
Generable Inc. is a pioneering company in Bayesian Scientific Machine Learning, focusing on predictive modeling for clinical decision-making in oncology and rare diseases. Their innovative models, which include Joint Outcome-Biomarker Models and Complex PK/PD Models, are designed to provide accurate predictions and insights for pharmaceutical and biotech companies. By leveraging advanced computational statistics, Generable aims to improve the understanding of biomarkers and treatment efficacy, positioning itself as a leader in the healthcare analytics space.

Generable Inc. is a pioneering company in Bayesian Scientific Machine Learning, focusing on predictive modeling for clinical decision-making in oncology and rare diseases. Their innovative models, which include Joint Outcome-Biomarker Models and Complex PK/PD Models, are designed to provide accurate predictions and insights for pharmaceutical and biotech companies. By leveraging advanced computational statistics, Generable aims to improve the understanding of biomarkers and treatment efficacy, positioning itself as a leader in the healthcare analytics space.
Core focus: Bayesian scientific machine learning for clinical research in oncology and rare diseases
Founded: 2016
Headquarters: New York City
Founders / leaders: Eric Novik, Daniel Lee, Jacqueline Buros
Known investor: Techstars (seed-stage)
Clinical research analytics, trial design, and precision medicine for oncology and rare diseases
2016
Biotechnology
120000
“Techstars-backed seed funding”