A Systems Approach to Designing Effective Clinical Trials Using Simulations

Vincent A. Fusaro; Prasad Patil; Chih-Lin Chi; Charles F. Contant; Peter J. Tonellato

CIRCULATIONAHA.112.123034 Published online before print December 21, 2012

Abstract

Background—Pharmacogenetics in warfarin clinical trials have failed to show a significant benefit compared to standard clinical therapy. This study demonstrates a computational framework to systematically evaluate pre-clinical trial design of target population, pharmacogenetic algorithms, and dosing protocols to optimize primary outcomes.

Methods and Results—We programmatically created an end-to-end framework that systematically evaluates warfarin clinical trial designs. The framework includes options to create a patient population, multiple dosing strategies including genetic-based and non-genetic clinical-based, multiple dose adjustment protocols, pharmacokinetic/pharmacodynamics (PK/PD) modeling and international normalization ratio (INR) prediction, as well as various types of outcome measures. We validated the framework by conducting 1,000 simulations of the CoumaGen clinical trial primary endpoints. The simulation predicted a mean time in therapeutic range (TTR) of 70.6% and 72.2% (P = 0.47) in the standard and pharmacogenetic arms, respectively. Then, we evaluated another dosing protocol under the same original conditions and found a significant difference in TTR between the pharmacogenetic and standard arm (78.8% vs. 73.8%; P = 0.0065), respectively.

Conclusions—We demonstrate that this simulation framework is useful in the pre-clinical assessment phase to study and evaluate design options and provide evidence to optimize the clinical trial for patient efficacy and reduced risk.