
The global rise of antimicrobial resistance (AMR) has created an urgent need for new chemical modalities to combat drug-resistant pathogens. In response, researchers are increasingly turning to generative AI to explore untapped regions of chemical space beyond traditional screening libraries.
A recent breakthrough from the Broad Institute of MIT and Harvard showcases this potential. Using deep learning models, the team designed novel antibiotics with modes of action distinct from current treatments. Their AI system screened over 45 million chemical fragments in silico against Neisseria gonorrhoeae and Staphylococcus aureus, two high-priority pathogens. From this dataset, they identified two standout compounds, named NG1 and DN1, with potent and selective antibacterial activity.
The question then is, if an AI designed the compounds, who owns the invention?
In 2023, the UK Supreme Court ruled in Thaler v Comptroller-General of Patents that an AI system cannot be named as an inventor under current law. Since patent rights are derived from the inventor, can the Broad Institute claim ownership over these compounds?
The paper from the research team makes it clear that human researchers played a critical role, such as the selection of compounds that were synthetically tractable (meaning a human chemist could feasibly produce them). Interestingly, the researchers refined the AI-generated leads through conventional medicinal chemistry; the team synthesized around 100 analogues of the compounds, some of which showed even greater potency than the original AI-designed molecules.
With over 30 authors listed on the paper, any resulting patent application will likely have several human candidates for patent inventorship. The AI may have opened up the chemical space, but human expertise found and synthesized the viable drug candidates.
Either way, this study demonstrates that an iterative design process, powered by AI, can enable the discovery of drug-like molecules not derived from existing libraries, which could be a major advantage in the fight against AMR.
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“We’re excited about the new possibilities that this project opens up for antibiotics development. Our work shows the power of AI from a drug design standpoint, and enables us to exploit much larger chemical spaces that were previously inaccessible,” says James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering.