Each revolutionary change in

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1 The Art and Science of Personalized Medicine M Piquette-Miller and DM Grant If it were not for the great variability among individuals, medicine might as well be a science and not an art. Sir William Osler, 1892 Each revolutionary change in human medicine, from antibiotics to insulin to vaccines, has dramatically improved patient treatment and the quality of public health. Are we now witnessing a revolution in our understanding of genetic contributions to disease and to its treatment? The speed and specificity of emerging genomic technologies and the availability of the complete human genome as a resource have allowed us to more efficiently search for gene variants responsible for drug actions and toxicities in populations and in individual patients. Pharmacogenetics and pharmacogenomics examine how genetic composition affects both disease predisposition and response to therapy and bring the promise of a new era of personalized medicine : delivery of the right drug to the right patient at the right dose (Figure 1). In this regard, it is implicit Osler s quotation above acknowledges that clinicians have always strived to practice personalized medicine, based on knowledge of patient variability and the ascertainment of patient information, including family history. Pharmacogenetics-based prescribing promises to be an additional and potentially powerful tool in the clinician s armament for a still-to-be defined subset of drug-prescribing situations. Current drug development and patient treatment strategies target large patient populations as homogeneous groups on the basis of population means, irrespective of the potential for variation among patients. This one drug fits all method of drug development and use is often neither effective nor safe, with the consequence of high costs to the health-care system. Evidence suggests that, in a significant proportion of patients (ranging from 30% to 60%), many important classes of therapeutic drugs show no clinically significant efficacy, resulting in unnecessary costs to the health-care system and failure to effectively treat disease in individual patients. Morbidity, mortality, and economic costs associated with the occurrence of adverse drug reactions also represent a large burden on the healthcare system, representing the fourth leading cause of hospitalization and being responsible for roughly 100,000 deaths per year in the United States, with an estimated annual cost to the health-care system ranging from $30 to $150 billion. Historical perspective Interindividual variation in drug response has been commented on by clinicians, including Osler, since the late 19th century. Classical pharmacogenetic traits began to be discovered in the 1950s Leslie Dan Faculty of Pharmacy and Department of Pharmacology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada. Correspondence: M Piquette-Miller (m.piquette.miller@utoronto.ca). doi: /sj.clpt CLINICAL PHARMACOLOGY & THERAPEUTICS VOLUME 81 NUMBER 3 MARCH

2 nature publishing group NON-RESPONDERS AND TOXIC RESPONDERS ALL PATIENTS WITH SAME DIAGNOSIS Treat with alternative drug or dose RESPONDERS AND PATIENTS NOT PREDISPOSED TO TOXICITY Treat with conventional drug or dose Rebecca Henretta Figure 1 Pharmacogenomic approach to personalized medicine. Drug therapy is chosen for each patient based on their particular genetic profile. on the basis of clinical observations of aberrant drug response or toxicity phenotypes in a subset of the population, inspiring subsequent research efforts to delineate underlying mechanisms of such anomalies. Early work in the field involved studying mostly monogenic defects in enzymes of drug biotransformation, because these showed easily measurable phenotypes and often high population frequencies. For instance, genetic mutations of the cytochrome P450 and phase II drug metabolizing enzymes occur frequently, and these variants have been linked to changes in drug disposition, efficacy, and toxicity. 1 As is described in this issue, investigators continue to make important strides in the identification and characterization of the role of genetic variants of enzymes in addiction and in the response to immunosuppressant and anticancer therapy. 2,3 These variants may also contribute to ethnicspecific responses to drugs such as the antihypertensives. 4 Likewise, pharmacokinetic variation could stem from alterations in drug transporters, but whether genetic variants of these transporters affect clinical outcomes is still unclear. 5,6 Although the study of genetic influences on pharmacodynamics due to polymorphisms in drug targets is less advanced, in recent years many investigations have uncovered clinically relevant genetic variations in several drug targets. For instance, polymorphisms have been identified in the β 2 -adrenergic receptor, a target for medications used in the treatment of cardiovascular and respiratory disorders. 2 Genetic variants in the µ-opioid receptor are also thought to contribute to the large interindividual variability observed in dosage requirements and response to opioids VOLUME 81 NUMBER 3 MARCH

