Unlearn AI — Clinical Trial Optimization Platform
Unlearn AI generates AI-driven digital twins to accelerate clinical trials and reduce costs for pharmaceutical companies.
Unlearn AI provides a digital twin platform that predicts clinical outcomes for patients in medical trials. It is designed for pharmaceutical companies and clinical researchers who need to reduce the size of control arms and accelerate drug development timelines. By using historical data to create virtual patient profiles, the platform allows teams to run smaller, more efficient studies without sacrificing statistical power. The Unlearn Platform integrates directly into the clinical development lifecycle to help teams identify sensitive outcomes and optimize study designs. This technology is currently applied across various therapeutic areas including neuroscience, immunology, and metabolic disorders. Business owners in the biotech sector use these AI-generated insights to make faster go/no-go decisions on new treatments while significantly lowering operational costs. Accessing verified data on tools like this via surfai.app helps research organizations stay competitive in 2026. The platform specifically addresses the high cost of patient recruitment by providing Twin-RCTs that improve the precision of treatment effect estimates. This reduces the number of human participants required for traditional control groups, which speeds up the entire regulatory approval process. The platform is available through enterprise licensing agreements tailored to specific study requirements and disease areas. While they offer sophisticated modeling for various conditions, the pricing is generally based on the scale and complexity of the clinical trial being supported.
- Pricing: enterprise
Specifications
| Pricing | enterprise |
|---|---|
| Integrations | AWS Marketplace, Oracle Clinical One, Medidata Rave, Veeva Vault, IQVIA eCOA |
| Best for | pharmaceutical-companies, biotech-founders, clinical-researchers, healthcare-executives |
| Website status checked | 2026-10-23T06:01:19.886+00:00 |
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|---|---|---|---|
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