorphisms. The results showed this prediction equation was valid, which might be used for different types of surgeries. We established an equation for individual dosage of sufentanil for postoperative analgesia based on gene polymorphisms. The results show that the prediction equation is valid, the information might be used for different types of postoperative analgesia, and the painful patients will have great potential safe and personalized pain control after analgesic therapy. It might also have potential as a clinical tool.

Ontogeny and the Application of Pharmacogenomics to Pediatric Drug Development

Drug product labels are important vehicles for conveying the scientific information needed for the safe and effective use of a medicinal product. Increasingly, pharmacogenomic (PGx) information is being incorporated into US Food and Drug Administration-approved product labels. In the majority of cases, the PGx information in labeling is derived from studies in adults. Observed genotype-phenotype relationships in adults may not always be reflective of those in certain pediatric age groups because of the influence of ontogeny. The quantitative data necessary for modeling certain genomic markers in pediatrics is still lacking, and further research focused on generating this is needed. In addition, drug safety research focused on understanding the potential contributions of ontogeny, PGx and other underlying mechanisms to differences in adverse drug reactions between pediatrics and adults is warranted.

Pharmacogenetic Labeling of FDA-Approved Drugs: A Regulatory Retrospective

The U.S. Food and Drug Administration recently marked 10 years since first updating the labeling for warfarin (often referred to as the “poster child” of pharmacogenomics) to include information regarding the potential impact of CYP2C9 and VKORC1 genetic variation on warfarin dosing requirements and risks. Herein, we opine on the experience updating the warfarin labeling, highlighting more generally the enabling factors and challenges encountered when considering incorporation of pharmacogenomic information into the prescribing recommendations for already approved drugs. We also provide a historical perspective of implemented changes in regulatory policies related to personalized medicine.

Genetic structure of pharmacogenetic biomarkers in Brazil inferred from a systematic review and population-based cohorts: a RIBEF/EPIGEN-Brazil initiative

We present allele frequencies involving 39 pharmacogenetic biomarkers studied in Brazil, and their distribution on self-reported race/color categories that: (1) involve a mix of perceptions about ancestry, morphological traits, and cultural/identity issues, being social constructs pervasively used in Brazilian society and medical studies; (2) are associated with disparities in access to health services, as well as in their representation in genetic studies, and (3), as we report here, explain a larger portion of the variance of pharmaco-allele frequencies than geography. We integrated a systematic review of studies on healthy volunteers (years 1968-2017) and the analysis of allele frequencies on three population-based cohorts from northeast, southeast, and south, the most populated regions of Brazil. Cross-validation of results from these both approaches suggest that, despite methodological heterogeneity of the 120 studies conducted on 51,747 healthy volunteers, allele frequencies estimates from systematic review are reliable. We report differences in allele frequencies between color categories that persist despite the homogenizing effect of >500 years of admixture. Among clinically relevant variants: CYP2C9*2 (null), CYP3A5*3 (defective), SLCO1B1-rs4149056(C), and VKORC1-rs9923231(A) are more frequent in Whites than in Blacks. Brazilian Native Americans show lower frequencies of CYP2C9*2, CYP2C19*17 (increased activity), and higher of SLCO1B1-rs4149056(C) than other Brazilian populations. We present the most current and informative database of pharmaco-allele frequencies in Brazilian healthy volunteers.

Considerations for Developing Targeted Therapies in Low-Frequency Molecular Subsets of a Disease

Advances in our understanding of the molecular underpinnings of disease have spurred the development of targeted therapies and the use of precision medicine approaches in patient care. While targeted therapies have improved our capability to provide effective treatments to patients, they also present additional challenges to drug development and benefit-risk assessment such as identifying the subset(s) of patients likely to respond to the drug, assessing heterogeneity in response across molecular subsets of a disease, and developing diagnostic tests to identify patients for treatment. These challenges are particularly difficult to address when targeted therapies are developed to treat diseases with multiple molecular subtypes that occur at low frequencies. To help address these challenges, the US Food and Drug Administration recently published a draft guidance entitled "Developing Targeted Therapies in Low-Frequency Molecular Subsets of a Disease." Here we provide additional information on specific aspects of targeted therapy development in diseases with low-frequency molecular subsets.

