Simmons Conference: Dr. Tanner Wilson "Update on Reinforcement Learning-Based Blood Product Resuscitation in Gastrointestinal Hemorrhage"and Dr. Shravan Leonard-Murali "Uveal Melanoma Immunogenomics Predict Immunotherapy Resistance and Susceptibility"

Dr. Tanner Wilson, MD

Update on Reinforcement Learning-Based Blood Product Resuscitation in Gastrointestinal Hemorrhage

We will provide an update on efforts to design a reinforcement learning-based algorithm to guide component blood product resuscitation for ICU patients with GI hemorrhage. We will provide evidence suggestive of improved mortality and other metrics with more liberal, balanced resuscitation strategies, and we will provide an overview of ongoing areas of investigation relating to clinical state space representation strategies in reinforcement learning.

Mentor: Dr. Gilles Clermont, MD; Dr. Harry Hochheiser, PhD

Dr. Shravan Leonard-Murali, MD

Uveal Melanoma Immunogenomics Predict Immunotherapy Resistance and Susceptibility

Immunotherapy targeting immune checkpoint molecules can induce regression of metastatic cutaneous melanoma and improve patient survival. Unfortunately, this therapeutic approach has not shown comparable activity against most other solid tumors, especially those with low tumor mutational burden. We postulated that focused studies of uveal melanoma (UM), a treatment resistant melanoma variant with few somatic mutations, may provide generalized insights to develop improved therapeutics for immunotherapy resistant cancers. Here we summarize a manuscript that profiles the immunogenomic landscape of metastatic UM to uncover tumor microenvironmental properties that underlie its occult immunogenicity and predict its resistance and susceptibility to different immunotherapeutic approaches.

Mentor: Dr. Udai Kammula, MD