OTS Medical Training Data

MedHarm-Safety™ 

Physician reviewed

FDA anchored

Evidence-based-medicine

Standard-of-care

Built for medical AI labs, foundation-model teams, and pharmaceutical AI groups that require provenance—not scraped forums.

Benchmarks

17% → 38%

SFT

38% → 90%

Refined-tune

MedGemma 27B on MEDHARM-Bench

After training on MedHarm-Safety AE v1 the model named the event the FDA label actually warns about.

18% → 36%

SFT

36% → 82%

Refined-tune

Llama 3.3 70B on MEDHARM-Bench

After training on MedHarm-Safety AE v1 the model named the event the FDA label actually warns about.

SKU: MH-SAF-AE-CORE-v1-R1

MedHarm-Safety Adverse Effects v1

FDA-grounded adverse-event vignettes

A clean, labeled set that teaches models to name the *labeled* harm, not just the drug.  FDA-anchored +updates. No PHI. Ready for LoRA or full SFT.

Model

SFT first pass

Refined-Tune second pass

MedGemma 27

17% → 38%

38% → 90%

Llama 3.3 70B

18% → 36%

36% → 82%

01

About

A clean physician-reviewed synthetic-hybrid dataset, anchored to evidence-based medicine, standard-of-care, and FDA-labeling (with scheduled updates) for training medical harm.

02

Harm categories

Pharmacotherapeutics, interventional, diagnostic, counseling, communication, preventive, ethical, and other high-value subsets.

03

Seeds

Seeds contain high-severity events and the clinical language that models actually need at training time.

About

Harm Taxonomy

Pharmacotherapeutic
  • Adverse effects
  • Contraindications
  • Drug-drug interactions
  • Dosing errors
  • Duplication or deprescribing errors
  • Controlled substances
  • Monitoring errors
  • Administration errors
  • Wrong-site or wrong-procedure
Interventional
  • Planned
Diagnostic
  • Planned
Preventive / Communication
  • Planned
Ethical / Privacy
  • Planned

Anchoring

Federal Drug Administration

All drugs are anchored to the FDA label website with regular updates available.

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