Predicting treatment responses to novel antihyperglycemic therapies

Using a machine learning-guided method of computational trial phenomapping, E2H co-founders led the development of INSIGHT, a novel online tool that can guide sodium-glucose cotransporter-2 (SGLT2) inhibitor therapy in type 2 diabetes mellitus. Based on the science behind TrialMap, the authors analyzed individual participant-level data from the CANVAS and CANVAS-Renal trials, deriving and validating phenotypic signatures of individualized cardiovascular benefit with canagliflozin use. 

The full results can be accessed at: https://diabetesjournals.org/care/article-abstract/doi/10.2337/dc21-1765/144528/Phenomapping-Derived-Tool-to-Individualize-the?redirectedFrom=fulltext 

The INSIGHT tool is available at: https://www.cards-lab.org/insight 

Read more at: https://medicine.yale.edu/news-article/introducing-insight-a-machine-learning-approach-to-managing-diabetes-and-cardiovascular-risk/