Speakers: Todd Bradley, PhD

Todd Bradley, PhD

Director of Immunogenomics, Genomic Medicine Center, Children’s Mercy
Associate Professor of Pediatrics, UMKC School of Medicine
Assistant Professor of Pediatrics; Pathology and Laboratory Medicine; and Microbiology, Molecular Genetic and Immunology, University of Kansas Medical Center

 

Dr. Todd Bradley is Director of Immunogenomics in the Genomic Medicine Center at Children’s Mercy Kansas City. He is also Associate Professor of Pediatrics at UMKC School of Medicine and Assistant Professor of Pediatrics; Pathology and Laboratory Medicine; and Microbiology, Molecular Genetic and Immunology at the University of Kansas Medical Center. Prior to joining these roles in 2019, Dr. Bradley was a Director and Assistant Professor at the Human Vaccine Institute at Duke University Medical Center. Dr. Bradley leads clinical translational research and development programs to engineer and implement novel diagnostic and therapeutic tools to monitor and regulate the immune system in health and disease. He has over a decade of experience driving translational research at the intersection of genomics, immunology and precision medicine. His work has led to pioneering discoveries in how viruses such as HIV, RSV, SARS-CoV-2 and enteroviruses cause inflammation, and contributed to the design of vaccines and immunotherapies to combat their effects.

 

AI-guided Protein Design to Regulate Inflammatory Responses

Excessive Toll-like receptor 4 (TLR4) signaling is a central driver of numerous inflammatory conditions such as sepsis, acute lung injury, necrotizing enterocolitis and neurodegenerative disease. Current therapeutic approaches to inhibit TLR4 signaling have been limited by poor bioavailability, toxicity or lack of receptor specificity. A critical challenge is to develop effective and selective strategies to disrupt TLR4 signaling during disease without causing systemic immune suppression. This could provide therapeutic tools for blunting pathogenic TLR signaling during that drives tissue damage while preserving beneficial host immune responses. In this project, we designed and optimized peptide inhibitors of TLR4 signaling using deep-learning-based de novo design tools, and tested their therapeutic potential using preclinical cellular and in vivo inflammatory models.