
bfPREPTM
bfPREP™ transforms raw, fragmented biomedical data into clean, harmonized, AI-ready assets you can trust.
- Prepare clinical trial data for analysis
- Harmonize multi-omics, and clinical data sets
- Enable reliable AI/ML drug target discovery
- Accelerate data readinesstrust.

bfLEAP®
bfLEAP® uncovers biologically meaningful patterns, subgroups, and drivers hidden within complex, multimodal datasets.
- Identify responder and non-responder Patient subgroups
- Discover novel drug targets and biomarkers
- Understand disease heterogeneity
- Understand disease mechanisms
- Optimize translational insights from preclinical to clinical

Coming Soon
Convert biological insight into ranked, explainable decisions that drive portfolio confidence.
- Prioritize Drug Targets and development program
- Support indication selection and trial design decisions
- Rank portfolio options by scientific and clinical impact
- Build diversified, risk-balanced R&D portfolios


bfPREP™
Data Harmonization Platform
Data Extraction, Feature Engineering, Schema Design
bfLEAP™
Biomedical Data Analysis
Subgroup and Driver Identification in Complex Datasets
AI Decision Support
AI Decision Support
Define what matters. Get defensible rankings
Whitepapers
AI-Powered Patient Subtyping Reveals Predicted Treatment Responders in a Post Hoc Analysis of a Phase 3 Pancreatic Cancer Trial
A collaboration between BullFrog AI and H. Lee Moffitt Cancer Center, with trial data provided by Eleison Pharmaceuticals. Accepted for…
Data Harmonization: The Hidden Prerequisite for Reliable AI/ML in Life Sciences
Artificial intelligence promises to accelerate drug discovery, but most AI initiatives in biopharma fail before a model is ever trained….
Webinars
Webinar: Turning AI Recommendations into Clear, Defensible Decisions
Friday March 27, 11am EDT Biopharma teams routinely face high-stakes prioritization decisions, including which targets to advance, which biomarkers to…
Vin Singh Appears on RedChip’s AI Conference
See Vin’s presentation about BullFrog AI (BFRG)