Hey HN, I built this because I was trading biotech stocks and got tired
of manually tracking PDUFA dates, FDA decisions, and trial readouts
across multiple sources.
What it does:
- Aggregates ~1000 biotech companies from ClinicalTrials.gov, SEC EDGAR, FDA
- Daily data sync
- ML predictions for catalyst impact (XGBoost) and likelihood of approval
(Random Forest)
Technical details:
- XGBoost model trained on historical catalyst events
- Features: catalyst type, phase, therapeutic area, market cap, price momentum
- Random Forest for LOA scores based on BIO 2024 clinical success benchmarks
- Weekly model retraining
The ML part is experimental - I'm genuinely not sure if it's useful or
just fancy noise. Would love feedback from anyone who trades biotech or
has experience with financial ML.
nykodev•8h ago
What it does: - Aggregates ~1000 biotech companies from ClinicalTrials.gov, SEC EDGAR, FDA - Daily data sync - ML predictions for catalyst impact (XGBoost) and likelihood of approval (Random Forest)
Technical details: - XGBoost model trained on historical catalyst events - Features: catalyst type, phase, therapeutic area, market cap, price momentum - Random Forest for LOA scores based on BIO 2024 clinical success benchmarks - Weekly model retraining
The ML part is experimental - I'm genuinely not sure if it's useful or just fancy noise. Would love feedback from anyone who trades biotech or has experience with financial ML.
Free tier: 3 predictions/day + full calendar Paid tiers: unlimited predictions, smart money signals, entry timing
Happy to answer questions about the data pipeline or ML approach.