Key areas of work include: developing and applying causal inference methods (e.g., causal graphs, potential outcomes, propensity and weighting methods, instrumental variables, difference-in-differences, structural causal models) to estimate treatment effects; designing and building digital twins of patients, disease trajectories, or clinical trials, models that combine mechanistic, statistical, or generative approaches and can be simulated under counterfactual scenarios; validating and calibrating those digital twins against clinical and real-world data; partnering with clinical and scientific collaborators to frame questions and communicate insights; and staying current with methodological advances to justify the methods you select. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).