Leveraging Mendelian Randomization for Drug Development: A Case Study using Epiregulin Antagonist

Music City Center 

A growing body of research indicates that drug candidates with genetically supported targets have a significantly higher probability of success compared to those without such evidence (Minikel et al., 2023). Mendelian Randomization (MR), a method that leverages genetic variants as instrumental variables, is an ideal approach for inferring causal relationships. Eli Lilly is not alone in using MR to inform clinical decision-making, and companies like Alector and GSK are employing similar strategies to explore PGRN targeting for Alzheimer's treatment. However, our unique proposed approach has successfully identified and validated gene targets preclinically. More recently, this tool has been applied to inform the clinical development of LY3848575, an epiregulin antagonist for polyneuropathic pain (Study CYAB: NCT06568042). Our analysis explored its pathways in both diabetic peripheral neuropathic pain and polyneuropathic pain, revealing comparable effect sizes. Overall, this approach extends beyond traditional clinical trial design by integrating genetic data into decision-making. In this talk, we will provide MR overview and share key results.

Mendelian Randomization

Polyneuropathic Pain

Diabetic Peripheral Neuropathic Pain

Epiregulin Antagonist

Clinical Trial Design 

Biopharmaceutical Section