Enrolment Forecasting

Enrolment forecasting predicts patient recruitment rates for clinical trials using historical trial data, disease epidemiology, and site-specific recruitment capacity. Accurate forecasting enables appropriate site selection, resource allocation, and realistic timeline establishment. Underestimated enrolment rates extend trial duration increasing costs and delaying market access. Over-estimation leads to prematurely closing sites wasting resources. Predictive models incorporating site experience, disease prevalence, and physician referral patterns provide data-driven projections.

Feasibility assessments conducted during trial design employ enrolment forecasting identifying recruitment risks. Real-time recruitment monitoring enables protocol amendments, investigator communication, and site performance assessment. Adaptive trial designs permit interim recruitment rate evaluation with protocol modifications enhancing enrolment. Eligibility criteria refinement balances patient population representation against recruitment feasibility. Digital recruitment strategies employing patient registries and social media improve patient identification. Regulatory expectations emphasise robust enrolment feasibility assessment protecting trial viability.