How it works
ApprovalAlpha estimates the probability that a drug application will receive FDA approval by combining published clinical success rates with real-time signals from public data sources.
DATA SOURCES
ClinicalTrials.gov — Active trials, enrollment pace, and phase advancement history for every program in the pipeline.
SEC EDGAR — Financial filings provide cash runway and insider transaction patterns. 8-K filings are scanned for FDA correspondence including advisory committee outcomes and designation grants.
FDA openFDA API — Drug application records, approval history, and regulatory track record at the company level.
MODEL
A proprietary multi-factor probability model anchored to published phase × indication success rate tables. Each program is scored independently across a set of clinical, regulatory, and financial factors, then combined into a portfolio-level probability.
The model is validated against a historical dataset of FDA decisions using a time-based holdout. Output is a calibrated probability estimate with a confidence interval, not a qualitative rating.
VALIDATION
The model is evaluated on a time-based holdout: calibrated on pre-2021 decisions, tested on 2021–2024 outcomes. The historical dataset spans 257 FDA decisions from 2013–2024 across approvals and complete response letters.
LIMITATIONS
Manufacturing and CMC-related complete response letters are structurally undetectable from public pre-PDUFA data and represent the primary source of model error. All outputs are for research purposes only and do not constitute investment advice.