Proteomics in Clinical Trials: Lessons from Semaglutide Treatment in Individuals with Obesity
Gain insights into mechanisms of action and potential novel indications of semaglutide with high-plex proteomics
Advancements in proteomic profiling have opened new avenues for understanding the complex mechanisms underlying obesity and its comorbidities. By measuring thousands of proteins at once, researchers gain a comprehensive view of an individual’s metabolic health, revealing subclinical processes and pinpointing potential therapeutic targets.
Dipender Gill, PhD, will discuss key learnings from the proteomic data that was captured in the STEP 1 and STEP 2 trials investigating the effects of semaglutide in individuals with obesity with or without diabetes, as well as their implications for the design of future trials that incorporate proteomic data.
In this webinar you’ll learn:
- How measuring more than 6,000 individual proteins in 1,956 participants offered insights to illuminate the mechanisms of weight management and metabolic health, providing a deeper understanding of how semaglutide may exert its effects
- Why incorporating proteomic data early in clinical trial design can optimize the discovery of novel biomarkers and inform targeted treatment strategies for obesity and related conditions
- How real-world proteomic profiles reveal potential benefits for disease-specific proteomic signatures
Dipender Gill, BMBCh, MRCP, CCT, PhD
CEO, Sequoia Genetics
Dipender is a clinician scientist and leading expert in leveraging human genetic data for drug discovery, with over a decade of clinical experience, a PhD in genetic epidemiology and more than 250 research papers to his name. As the CEO of Sequoia Genetics, he combines his background in clinical medicine, academic research and pharmaceutical R&D to integrate genetic insights and enhance the efficiency of drug development.
Proteomics in Clinical Trials: Lessons from Semaglutide Treatment in Individuals with Obesity
A presentation by Dipender Gill, BMBCh MRCP CCT PhD
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