The scientific benefits and legal risks of AI-driven drug discovery are consequential. But recent IP law decisions allude to a general concept that IP rights will not be awarded if AI completely or significantly replaces human ingenuity in the creative process.
So, how can innovative companies walk this line?
Researchers should still be deemed rightful inventors if they merely use AI to accelerate drug discovery cycles—similar to computer or laboratory tools that have existed for decades. But IP rights come under threat when researchers cross an undefined threshold by allowing AI to replace the human role of inventing. The actual application of this general concept, however, will likely be difficult and uncertain until more case law has developed.
U.S. Patent and Trademark Office (USPTO) guidance has said that “while AI-assisted inventions are not categorically unpatentable, the inventorship analysis should focus on human contributions, as patents function to incentivize and reward human ingenuity.” Importantly: “patent protection may be sought for inventions for which a natural person provided a significant contribution to the invention.”
Conception is often referred to as a mental act that involves the formation in the mind of the inventor of a definite and permanent idea of the complete and operative invention. A related concept that comes after conception is the “reduction to practice”—the process of bringing the mental conception to a tangible form to demonstrate its operability. The USPTO emphasizes that “a human perform[ing] a significant contribution to reduction to practice of an invention conceived by another is not enough to constitute inventorship.”
According to this guidance, a human must make a significant contribution to the “conception” of a new drug for patent eligibility in AI-assisted inventions. What this means for pharmaceutical companies is that using AI as an acceleration tool to assist research may carry less risk to your IP profile as opposed to using AI for full automation of the drug discovery process. For example, a company that uses AI to predict molecule candidates, then uses robots to do the wet labs to test the candidates may carry more risk due to the lack of human involvement.
A unique body of case law has developed in addressing inventorship issues in molecular discovery that is relevant to AI-involved inventions. The Federal Circuit has held that the conception of a chemical compound requires both the idea of the compound’s structure and the possession of an operative method of making it. For inventions related to compounds whose syntheses are unpredictable, courts have held that the conception of a compound requires the inventor to recognize how the compound can be isolated from the rest of the physical environment. Hence, the completion of the conception of a compound that is unpredictable to synthesize requires a researcher to demonstrate that the digital representation can be produced and isolated in physical form. This provides a reliable way to allow significant human contribution in AI-assisted drug discovery.
The evolving law surrounding AI in drug discovery and its effect on IP rights will play a substantial role in how major players in the pharmaceutical industry innovate.
Understanding AI’s role in IP issues early in the drug discovery process will become critical in ensuring a company’s success. It will be vital to develop a holistic exclusivity strategy that maximizes a company’s IP rights in light of AI involvement, but also to understand AI tool adoption and due diligence in M&A.
Since the law governing IP rights in AI-driven drug discovery is still in its infancy, any future legal developments are likely to have profound implications. For example, new court or legislative outcomes may affect:
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.