Event sponsored by:
Computational Biology and Bioinformatics (CBB)
Biomedical Engineering (BME)
Biostatistics and Bioinformatics
Center for Advanced Genomic Technologies
Computer Science
Department of Surgery
Duke Center for Genomic and Computational Biology (GCB)
Electrical and Computer Engineering (ECE)
School of Medicine (SOM)
University Program in Genetics & Genomics (UPGG)
Contact:
Franklin, Monica
Speaker:
Rishi Kamaleswaran, PhD
Sepsis, a life-threatening syndrome arising from a dysregulated host response to infection, exhibits significant heterogeneity in clinical presentation and outcome. This complexity underscores the need for refined stratification strategies beyond traditional clinical parameters. This presentation will explore how the integration of multi-omic data (e.g., genomics, transcriptomics, proteomics, metabolomics) can be leveraged to identify distinct sepsis endotypes - biologically and clinically coherent patient subgroups. By correlating these multi-omic endotypes with specific clinical characteristics, including disease severity, organ dysfunction patterns, and treatment responses, we aim to unlock novel directions for understanding the underlying pathophysiology of sepsis. This integrated approach holds the potential to reveal previously unrecognized disease mechanisms, identify novel therapeutic targets, and ultimately pave the way for more personalized and effective interventions tailored to specific sepsis endotypes, thereby improving patient outcomes in this challenging clinical condition.
CBB Monday Seminar Series