QTL – R Package Creation

Context: Global pharmaceutical company requiring robust Quality Tailoring Limit (QTL) frameworks for clinical trial data integrity across 2,000+ studies.

Challenge: Needed to compare posterior data with prior data at specified intervals to uncover data fabrication and perform fraud detection, all while generating audit‑ready comparative reports.

Solution: Built 2 production‑grade R packages using the Golem architecture, applying:

• Bayesian methodology for probabilistic fraud detection
• Monte Carlo simulation to model uncertainty and compare distributions
• Generating Excel and HTML reports via R‑markdown scripts for adverse events (AE, SAE, BPD, OPD) and multi‑site visualization plots

Outcome: Provided standardized, audit‑ready comparative reporting across global clinical sites, enabling faster regulatory submissions and consistent fraud detection.