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How will generative AI disrupt data science in drug discovery?

Nature Biotechnology volume 41, pages 750–751 (2023)Cite this article

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In the short few months since the release of ChatGPT1,2, the potential for large language models (LLMs) and generative artificial intelligence (AI) to disrupt fields as diverse as art, marketing, journalism, copywriting, law and software engineering is already being realized. These technologies use deep learning models trained on enormous amounts of data to generate new texts or images. While trained only to capture statistical regularities in the training data, their ability, once trained, to imitate human language in a convincing way; to generate realistic images, sounds or software; or to solve tasks apparently involving higher cognitive functions such as reasoning has caught the world by surprise. As such, they are also poised to disrupt in many ways how scientists and engineers understand biology and discover and develop new treatments.

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  1. Owkin, Paris, France

    Jean-Philippe Vert

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  1. Jean-Philippe Vert
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Correspondence to Jean-Philippe Vert.

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J.P.V. is an employee of Owkin.

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Vert, JP. How will generative AI disrupt data science in drug discovery?. Nat Biotechnol 41, 750–751 (2023). https://doi.org/10.1038/s41587-023-01789-6

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