3 From pharmacogenetics to pharmacogenomics Since the completion of the Human Genome Project, the scientific practice of pharmacogenetics (the phenotype-togenotype experimental approach) has been significantly complemented by the broader discipline of pharmacogenomics. Pharmacogenomics uses high-throughput genomic analysis technologies and computational approaches, along with access to the human genome sequence, to extend beyond the study of monogenic traits of drug metabolism or transport, potentially encompassing the sum of all genes involved in complex diseases and drug responses. Indeed, it is becoming clear that future studies will need to quantify complex associations of polygenic variations that affect both drug pharmacokinetics and pharmacodynamics. Hence, genome-wide association studies are increasingly being used to explain sources of patient variability in disease and therapy. 2 However, the conduct of studies of this nature is still at an early stage, and will require further refinement of experimental design and data analysis. One goal of pharmacogenomic investigations is the targeted therapy of drugs to subgroups of patients according to distinct molecular mutations that drive their disease. In this regard, broad disease classifications such as cancer, hypertension, and diabetes usually reflect at least several mechanistically distinct disorders. The tactic of targeting specific molecular subtypes of disease is being applied in the development of novel anticancer agents. 7 Through their disease subtype selectivity, these new treatments hold the promise of increasing efficacy and tumor responsiveness. Such approaches, which directly identify the protein molecules associated with disease subtype ( molecular phenotyping ) rather than attempt to indirectly predict disease subtype from associated genetic markers, also promise to be powerful tools in optimizing therapy. Barriers to clinical translation Despite significant progress in pharmacogenomics research, relatively little information has been effectively translated into clinical practice. This is the result of several issues, which are discussed here. Interpretation of pharmacogenomic studies. Pharmacogenomic testing will be implemented in clinical practice only in cases where its predictive value for drug effectiveness is high. However, the complexity of genetic interactions, the multigenic origins of disease, and the influence of the environment often will make it difficult to apply pharmacogenetics to the clinic. Thus, an overarching challenge for pharmacogenomics in the future will be to devise effective experimental designs and data analysis strategies for the simultaneous investigation of multiple contributory genetic factors, while at the same time recognizing the degree to which environmental influences may be capable of obscuring genetic associations. To make sense of the generated information, it is clear that high-quality genotyping data must be combined with high-quality clinical patient phenotypic endpoints using powerful data manipulation and statistical analysis. Strength in each of these key elements greatly enhances the likelihood that the process will yield information of use to clinical practice. To achieve these goals, it will be important to involve teams of scientists with complementary expertise. The multidisciplinary, multiinstitution network-based approach of the NIH-funded Pharmacogenetics Research Network is an example of the type of integrated research strategy that is being used to address this issue. 8 With CLINICAL PHARMACOLOGY & THERAPEUTICS VOLUME 81 NUMBER 3 MARCH

4 nature publishing group experts in clinical and basic pharmacology, genomics, and bioinformatics integrated within research teams, an unprecedented collection of investigators with both depth and breadth has been created. Using a diverse array of research strategies and generation of a single publicly accessible database, the network is able to assemble, integrate, and disseminate research findings to the scientific and lay communities. This ensures the timely access, quality, and amalgamation of information to a broad community of stakeholders. Regulatory issues. With the evolution of genotyping technologies, the conduct of genome-wide association studies during clinical trials is becoming more feasible. However, as many pharmaceutical companies consider incorporating genomic testing into drug development programs, their enthusiasm may be tempered by the potential for negative ramifications. Widespread use could result in market segregation and decreased revenue due to exclusion of patient subpopulations, as well as the potential for additional regulatory impositions. If a drug is developed with the knowledge that its efficacy or safety is correlated with a specific set of genetic markers, then use of the drug would ultimately need to be linked to a diagnostic test for that genetic profile. Therefore, establishing regulatory guidelines has been viewed as key in bringing pharmacogenomics-based drugs to the market. With this in mind, integration of pharmacogenomics into drug development is being facilitated through FDA initiatives. Guidance documents released by the FDA in 2005 clarified the circumstances and processes for filing pharmacogenomic data and encouraged voluntary submission of exploratory genomic data. 9 It is hoped that, by offering early informal meeting opportunities and assurances that voluntary information would not be used in regulatory decisions, companies will accelerate efforts to perform and disseminate results of early-stage research. Although the full impact has yet to be realized, regulatory structures pertaining to genomics are being engineered. Costs of testing. Deciding who should bear the costs of pharmacogenomic clinical trials and testing is a source of debate. 10 Currently, the NIH and other publicly funded research granting agencies have borne a large portion of the costs for development of genotype and phenotype testing through sponsorship of academic programs. The pharmaceutical industry also plays a critical role in the discovery and validation of pharmacogenomic biomarkers during the drug development process. However, determining who pays, and the cost effectiveness of these studies may not be as simple when considering the costs of obtaining pharmacogenomic information for off-patent medications. Coverage of diagnostic tests and novel targeted drug products will influence how well the principles of personalized medicine fare in the marketplace. It is plausible that, in time, private insurance payers such as health maintenance organizations will become involved in determining the cost effectiveness of pharmacogenomic testing in larger patient populations. Education. Effective integration of pharmacogenomic information into medical practice and patient care will require a significant effort to educate health-care professionals. The majority of undergraduate programs in medicine and pharmacy currently possess only minimal content in pharmacogenomics. However, primary care practitioners need to become genetically literate as pharmacogenetics becomes increasingly relevant in prescribing decisions. Not only will clinicians need to properly identify which patients or therapeutic interventions 314 VOLUME 81 NUMBER 3 MARCH

