Evidence-based Bayesian predictions for clinical trial outcomes using academic-grade methodology with peer-reviewed priors from Nature Biotechnology and Harvard Data Science Review
Merck's Phase 3 pembrolizumab plus chemotherapy trial in advanced non-small cell lung cancer with 1,357 patient enrollment and progression-free survival endpoint.
Novartis CAR-T cell therapy in pediatric B-cell acute lymphoblastic leukemia with breakthrough therapy designation. AI identified 23% higher success rate than traditional models.
Hierarchical Bayesian modeling with therapeutic area-specific priors derived from meta-analyses of thousands of clinical trials published in Nature Biotechnology and Biostatistics.
Cross-domain pattern recognition identifies opportunities across therapeutic areas that require deep domain expertise, creating insights human analysts cannot achieve.
Credible intervals, model uncertainty, and data quality scores provide calibrated probability estimates with quantified confidence for strategic decision-making.
Next-generation anti-amyloid therapies with optimized dosing
Novel combination approaches for obesity and diabetes
CRISPR-based therapies for genetic disorders
Access evidence-based Bayesian analysis for any clinical trial with academic-grade rigor and peer-reviewed methodology used by leading biopharma companies.