The advanced analytics statistical methodology for modelling and forecasting patient recruitment is proposed. It allows forecasting recruitment at different levels (site/country/region) and re-projecting and optimally adjusting recruitment using interim data and Bayesian technique. The technique for optimal selecting sites/countries at the design stage to complete recruitment in time with a given confidence accounting for cost/time constraints is also presented. Further developments to forecasting event counts in event-driven trials accounting for ongoing recruitment are also discussed.
- Modelling and forecasting recruitment at different levels
- Optimal trial design accounting for countries/cost/time constraints
- Data-driven interim re-projecting and optimal adjustment of recruitment
- Forecasting event counts in event-driven trials