Case study
PeptPal
PeptPal is a React Native + Expo app backed by FastAPI and PostgreSQL. It tracks inventory, doses, cycles, and biomarkers, while flagging dangerous protocols by comparing user weight against trial cohorts. The core wedge is an evidence engine with trust-tiered citations, harmonic-decayed weighting, and per-peptide hard ceilings.
The brief
Challenge
Peptide forums propagate dangerous default doses copied from trial cohorts that are 60+ lb heavier than typical users, with no per-kg scaling and no source quality signal.
Approach
What we made
Built a per-kg dose scaling layer over a trust-tiered evidence engine, added a first-order degradation model so live vial potency is part of every injection decision, and wrote a weighted forum consensus that promotes bloodwork-backed posts over anecdote.
- Evidence engine spans 17 peptides x 4 personas with trust-tiered citations (A-F).
- Weight-scales every protocol dose and flags 'dangerous' at 1.4x trial per-kg exposure.
- Per-peptide first-order degradation model with live potency bar and dose compensation math.
- Weighted-median forum consensus: bloodwork-attached posts count 5x, 60+ day logs 2x.
- Passphrase-encrypted JSON backup with no server-side storage of user data.
Outcome
Results
A working monorepo mobile app with a functional evidence engine, degradation tracking, biomarker panels, and a tested consensus pipeline.
Gallery
Visual snapshots
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