Facilitating and Enhancing Biomedical Knowledge Translation: An in Silico Approach to Patient-centered Pharmacogenomic Outcomes Research

Abstract

Current research paradigms such as traditional randomized control trials mostly rely on relatively narrow efficacy data which results in high internal validity and low external validity. Given this fact and the need to address many complex real-world healthcare questions in short periods of time, alternative research designs and approaches should be considered in translational research. In silico modeling studies, along with longitudinal observational studies, are considered as appropriate feasible means to address the slow pace of translational research. Taking into consideration this fact, there is a need for an approach that tests newly discovered genetic tests, via an in silico enhanced translational research model (iS-TR) to conduct patient-centered outcomes research and comparative effectiveness research studies (PCOR CER). In this dissertation, it was hypothesized that retrospective EMR analysis and subsequent mathematical modeling and simulation prediction could facilitate and accelerate the process of generating and translating pharmacogenomic knowledge on comparative effectiveness of anticoagulation treatment plan(s) tailored to well defined target populations which eventually results in a decrease in overall adverse risk and improve individual and population outcomes. To test this hypothesis, a simulation modeling framework (iS-TR) was proposed which takes advantage of the value of longitudinal electronic medical records (EMRs) to provide an effective approach to translate pharmacogenomic anticoagulation knowledge and conduct PCOR CER studies. The accuracy of the model was demonstrated by reproducing the outcomes of two major randomized clinical trials for individualizing warfarin dosing. A substantial, hospital healthcare use case that demonstrates the value of iS-TR when addressing real world anticoagulation PCOR CER challenges was also presented.