An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials.

Objectives: The main objective of our work was to compare different randomized clinical trial (RCT) experimental designs in terms of power, accuracy of the estimation of treatment effect, and number of patients receiving active treatment using in silico simulations.

Study Design And Setting: A virtual population of patients was simulated and randomized in potential clinical trials. Treatment effect was modeled using a dose-effect relation for quantitative or qualitative outcomes.

Experimental designs for small randomised clinical trials: an algorithm for choice.

Background: Small clinical trials are necessary when there are difficulties in recruiting enough patients for conventional frequentist statistical analyses to provide an appropriate answer. These trials are often necessary for the study of rare diseases as well as specific study populations e.g.

Quantitative prediction of the impact of drug interactions and genetic polymorphisms on cytochrome P450 2C9 substrate exposure.

Background And Objective: Cytochrome P450 (CYP) 2C9 is the most common CYP2C enzyme and makes up approximately onethird of total CYP protein content in the liver. It metabolises more than 100 drugs. The exposure of drugs mainly eliminated by CYP2C9 may be dramatically modified by drug-drug interactions (DDIs) and genetic variations.