A pharmacogenetics approach to pain management

Introduction

Opioid analgesics are widely used as effective analgesics for the treatment of moderate‐to‐severe pain. However, the analgesic efficacy of opioids is well known to vary widely among individuals, and effective pain treatment is hampered by vast individual differences. Although these differences in opioid requirements have been attributed to various factors, genetic factors are becoming increasingly relevant to the development of genome science.

Aim

This review covers the association between opioid analgesic requirements and particularly gene polymorphisms.

Future perspectives

Personalized pain treatment has begun using prediction formulas based on associated gene polymorphisms. Improvements in personalized pain treatment are expected as scientific knowledge further expands in the future.

The analgesic efficacy of opioids is well known to vary widely among individuals, and effective pain treatment is hampered by vast individual differences. Although these differences in opioid requirements have been attributed to various factors, genetic factors are becoming increasingly relevant to the development of genome science. This review covers the association between opioid analgesic requirements and particularly gene polymorphisms.

A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics

Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicity with the underlying genetic composition, particularly in genes encoding for protein factors and enzymes involved in drug metabolism and transport. In several European populations, particularly in countries with lower income, information related to the prevalence of pharmacogenomic biomarkers is incomplete or lacking. Here, we have implemented the microattribution approach to assess the pharmacogenomic biomarkers allelic spectrum in 18 European populations, mostly from developing European countries, by analyzing 1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant inter-population pharmacogenomic biomarker allele frequency differences, particularly in 7 clinically actionable pharmacogenomic biomarkers in 7 European populations, affecting drug efficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on the differences observed in the prevalence of high-risk genotypes in these populations, as far as common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMT pharmacogenes are concerned. Also, our data demonstrate notable differences in predicted genotype-based warfarin dosing among these populations. Our findings can be exploited not only to develop guidelines for medical prioritization, but most importantly to facilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomic testing. This may subsequently contribute towards significant cost-savings in the overall healthcare expenditure in the participating countries, where pharmacogenomics implementation proves to be cost-effective.

Pharmacogenomic Biomarkers: an FDA Perspective on Utilization in Biological Product Labeling

Precision medicine promises to improve both the efficacy and safety of therapeutic products by better informing why some patients respond well to a drug, and some experience adverse reactions, while others do not. Pharmacogenomics is a key component of precision medicine and can be utilized to select optimal doses for patients, more precisely identify individuals who will respond to a treatment and avoid serious drug-related toxicities. Since pharmacogenomic biomarker information can help inform drug dosing, efficacy, and safety, pharmacogenomic data are critically reviewed by FDA staff to ensure effective use of pharmacogenomic strategies in drug development and appropriate incorporation into product labels. Pharmacogenomic information may be provided in drug or biological product labeling to inform health care providers about the impact of genotype on response to a drug through description of relevant genomic markers, functional effects of genomic variants, dosing recommendations based on genotype, and other applicable genomic information. The format and content of labeling for biologic drugs will generally follow that of small molecule drugs; however, there are notable differences in pharmacogenomic information that might be considered useful for biologic drugs in comparison to small molecule drugs. Furthermore, the rapid entry of biologic drugs for treatment of rare genetic diseases and molecularly defined subsets of common diseases will likely lead to increased use of pharmacogenomic information in biologic drug labels in the near future. In this review, we outline the general principles of therapeutic product labeling and discuss the utilization of pharmacogenomic information in biologic drug labels.

Improving the Efficiency and Quality of the Value Assessment Process for Companion Diagnostic Tests: The Companion test Assessment Tool (CAT)

BACKGROUND

Companion diagnostic tests (CDTs) have emerged as a vital technology in the effective use of an increasing number of targeted drug therapies. Although CDTs can offer a multitude of potential benefits, assessing their value within a health technology appraisal process can be challenging because of a complex array of factors that influence clinical and economic outcomes.

