GenAI Platform for Medical Research Spin-Outs
Leveraging GenAI to analyze published medical papers and identify high-potential research for commercialization opportunities
Client
University Research Institution
Challenge
The university needed to systematically identify promising research with commercial potential from thousands of published medical papers, but manual review processes were time-consuming and inconsistent.
- Overwhelming volume of published research made manual screening impossible at scale
- Inconsistent evaluation criteria across different research domains and reviewers
- Need to identify early-stage research with significant commercial spin-out potential
Our Approach
We developed a sophisticated GenAI platform that could systematically analyze medical research papers and automatically identify those with the highest commercial spin-out potential using advanced natural language processing and machine learning algorithms.
- Built automated research paper ingestion system to process thousands of publications from major medical journals
- Developed GenAI models to analyze research novelty, clinical relevance, and commercialization potential
- Created scoring algorithm that ranks research based on market potential, patent landscape, and implementation feasibility
Results
The GenAI platform successfully transformed how the university identifies commercial opportunities, processing thousands of papers in minutes and delivering consistent, data-driven research assessments.
- 85% reduction in research screening time, processing 10,000+ papers per month
- Identified 12 high-potential research projects that led to successful spin-out companies
- Platform accuracy improved to 91% through continuous machine learning from expert feedback
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