My prior training and my immediate and long-term aspirations make this Translational Scholar Award in Pharmacogenomics and Personalized Medicine (K23) an ideal opportunity to further shape my career. Within the past three years I completed a fellowship in Clinical Pharmacology and Pharmacogenomics at the University of Chicago. My fellowship research focused on studying the pharmacogenomics of anticancer drugs. This training allowed me to develop an advanced understanding of pharmacogenomic approaches, and provided me with significant experience in designing and analyzing genome-wide association studies in pharmacogenomics. I developed and initiated two different prospective clinical observational studies with pharmacogenomic primary endpoints. These projects solidified my interest in patient-oriented research, particularly in the field of translaton of pharmacogenomics. The study of pharmacogenomics has allowed the discovery of genetic variants impacting response or toxicity for hundreds of drugs, but the information has infrequently been utilized in prescribing decisions. Implementation has been hampered by skepticism regarding the clinical utility of associations, poor physician knowledge about drug-gene relationships, limited avenues for testing, and delays in the receipt of pharmacogenomic results. I became especially interested in pursuing a clinical research project to assess whether the growing number of emerging pharmacogenomic discoveries could be used in clinical practice if common barriers to implementation could be identified and overcome. It is likely that the efficacious clinical translation of genomic discovery will be mediated by both systems/technology changes and changes in behaviors. This was the genesis for my interest in designing "The 1200 Patients Project"-the clinical research study which is the subject of this application. The study aims to determine whether and how preemptive pharmacogenomic test information might be incorporated into routine clinical treatment decisions by examining 1200 physician-patient pairs. The hypothesis is that a preemptive 'medical system model'for personalized care that makes relevant pharmacogenomic information instantaneously accessible at the time of prescribing will alter knowledge and attitudes about pharmacogenomics in ways that will improve prescribing behaviors. By providing an individualized health care model of preemptive pharmacogenomic testing, I will study how pharmacogenomic information is accessed and utilized by physicians when timely, relevant results are available;its impact on physician prescribing habits and patient and physician satisfaction with care;and the effect of physician knowledge and attitudes/perceptions about pharmacogenomics as mediators of prescribing behavior change. The proposed project is prospectively enrolling and preemptively genotyping (using a panel of variants selected for their pharmacogenomic role) 1200 adults receiving outpatient care. Patient-specific results are available to study physicians through a created research portal, or genomic prescribing system (GPS), which provides instantaneous pharmacogenomic guidance. Encounter-level data will be collected for thousands of visits to assess the aims. It is hypothesized that inappropriate or high risk medications will be less likely to be prescribed to genetically at-risk patients if pharmacogenomic results are preemptively known. In the research plan, I describe the specific methods which will be used to measure the mediators and moderators of prescribing behavior in the context of immediate availability of pharmacogenomic results. I have developed, with input from my mentors, a conceptual framework that combines elements of a dissemination and implementation model, and the self-regulation theory of health behavior.
The aims are written around this model. Successful demonstration of feasibility, and refinement of the model through this study, would then justify application more widely-in diverse practice settings-in future dissemination and implementation projects. The effectiveness, future efficacy, and impact on public health will result not just from the innovative technology we employ to make pharmacogenomic information available, but from our understanding of provider-patient pair decision-making processes involved in promoting and adopting risk-reductive behavior. To be successful in this type of translational work in clinical pharmacogenomics, I need to gain specific training and experience in the areas of knowledge translation/adoption, and behavior change. I have identified new mentors with expertise in these areas to guide my Training Plan. With their direction, I have proposed a comprehensive and customized program of courses and workshops for advanced training in the social sciences and in implementation research. The University of Chicago offers a rich atmosphere of resources and mentorship in which to pursue this training and career development. With such training through this K award, I will be prepared for an independent research career in clinical implementation of pharmacogenomics. Results from the project, combined with my concomitant training, would form the foundation for my first R01 proposal in which many patient-provider pairs from diverse settings could be randomized to preemptive genotyping/GPS availability versus prescribing without pharmacogenomics, to develop more definitive evidence concerning the efficacy and effectiveness of pharmacogenomic testing on adverse drug event/response outcomes and its sustainable dissemination.
Physicians and patients have become increasingly aware that people often react or respond to medications very differently-even when a medication is being used to treat the same condition-and recent research is showing that there may be genetic explanations for this variation between people (pharmacogenomics). Routine consideration of genetic information about drugs could lead to more informed prescribing of medications, allowing treatments to be chosen and/or dosed based upon each individual's personal risk of developing side-effects, balanced against his or her individual chance of receiving benefit. On a population scale, it has the potential to reduce the significant burden of illness caused by drug-induced complications.
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