OBJECTIVE

To develop a user-friendly tool to assist managed care and other health care decision makers in screening companion tests and determining whether an intensive technology review is necessary and, if so, where the review should be focused to improve efficiency.

METHODS

First, we conducted a systematic literature review of CDT cost-effectiveness studies to identify value drivers. Second, we conducted key informant interviews with a diverse group of stakeholders to elicit feedback and solicit any additional value drivers and identify desirable attributes for an evidence review tool. A draft tool was developed based on this information that captured value drivers, usability features, and had a particular focus on practical use by nonexperts. Finally, the tool was pilot tested with test developers and managed care evidence evaluators to assess face-validity and usability. The tool was also evaluated using several diverse examples of existing companion diagnostics and refined accordingly.

RESULTS

We identified 65 cost-effectiveness studies of companion diagnostic technologies. The following factors were most commonly identified as value drivers from our literature review: clinical validity of testing; efficacy, safety, and cost of baseline and alternative treatments; cost and mortality of health states; and biomarker prevalence and testing cost. Stakeholders identified the following additional factors that they believed influenced the overall value of a companion test: regulatory status, actionability, utility, and market penetration. These factors were used to maximize the efficiency of the evidence review process. Stakeholders also stated that a tool should be easy to use and time efficient. Cognitive interviews with stakeholders led to minor changes in the draft tool to improve usability and relevance. The final tool consisted of 4 sections: (1) eligibility for review (2 questions), (2) prioritization of review (3 questions), (3) clinical review (3 questions), and (4) economic review (5 questions).

CONCLUSIONS

Although the evaluation of CDTs can be challenging because of limited evidence and the added complexity of incorporating a diagnostic test into drug treatment decisions, using a pragmatic tool to identify tests that do not need extensive evaluation may improve the efficiency and effectiveness of CDT value assessments.

Implementation of personalized medicine services in community pharmacies: perceptions of independent community pharmacists

OBJECTIVES

To evaluate the perceptions of independent community pharmacists within a regional independent community pharmacy cooperative on implementing personalized medicine services at their pharmacies and to gauge the pharmacists' self-reported knowledge of pharmacogenomic principles.

DESIGN

Descriptive, exploratory, nonexperimental study.

SETTING

American Pharmacy Services Corporation (APSC), 2011-12.

PARTICIPANTS

Pharmacists (n = 101) affiliated with the independent pharmacies of APSC.

INTERVENTION

Single-mode survey.

MAIN OUTCOME MEASURES

Independent community pharmacists' interest in implementing personalized medicine services, perceived readiness to provide such services, and perceived barriers to implementation.

RESULTS

101 completed surveys were returned for data analysis. The majority of pharmacists surveyed (75%) expressed interest in offering personalized medicine services. When asked to describe their knowledge of pharmacogenomics and readiness to implement such services, more than 50% said they were not knowledgeable on the subject and would not currently be comfortable making drug therapy recommendations to physicians or confident counseling patients based on results of genetic screenings without further training and education. Respondents identified cost of providing the service, reimbursement issues, current knowledge of pharmacogenomics, and time to devote to the program as the greatest barriers to implementing personalized medicine services.

CONCLUSION

The majority of independent community pharmacists are interested in incorporating personalized medicine services into their practices, but they require further education before this is possible. Future initiatives should focus on the development of comprehensive education programs to further train pharmacists for provision of these services.

Prediction formulas for individual opioid analgesic requirements based on genetic polymorphism analyses

BACKGROUND

The analgesic efficacy of opioids is well known to vary widely among individuals, and various factors related to individual differences in opioid sensitivity have been identified. However, a prediction model to calculate appropriate opioid analgesic requirements has not yet been established. The present study sought to construct prediction formulas for individual opioid analgesic requirements based on genetic polymorphisms and clinical data from patients who underwent cosmetic orthognathic surgery and validate the utility of the prediction formulas in patients who underwent major open abdominal surgery.

