Independent evaluation of BioMate's workflow routing, pharmacokinetic modeling, QC grading, and regulatory compliance capabilities. All numbers are from internal benchmarks run against published reference datasets.
Measured across all 37 biological domains using held-out queries not seen during system development. Each metric is tested with a minimum of 3 independent repetitions.
Validated against FDA first-in-human guidance datasets using 15 reference compounds. All predictions fall within the FDA-accepted 2-fold accuracy window.
| Compound | Prediction Error | FDA Standard | Result |
|---|---|---|---|
| Midazolam | 0.4% | FDA FIH 2005 | ✓ Pass |
| Lorazepam | 0.7% | FDA FIH 2005 | ✓ Pass |
| Gabapentin | 0.9% | FDA FIH 2005 | ✓ Pass |
| Metformin | 9.8% | FDA FIH 2005 | ✓ Pass |
| Theophylline | 17.5% | FDA FIH 2005 | ✓ Pass |
| Atenolol | 34.1% | FDA FIH 2005 | ✓ Pass |
| All 15 compounds | 100% pass rate | — | ✓ Pass |
All predictions within FDA-accepted 2-fold accuracy window. Validated against FDA first-in-human guidance datasets.
Every biological domain handled by BioMate has quantitative pass/fail thresholds derived from published community standards. Gates are independently thresholded at Gold, Silver, and Bronze levels.
| Domain | Gates | Standards Referenced |
|---|---|---|
| Cryo-EM | 3 | Rosenthal & Henderson 2003 |
| Cryo-ET | 3 | Rosenthal & Henderson 2003; Hagen 2017 |
| Protein structure | 3 | Jumper et al. 2021; Tunyasuvunakool 2021 |
| Cancer / somatic variants | 3 | GATK/Mutect2; Strelka2 |
| LNP formulation | 3 | USP standards |
| Population PK | 3 | nlmixr2/NONMEM guidelines |
| Drug discovery | 2 | Le Guilloux 2009; Genheden 2020 |
| High-throughput screening | 2 | Zhang 1999; Iversen 2006 |
| ADME / PK | 2 | Obach 1999; FDA FIH 2005 |
| Clinical trial design | 1 | Liu & Yuan 2015 (BOIN) |
| ICH safety (S5/S7) | 2 | ICH S5R3; ICH S7B |
| Total across 20+ domains | 26 | ENCODE, GTEx, nf-core, FDA, ICH, and domain-specific literature |
Each gate independently thresholded at Gold (all metrics pass), Silver (minor flag), Bronze (below threshold — triggers auto-remediation).
Evaluated on a 100-example FDA drug label dataset. BioMate uses Claude Sonnet 4.6 for regulatory language parsing, adverse event detection, and phase-gating compliance checks.
| Metric | Score | Notes |
|---|---|---|
| Overall (macro average) | 87.1% | Claude Sonnet 4.6 on FDA drug label dataset (n=100) |
| Adversity language detection | 100% | |
| Phase gating accuracy | 100% | |
| Numeric range compliance | 100% | |
| Citation accuracy | 76% |
Benchmarks are run with a minimum of 3 independent repetitions. Routing benchmarks use held-out queries not seen during system development. PBPK validation uses FDA first-in-human reference compounds. Regulatory evaluation uses a 100-example FDA drug label dataset. Results are updated as models and pipelines improve.
In cross-domain routing benchmarks across 120 test cases spanning all 37 biological domains, BioMate achieves 94.6% first-pick routing accuracy — exceeding the 80% target. Routing stability is 100% across independent runs (Cohen’s Kappa = 1.0).
BioMate’s PBPK simulation achieves a 100% pass rate on 15 FDA-standard reference compounds. Prediction errors range from 0.4% (Midazolam) to 34.1% (Atenolol), all within the 2-fold FDA-accepted accuracy window.
BioMate applies 26 quantitative QC gates across 20+ biological domains, each with Gold/Silver/Bronze thresholds based on published community standards (ENCODE, GTEx, nf-core, FDA, ICH).
On a 100-example FDA drug label evaluation dataset, BioMate’s Claude Sonnet 4.6 integration scores 87.1% overall, with 100% accuracy on adverse language detection and phase gating.
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