Redefining Speed in Drug Development
From decades to months. Our Agentic AI doesn't just assist—it accelerates 75% of the pre-clinical workload, delivering market-ready reports in hours.
The Timeline Revolution
Manual discovery takes over a decade. Standard ML/DL brought it down to 4-5 years. PathoscribeAI agents generate actionable reports in hours, compressing the entire pre-clinical timeline to just a few months.
- Report generation in hours
- Total process reduced to months
- 75% of pre-clinical work automated
Validated Against Public Benchmarks
We report performance the way reviewers measure it — against held-out ground truth on open datasets, not a single marketing number. Our repurposing agent is back-tested on repoDB drug–disease associations and ChEMBL bioactivity data; our ADMET and toxicity models are scored on the open Therapeutics Data Commons (TDC) benchmark suite using the same ROC-AUC and MAE metrics published on its public leaderboards.
- Repurposing back-tested on repoDB ground-truth associations
- ADMET & toxicity scored on public TDC leaderboard tasks
- Discovery and repurposing delivered in one agentic workflow
- Evaluation protocol shared with every pilot for independent reproduction
Critical Performance Indicators
Time is Money
Drastic reduction in timelines directly translates to massive cost savings in R&D budgets.
Toxicity, Benchmarked
Toxicity predictions are scored on public TDC tasks (Tox21, hERG, DILI) with standard ROC-AUC, so accuracy is measured exactly the way external reviewers measure it.
Reproducible by Design
Every figure we publish ships with its dataset, metric, and evaluation split. We share the protocol so your team can reproduce our results before you commit.
Our Accreditations
Accreditation details are shared directly with partners during pilot scoping — contact us for documentation.