Artificial intelligence guided discovery of a barrier-protective therapy in inflammatory bowel disease

Debashis Sahoo (), Lee Swanson, Ibrahim M. Sayed, Gajanan D. Katkar, Stella-Rita Ibeawuchi, Yash Mittal, Rama F. Pranadinata, Courtney Tindle, Mackenzie Fuller, Dominik L. Stec, John T. Chang, William J. Sandborn, Soumita Das () and Pradipta Ghosh ()
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Debashis Sahoo: University of California San Diego
Lee Swanson: University of California San Diego
Ibrahim M. Sayed: Assiut University
Gajanan D. Katkar: University of California San Diego
Stella-Rita Ibeawuchi: University of California San Diego
Yash Mittal: University of California San Diego
Rama F. Pranadinata: University of California San Diego
Courtney Tindle: University of California San Diego
Mackenzie Fuller: University of California San Diego
Dominik L. Stec: University of California San Diego
John T. Chang: University of California San Diego
William J. Sandborn: University of California San Diego
Soumita Das: University of California San Diego
Pradipta Ghosh: University of California San Diego

Nature Communications, 2021, vol. 12, issue 1, 1-14

Abstract: Abstract Modeling human diseases as networks simplify complex multi-cellular processes, helps understand patterns in noisy data that humans cannot find, and thereby improves precision in prediction. Using Inflammatory Bowel Disease (IBD) as an example, here we outline an unbiased AI-assisted approach for target identification and validation. A network was built in which clusters of genes are connected by directed edges that highlight asymmetric Boolean relationships. Using machine-learning, a path of continuum states was pinpointed, which most effectively predicted disease outcome. This path was enriched in gene-clusters that maintain the integrity of the gut epithelial barrier. We exploit this insight to prioritize one target, choose appropriate pre-clinical murine models for target validation and design patient-derived organoid models. Potential for treatment efficacy is confirmed in patient-derived organoids using multivariate analyses. This AI-assisted approach identifies a first-in-class gut barrier-protective agent in IBD and predicted Phase-III success of candidate agents.

Date: 2021
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DOI: 10.1038/s41467-021-24470-5

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