Clinical Trial Simulations
Based on advances in statistical methodologies and computational technology, the traditional process for medical research and drug development has evolved to become more time- and cost-effective. In the late 1970’s, the concept of Clinical Trial Simulation (CTS) was conceived, following the successful application of simulations in the auto and aerospace industries. However, pharmaceutical industry applications to assist clinical trial design and drug development did not occur until the mid 1990’s when the power of computing was significantly improved and user-friendly trial simulation tools were developed. The purpose of CTS is to investigate assumptions in clinical trials and to influence trial design in order to maximize the amount of pertinent information gained throughout clinical trial process. CTS is the process of using computer programs to mimic the conduct of a clinical trial based on pre-specified models, which adequately reflect the actual situation being simulated. In general, a model employed in a clinical trial simulation should approximately describe the clinical effects and should reflect the dose-concentration-effect relationships for the drug. The primary objective of the CTS is therefore to describe, extrapolate or predict the clinical trial outcomes. Our research group focuses mainly on AIDS clinical trial simulation. We are developing mathematical models for pharmacokinetics/pharmacodynamics (PK/PD) of antiviral agents, adherence, drug resistance and antiviral responses, as well as developing new statistical methods for parameter estimation in the models. The validity of these models and methods is being tested based on simulated and/or clinical data. CTS software will be developed based on this project. We expect that the developed models and the accompanying CTS software will be used to improve the design of future clinical trials, to study the pathogenesis of AIDS progression, to evaluate new treatment strategies, to select optimal doses and dose regimens, and to maximize the chances of success in clinical trials.