Integrating AI tools into drug discovery introduces a mix of opportunities and challenges for startups and large pharmaceutical companies. These challenges often center on intellectual property (IP) risks, licensing considerations, M&A due diligence, and documentation practices. This article examines these issues from various perspectives, offering insights tailored to both startups and established industry players.
AI startups in the drug discovery sector must navigate the complexities of IP rights early in their process. For startups positioning themselves as acquisition targets, ensuring exclusivity on drug candidates is critical—losing it could derail potential deals with large pharmaceutical companies. To mitigate these risks, startups should engage IP counsel early to balance their innovative research methods with the risk of adverse IP events and ensure sufficient human contribution to the drug candidate.
Publications require careful consideration. While publishing serves as an essential purpose for marketing and rewarding scientists, startups must manage their messaging through the lens of IP rights. Highlighting AI's role too heavily for marketing purposes may diminish the perception of human inventive activity, potentially leading to weakened IP protections. A poorly timed or overly transparent publication about a fully automated drug discovery process could inadvertently harm the startup’s IP position.
For large pharmaceutical companies, the benefits of AI tools in drug discovery often outweigh the IP risks, but those risks must still be managed strategically. Adopting an AI policy and framework is crucial to ensure that AI tools are used in ways that maximize human contribution to drug discovery and reduce potential IP risk.
When licensing AI tools from third-party AI companies, big pharmaceutical firms should consider including terms in the license agreement to secure all potential IP rights to resulting drug candidates. This is critical, as there are scenarios where a person who trained an AI could be deemed a drug’s co-inventor. Such clauses are not always standard in typical Software-as-a-Service license agreements, making tailored agreements essential.
During acquisitions, especially of startups with AI-discovered drug candidates, large pharmaceutical companies should make AI involvement a core component of their due diligence process. This may involve examining how AI was used in the target company’s drug discovery processes, reviewing academic papers for AI-related disclosures, and analyzing lab notebooks to differentiate between scientists' contributions versus AI contributions. Thorough diligence review of IP rights, including AI involvement, will become increasingly important as AI becomes more prevalent in drug discovery.
In-house counsel in pharmaceutical companies face unique challenges regarding documenting AI involvement in research. Maintaining detailed experimentation records can bring benefits such as informed decision-making in drug candidate selection and better assessment of legal risks. Detailed documentation may also be helpful to provide during the patent application process if AI’s involvement becomes a material fact affecting patentability.
However, determining what level of documentation is appropriate is not straightforward. Over-documenting AI outputs could disrupt research workflows, while traditional lab notebook practices may fail to capture critical details about AI involvement, creating IP uncertainties. The preferable manner of documentation will depend on the research team’s specific situation and the degree to which AI tools are integrated.
The implications of AI in drug discovery on IP rights are complex and multifaceted, affecting startups and big pharmaceutical companies differently. Early understanding of AI's role in IP issues and developing a holistic exclusivity strategy that maximizes IP rights while considering AI tool adoption and due diligence in M&A is vital for a company's success in the pharmaceutical industry. Early engagement with IP counsel and a proactive approach to exclusivity and documentation will be essential for long-term success.
For more insights at the intersection of AI drug discovery and intellectual property, see our publication “Emerging Legal Terrain: IP Risks from AI's Role in Drug Discovery,” published by IP Strategist.