Artificial Intelligence is reshaping drug discovery. At SF @Tech Week by a16z, we co-hosted a fantastic session with @a16z on the rise of the AI-native scientist, where data-first labs, agentic systems, and copilots are changing discovery.
Our top legal takeaways for teams building with agents and copilots:
- Human Inventorship: Only human inventors qualify for patents, which are fundamental for foundational discoveries. AI solutions should be implemented making room for intellectual human involvement, setting inventive criteria for patentable inventions.
- AI-Expert Collaboration: AI solutions provide compounded value when they allow for leveraging scientists' expertise.
- Data is King: There is broad consensus that high-quality data sets suitable for AI solutions are crucial to extract the most value from the AI revolution. Companies focus their data-collection efforts by incrementally testing with AI tools what data sets will be most valuable.
- User-Level Institutional Contacts and Adoption: Adoption is much likelier when AI solutions are procured and deployed by contacts that are close to intended users. VP-level engagements are much more likely to fail adoption. Interoperability of data sets is another bottleneck to adoption.
- Friction in IP Ownership Terms: Traditional pharma insists on ownership of all outputs for volumes disproportionally larger than payments involved, and AI providers experiment with commercial frameworks for faster adoption.
- Custom Legal Terms: High demands by pharma require customized legal terms, a deviation from traditional SaaS businesses that run on standard terms.
Thank you to all attendees and speakers. We’re looking forward to what comes next in AI-enabled drug discovery. Learn more about Fenwick's life sciences capabilities.