5 would benefit from genetic testing, but there will also be an increased complexity in the interpretation of these data, particularly when placed in the context of environmental and pathophysiological influences. The use of integrated healthcare teams that combine complementary expertise in diagnostics, genomics, pharmacology, pharmacokinetics, and therapeutics will be of value in dealing with this complexity. Nevertheless, expansion of current undergraduate, professional, and continuing education programs will be required. As ethical issues and fear of genetic discrimination continue to arise in the general population, it is also crucial to inform and educate the public. Development of novel educational programs that use a variety of methods to aid in learning, such as the visual, gaming, and interactive biomedical imaging techniques described by Wilson-Pauwels et al. (in this issue), may assist in the education of patient and health-care professional groups. 11 Indeed, an interactive multimedia online pharmacogenetics educational program for patients and pharmacists is under development. Summary The ultimate vision for pharmacogenomics is to develop and enable routine use of genetic profiles so as to select drugs that are most likely to be both safe and effective for each patient. Researchers, regulators, and public and private organizations are all making significant strides in discovering, assembling, and interpreting genetic variability information pertaining to disease and drug therapy. Because no single institution or company will have the sufficient resources to develop a genomic prescribing system, a collaborative model must be introduced. US Senator Barack Obama recently proposed Bill 3822, which could rapidly accelerate pharmacogenomics research through the creation of a new agency for personalized medicine. 12 Such an integrative approach to science promises to bring significant breakthroughs in the implementation of individualized therapy and health-care practice. Clinical pharmacologists have driven personalized medicine to its current location and will continue to propel it to its final destination: improved patient care ASCPT 1. Grant, D. & Kalow, W. Pharmacogenetics and pharmacogenomics. In Principles of Medical Pharmacology 7th edn. (eds. Kalant, H., Grant, D.M. & Mitchell, J.) (Elsevier Canada, Toronto, 2006). 2. Giacomini, K.M. et al. The Pharmacogenetics Research Network: from SNP discovery to clinical drug response. Clin. Pharmacol. Ther. 81, (2007). 3. Lévesque, E. et al. The impact of UGT1A8, UGT1A9, and UGT2B7 genetic polymorphisms on the pharmacokinetic profile of mycophenolic acid after a single oral dose in healthy volunteers. Clin. Pharmacol. Ther. 81, (2007). 4. Langaee, T.Y. et al. Association of CYP3A5 polymorphisms with hypertension and antihypertensive response to verapamil. Clin. Pharmacol. Ther. 81, (2007). 5. Glaeser, H. et al. Intestinal drug transporter expression and the impact of grapefruit juice in humans. Clin. Pharmacol. Ther. 81, (2007). 6. Somogyi, A.A., Barratt, D.T. & Coller, J.K. Pharmacogenetics of opioids. Clin. Pharmacol. Ther. 82, (2007). 7. McLarty, K. & Reilly, R.M. Molecular imaging as a tool for personalized and targeted anticancer therapy. Clin. Pharmacol. Ther. 81, (2007). 8. Long, R.M. Planning for a national effort to enable and accelerate discoveries in pharmacogenetics: the NIH Pharmacogenetics Research Network. Clin. Pharmacol. Ther. 82, (2007). 9. Food and Drug Administration. FDA Guidance for Industry Pharmacogenomic Data Submissions. < (March 2005). Accessed 15 December Relling, M.V. & Hoffman, J.M. Should pharmacogenomic studies be required for new drug approval? Clin. Pharmacol. Ther. 82, (2007). 11. Wilson-Pauwels, L., Bajcar, J., Woolridge, N. & Jenkinson, J. Biomedical communications: collaborative research in scientific visualization, online learning and knowledge translation. Clin. Pharmacol. Ther. 82, (2007). 12. Ratain, MJ. Personalized medicine: building the GPS to take us there. Clin. Pharmacol. Ther. 82, (2007). CLINICAL PHARMACOLOGY & THERAPEUTICS VOLUME 81 NUMBER 3 MARCH