White Paper: Model-Based Approach for Better Enrollment Forecasting

February 4, 2022

According to the Clinical Trials Database, low recruitment rates were the largest factor determining whether a trial would terminate in 2018. However, data-driven insights from advanced simulations can help ensure accurate recruitment forecasting. A new white paper from Cytel explains how Monte Carlo simulations can help researchers make better recruitment estimates for clinical trials.

According to the white paper, “A model-based approach captures two realities of the enrollment process. The first reality is that enrollment is nonlinear. Different sites may open at different times, so that enrollment starts very gradually, but then accelerates over time as more sites come on board. The second reality is that enrollment is random. A different number of patients will be recruited from one week to the next, simply due to chance. A model-based approach can easily accommodate these two basic facts(nonlinearity and randomness), which would be impossible using conventional methods alone.”