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Date: 2nd June 2023
Time: 14:00 - 16:00
Location: IF 1.15

Title: Drug Mechanism of Action Retrieval using Neurosymbolic Path Finding
Speakers: Lauren DeLong

Researchers I will be collaborating with have discovered novel plant-based drug compounds that possess some therapeutic effect. However, they do not yet understand how these compounds achieve such effects, otherwise known as the drug’s mechanism of action (MOA). Uncovering drug MOAs is non-trivial: while some drug compounds act directly upon a cellular component which induces some therapeutic effect, many others act indirectly through a series of interactions. Therefore, the goal of my internship project is to use neurosymbolic AI on a biomedical knowledge graph to unveil the most likely paths by which these compounds execute their MOAs. By revealing the most likely MOAs, my method will assist the drug discovery process by facilitating a deeper understanding of: (1) how directly or indirectly a given drug compound achieves some therapeutic effect,  (2) what additional therapeutic or adverse effects can be expected from usage of said compound, and (3) how such effects may vary across cell and tissue types.