FlashPath AI offers a data‑first platform that cleans, harmonizes, and structures millions of preclinical toxicology records into a unified, AI‑ready repository.
Funding
Funding not disclosed
Founders
Product
Problem
Preclinical toxicology records are stored in disparate formats and legacy systems, making them inconsistent, difficult to access, and unsuitable for large‑scale analysis. This fragmentation hampers mechanistic insight, slows safety assessment, and contributes to high failure rates in clinical development.
Solution
FlashPath AI provides a data‑first platform that cleans, harmonizes, and structures millions of animal toxicology records into a single, AI‑ready repository. The unified dataset supports lesion‑level enrichment and cross‑study analysis, enabling researchers to build high‑fidelity predictive safety models. By linking preclinical findings with real‑world clinical adverse event signals, the platform helps safety scientists and modelers derive mechanistic insights and make more informed drug‑development decisions.
Target Audience
Primary customers are pharmaceutical and chemical companies, as well as contract research organizations and safety teams that need reliable preclinical toxicology data for predictive modeling and risk assessment.
Features
- Automated extraction and standardization of toxicology data from legacy files, databases, and study reports
- Unified schema that captures lesion‑level details, dosing information, and study metadata for cross‑study queries
- Scalable cloud infrastructure that stores cleaned data and provides API access for downstream analytics
- Built‑in tools for translational mapping of animal findings to clinical adverse event datasets (e.g., ToxiDex™ to FlashAE)
- Support for AI/ML model development with ready‑to‑use, high‑quality training datasets
- Transparent data provenance and domain‑expert validation to ensure scientific rigor