Translational Proteomics for Obesity Clinical Trials

When a patient on a GLP-1 receptor agonist loses significant body weight, hundreds of plasma proteins change. The central analytical challenge is interpretation: which of those changes reflect the drug’s direct mechanism, and which are indirect consequences of weight loss itself? Disentangling these signals is what determines whether a protein change is a real biomarker candidate or an artifact that would mislead clinical decisions.

At Lilly, I work at this intersection of clinical omics and drug development, applying large-scale proteomics (primarily Olink Explore HT and SomaScan 11k) to phase 2 and phase 3 clinical trials for obesity and cardiometabolic disease. The analytical toolkit combines longitudinal mixed models to track protein trajectories over time, mediation analysis to test whether protein changes drive clinical outcomes, dose-response comparisons across treatment arms, and genetic causal inference (Mendelian randomization, pQTL colocalization) to anchor signals in biology rather than confounding. I also build the analytical infrastructure (pipelines, data models, dashboards) that supports the broader clinical omics team.

Related: UK Biobank Pharma Proteomics Project — the foundational proteomics resource that guides some of the analytical work described above.