What patents on AI-derived drugs reveal

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Copyright © 2025 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Document Type

Article

Publication Date

5-29-2025

ISSN

0036-8075

Publisher

American Association for the Advancement of Science

Language

en-US

Abstract

Proponents of the use of artificial intelligence (AI) in drug discovery predict that it is likely to make drug discovery and development faster and cheaper, particularly in preclinical stages before patents are filed (1). But AI use may also create tendencies to file “compound” patents on molecules that disclose little evidence of real-world testing, exacerbating an issue already of concern in more traditional (even if also computer-aided) drug development and patenting. Our preliminary analyses of an original dataset of compound patents on small-molecule drugs suggest that, compared with more traditional drug developers, “AI-native” developers perform less in vivo, in-depth testing before patenting. In light of the potential for such early patenting to dampen overall drug research and development, it is worth considering policies that encourage disclosure of more evidence for securing a patent and provide incentives for research on disclosed but unpatented structures.

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