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Nodes2024

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Ontology-Backed GraphRAG: Injecting Biomedical Logic in LLMs for Drug Discovery

Session Track: Data Science

Session Time:

Session description

This session will dive into the integration of ontology-backed GraphRAG with LLMs for enhanced drug discovery. The speaker will demonstrate how biomedical and custom ontologies can be leveraged to inject domain-specific logic into language models, improving their performance and precision in complex drug discovery research tasks. You'll learn about the technical challenges of combining graph-based retrieval with LLMs and how ontological constraints can guide more accurate and relevant biological predictions. The session will cover implementation strategies and practical insights into its applications in target identification, drug repurposing, and mechanism-of-action prediction.

Speakers

photo of Christopher Li

Christopher Li

CEO & Co-Founder, BioBox Analytics

Christopher Li is the CEO & co-founder of BioBox Analytics, a software company working at the intersection of biology and computer science. Prior to BioBox, Chris was completing his PhD in laboratory medicine with a research focus on pediatric brain cancer.

photo of Hamza Farooq

Hamza Farooq

CTO, BioBox Analytics

As a Full Stack software engineer with a passion for making technological advancements easier to access for everyone, my current focus has evolved into bridging the gap between LLMs and Knowledge Graphs. In my capacity as CTO and co-founder, I have consistently led the delivery of a wide range of product capabilities, ensuring precision and punctuality at every step, while keeping engineering nimble and focused enough to deliver accurately in tight deadlines. My extensive background in bioinformatics continues to drive my mission of solving biological challenges one step at a time.