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Combining 3D cell culture & AI to translate drugs to clinical success
Known Medicine combines patient-specific 3D cell culture & AI to translate drugs to clinical success. We receive patient tumors, break them down, make thousands of micro-tumors, and then treat each with different drugs to determine which they will respond best to.
Known Medicine uses a machine learning-based sensitivity assay on living patient cells to predict drug responses, aiming to translate compounds into clinical success. It combines 3D cell culture data with omics to identify predictive biomarkers and likely responders for new drugs. The company positions itself as building a large, purpose-built dataset of patient cancer cell responses to drugs and combinations.
The platform leverages 3D cell culture of patient cancer cells and AI/ML analysis on -omics data to generate sensitivity predictions for drugs and drug combinations. It identifies predictive biomarkers and the most likely responders for any given drug, using a growing dataset of millions of images from patient-derived cells under various treatments to inform predictions and guide clinical and translational decisions.
Who it’s for: Pharma/biotech companies and researchers developing oncology therapies, translational researchers seeking predictive biomarkers and patient response insights, and organizations aiming to predict clinical success of cancer drugs.
Careers and news sections indicate ongoing hiring and activity; the site emphasizes dataset building and collaborations, suggesting ongoing growth and traction.
No founder data available for this company.
How Known Medicine’s homepage introduced itself over the years — each line is the page title the web actually saw, linked to that moment’s archived capture.
Using CRISPR to find treatments for cancer and inflammation
Using the immune system to cure disease