METHODS

To construct the prediction formulas, we performed multiple linear regression analyses using data from subjects who underwent cosmetic orthognathic surgery. The dependent variable was 24-h postoperative or perioperative fentanyl use, and the independent variables were age, gender, height, weight, pain perception latencies (PPL), and genotype data of five single-nucleotide polymorphisms (SNPs). To examine the utility of the prediction formulas, we performed simple linear regression analyses using subjects who underwent major open abdominal surgery. Actual 24-h postoperative or perioperative analgesic use and the predicted values that were calculated using the multiple regression equations were incorporated as dependent and independent variables, respectively.

RESULTS

Multiple linear regression analyses showed that the four SNPs, PPL, and weight were retained as independent predictors of 24-h postoperative fentanyl use (R² = 0.145, P = 5.66 × 10⁻¹⁰) and the two SNPs and weight were retained as independent predictors of perioperative fentanyl use (R² = 0.185, P = 1.99 × 10⁻¹⁵). Simple linear regression analyses showed that the predicted values were retained as an independent predictor of actual 24-h postoperative analgesic use (R² = 0.033, P = 0.030) and perioperative analgesic use (R² = 0.100, P = 1.09 × 10⁻⁴), respectively.

CONCLUSIONS

We constructed prediction formulas, and the possible utility of these prediction formulas was found in another type of surgery.

Progress towards the integration of pharmacogenomics in practice

Understanding the role genes and genetic variants play in clinical treatment response continues to be an active area of research with the goal of common clinical use. This goal has developed into today's industry of pharmacogenomics, where new drug-gene relationships are discovered and further characterized, published and then curated into national and international resources for use by researchers and clinicians. These efforts have given us insight into what a pharmacogenomic variant is, and how it differs from human disease variants and common polymorphisms. While publications continue to reveal pharmacogenomic relationships between genes and specific classes of drugs, many challenges remain toward the goal of widespread use clinically. First, the clinical guidelines for pharmacogenomic testing are still in their infancy. Second, sequencing technologies are changing rapidly making it somewhat unclear what genetic data will be available to the clinician at the time of care. Finally, what and when to return data to a patient is an area under constant debate. New innovations such as PheWAS approaches and whole genome sequencing studies are enabling a tsunami of new findings. In this review, pharmacogenomic variants, pharmacogenomic resources, interpretation clinical guidelines and challenges, such as WGS approaches, and the impact of pharmacogenomics on drug development and regulatory approval are reviewed.

Pharmacogenetics and cardiovascular disease--implications for personalized medicine

The past decade has seen tremendous advances in our understanding of the genetic factors influencing response to a variety of drugs, including those targeted at treatment of cardiovascular diseases. In the case of clopidogrel, warfarin, and statins, the literature has become sufficiently strong that guidelines are now available describing the use of genetic information to guide treatment with these therapies, and some health centers are using this information in the care of their patients. There are many challenges in moving from research data to translation to practice; we discuss some of these barriers and the approaches some health systems are taking to overcome them. The body of literature that has led to the clinical implementation of CYP2C19 genotyping for clopidogrel, VKORC1, CYP2C9; and CYP4F2 for warfarin; and SLCO1B1 for statins is comprehensively described. We also provide clarity for other genes that have been extensively studied relative to these drugs, but for which the data are conflicting. Finally, we comment briefly on pharmacogenetics of other cardiovascular drugs and highlight β-blockers as the drug class with strong data that has not yet seen clinical implementation. It is anticipated that genetic information will increasingly be available on patients, and it is important to identify those examples where the evidence is sufficiently robust and predictive to use genetic information to guide clinical decisions. The review herein provides several examples of the accumulation of evidence and eventual clinical translation in cardiovascular pharmacogenetics.

