Clinical trials play an essential role in drug development in helping drug developers better understand the safety and efficacy of a drug in the pipeline. However, a significant barrier to conducting clinical trials lies in their exuberant cost.
Clinical trial simulation provides a means to test and predict the outcomes of different trial designs prior to exposing patients to an experimental drug in development. Clinical trial simulation is an in silico methodology that involves performing Monte Carlo simulations of different clinical trial scenarios to approximate the distribution of possible trial outcomes. The goal of clinical trial simulations is to better understand a drug’s safety and efficacy, as well as optimize clinical trial design. By performing a series of simulations for a given model and clinical trial design, drug develops are able to evaluate design elements of a clinical trial, statistical power and the impact different factors may have on clinical trial outcomes (e.g. patient demographics). In the latter, by being able to evaluate the influence factors may have on trial outcomes, researchers are able to identify patient populations that are more likely to respond to the drug under investigation or have a higher risk of adverse events. Overall, by optimizing a clinical trial design it can increase the likelihood of a successfully conducted clinical trial, identify potential issues in advance, save time and reduce costs.