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Benefits of Trial Simulator
Exploring your drug and trial designs in Pharsight® Trial Simulator can help your team to:
Build More Informative Trials
Test trial designs against expected drug and subject characteristics to predict the probability of success.
Capture and Communicate the “Knowns” and “Unknowns” About Your Drug and Target Population
Trial Simulator models predict subject responses from subject, drug and disease characteristics. Your modeling team and/or Pharsight consultants build the drug model based on real data—your internal studies, literature data and public databases—using WinNonlin® and similar model fitting tools. Probability distributions in the models capture variability and uncertainty in key model features, including trial-to-trial variation, between- and within-subject variation, measurement error and other unexplained variability, as well as confidence intervals on expected outcomes.
Know the Range of Probable Trial Outcomes
Repeated, Monte-Carlo simulation of each Trial Simulator scenario generates a distribution of the most likely outcomes, so you know not only the most likely subject and trial outcomes, but also the confidence bounds on those outcomes.
Compare Trial Designs Across a Range of Assumptions, to Reduce the Likelihood of Failed Trials
Trial Simulator’s simulation scenarios and replicate-level variability allow your modeling team to simulate outcomes based on different trial design and model settings. Compare different dosing or sampling schemes, trial sizes or analyses. Test your designs against different possibilities for drug potency, subject recruitment or disease severity.
Update Your Simulation With New Information
New data are easily incorporated by editing the drug model, or swapping in alternate model segments.
Minimize Risks and Guide Decision Making
As knowledge accumulates in your Trial Simulator models, the uncertainty in outcomes decreases. Know how likely your trial is to succeed, and avoid surprises by simulating a variety of possible subject, disease and drug scenarios.