Pharmacogenomics: historical perspective and current status

Pharmacogenomics and its predecessor pharmacogenetics study the contribution of genetic factors to the interindividual variability in drug efficacy and safety. One of the major goals of pharmacogenomics is to tailor drugs to individuals based on their genetic makeup and molecular profile. From early findings in the 1950s uncovering inherited deficiencies in drug metabolism that explained drug-related adverse events, to nowadays genome-wide approaches assessing genetic variation in multiple genes, pharmacogenomics has come a long way. The evolution of pharmacogenomics has paralleled the evolution of genotyping technologies, the completion of the human genome sequencing and the HapMap project. Despite these advances, the implementation of pharmacogenomics in clinical practice has yet been limited. Here we present an overview of the history and current applications of pharmacogenomics in patient selection, dosing, and drug development with illustrative examples of these categories. Some of the challenges in the field and future perspectives are also presented.

'Personalized medicine' to identify genetic risks for type 2 diabetes and focus prevention: can it fulfill its promise?

Public health measures are required to address the worldwide increase in type 2 diabetes. Proponents of personalized medicine predict a future in which disease treatment and, more important, prevention will be tailored to high-risk individuals rather than populations and will be based on genetic and other new biomarker tests. Accurate biomarker tests to identify people at risk for diabetes could allow more-targeted and perhaps individualized prevention efforts. DNA variants conferring higher risk for type 2 diabetes have been identified. However, these account for only a small fraction of genetic risk, which limits their practical predictive value. Nor has identification of these variants yet led to new, individualized prevention methods. Further research is needed to identify genomic and other types of biomarkers that could accurately predict risk and facilitate targeted prevention.

Personalizing medicine with clinical pharmacogenetics

Clinical genetic testing has grown substantially over the past 30 years as the causative mutations for Mendelian diseases have been identified, particularly aided in part by the recent advances in molecular-based technologies. Importantly, the adoption of new tests and testing strategies (e.g., diagnostic confirmation, prenatal testing, and population-based carrier screening) has often been met with caution and careful consideration before clinical implementation, which facilitates the appropriate use of new genetic tests. Although the field of pharmacogenetics was established in the 1950s, clinical testing for constitutional pharmacogenetic variants implicated in interindividual drug response variability has only recently become available to help clinicians guide pharmacotherapy, in part due to US Food and Drug Administration-mediated product insert revisions that include pharmacogenetic information for selected drugs. However, despite pharmacogenetic associations with adverse outcomes, physician uptake of clinical pharmacogenetic testing has been slow. Compared with testing for Mendelian diseases, pharmacogenetic testing for certain indications can have a lower positive predictive value, which is one reason for underutilization. A number of other barriers remain with implementing clinical pharmacogenetics, including clinical utility, professional education, and regulatory and reimbursement issues, among others. This review presents some of the current opportunities and challenges with implementing clinical pharmacogenetic testing.

Biomarkers in drug development and regulation: a paradigm for clinical implementation of personalized medicine

The post-genomic era has been hallmarked by significant enthusiasm for therapeutic individualization through the use of pharmacogenomic and other biomarkers. This enthusiasm has been dampened by limited examples of widespread clinical adoption. The current clinical implementation paradigm may not be adequate to facilitate uptake of pharmacogenetics for a variety of reasons. This paper discusses certain limitations of the classical clinical implementation paradigm and describes the drug development paradigm as an additional, powerful mechanism to facilitate clinical implementation of individualized therapeutics.

Animal models in an age of personalized medicine

Personalized medicine is based on intraspecies differences. It is axiomatic that small differences in genetic make-up can result in dramatic differences in response to drugs or disease. To express this in more general terms: in any given complex system, small changes in initial conditions can result in dramatically different outcomes. Despite human variability and intraspecies variation in other species, nonhuman species are still the primary model for ascertaining data for humans. We call this practice into question and conclude that human-based research should be the primary means for obtaining data about human diseases and responses to drugs.