Drug development is notoriously high-risk, fewer than 10% of new therapeutics make it from Phase I trials to FDA approval, driving costs that can exceed $2.6 billion per drug.
One of the biggest challenges? Making sense of the massive, high-dimensional data generated across preclinical and clinical stages. Traditional analytics and many off-the-shelf AI/ML platforms fall short in synthesizing these complex, disparate datasets into actionable insights.
This white paper explores how BullFrog AI’s bfLEAP™ platform transforms predictive analytics in drug development. Purpose-built for life sciences, bfLEAP™ integrates multi-omics, clinical, and demographic data at scale, revealing hidden multivariate patterns that help researchers:
- Identify novel drug targets and biomarkers
- Optimize patient stratification in clinical trials
- Reduce failure rates and accelerate time-to-market
- Drive precision medicine strategies with explainable AI
Featuring a case study on the landmark CATIE schizophrenia trial, the paper demonstrates how bfLEAP™ uncovered new genetic predictors of treatment response, insights missed by conventional methods
Download the full white paper now to discover how predictive analytics powered by bfLEAP™ can help you reduce risk, cut costs, and unlock breakthrough success in therapeutic development.