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3203 Southeast Woodstock Boulevard, Portland, Oregon 97202-8199

https://www.reed.edu/biology/seminars/index.html
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"Start With the End in Mind: How Human Physiological Models Can Redirect Early-stage Drug Discovery"

Drug discovery is a molecular search task with a challenging objective: modify a complex biological system to interrupt disease processes. Conventionally, it is a high failure-rate process – with molecules clearing preclinical hurdles only to fail upon delivery to humans. To help improve the success rate of drug discovery, we should ideally look at design through the lens of human physiology. Quantitative systems models could offer the molecule-to-therapeutic-outcome mapping required to inform AI-driven drug design. However, these models present multiple challenges – from the complexity of the biological pathways and the knowledge gaps limiting model construction to the challenges presented by data limitations and the relative computational expense of mechanistic systems models. In this seminar, I will present our work on integrating mechanistic systems models with data-driven machine learning and generative AI models to empower physiology-informed design of new therapeutics.

Belinda Akpa is a Senior Staff Scientist in Quantitative Systems Biology at ORNL and Joint Associate Professor in Chemical and Biomolecular Engineering at the University of Tennessee. A highly interdisciplinary researcher, her current interest is in developing mathematical frameworks that integrate scarce and heterogeneous data to connect molecular phenomena to dynamic physiological outcomes. Akpa is broadly interested in computational biology, but more specifically in how mechanistic mathematical models can be used to inform targeted experimental strategies. To date, her work has touched the fields of pharmacology/toxicology, membrane biophysics, plant physiology, and forensic anthropology.

11:50 am- Snacks & Socializing
noon- Talk Begins

 

 

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