The Union of AI and Drug Discovery and Development Requires New Thinking for Structuring and Negotiating Strategic Transactions, and a Rigorous Analysis of Applicable Regulatory Considerations
The use of artificial intelligence and machine learning (AI/ML) in drug discovery and development is well established and here to stay. With AI tools developing the potential to impact virtually every stage of the life sciences product life cycle, the FDA continues to refine its framework for the use of AI to support regulatory decision-making. On April 7, the FDA ended its consultation period on two draft guidance documents, one containing recommendations on the use of AI to support FDA regulatory decision-making and another providing a “comprehensive approach” to the management of risk throughout the total product life cycle of AI-enabled devices. We also saw, in January of this year, the U.S. administration issue the Executive Order Removing Barriers to American Leadership in Artificial Intelligence. These developments, and potential developments, need to be carefully taken into account by life sciences companies that are considering transacting with an AI/ML tool provider.
Chinese Parties to International Licensing Deals Should Consider How Terms Translate
Licensing deals are still relatively new in China compared to the United States and Europe. Tom Duley and Ruchun Ji explain why this means Chinese parties need to be careful about the history of terms and the choice of governing law and arbitration venue when negotiating contracts.
‘Ring-fencing’ Biological Targets in Collaboration Agreements
Stephen Abreu explains how licensors can make sure they do not give a licensee unintended rights to biological targets arising out of their own internal research, or from separate collaborations with third parties.
