MCS

The objective of this project is to develop an interactive R Shiny application that enables researchers, clinicians, and trial planners to accurately simulate, plan, and forecast patient enrollment in clinical trials by leveraging statistical modeling and simulation-based methodologies. This tool will provide interactive visualizations, real-time forecasting, and probabilistic outputs, improving the planning efficiency and reducing risks associated with recruitment delays.

The R Shiny app will: • Allow users to input clinical trial design details, site activation schedules, and recruitment rates. • Forecast patient enrollment timelines by applying simulation-based methodologies. • Offer customizable probabilistic outputs for decision-making, like expected time to last subject randomization (LSR). • Incorporate realistic assumptions (e.g., site fatigue, seasonal impacts, etc.) to enhance forecasting accuracy. • Provide outputs in interactive visual formats such as dynamic plots, tables, and probability distributions.

Tools and Skills Students will Use and Learn: Implementation of R package and shiny app, nlme, JAGS/STAN

Preference for Student Profile: Proficiency in R and JAGS/STAN