Hamza Farooq
Co-Founder and CTO at BioBox
Toronto, Canada
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Hamza Farooq is the Co-Founder and Chief Technology Officer of BioBox Analytics, where he leads the development of graph-powered AI systems designed to accelerate drug discovery. His work centers on applying knowledge graphs, GraphRAG, and agentic architectures to transform complex biomedical data into reliable, interpretable tools for scientific reasoning.
With a background in bioinformatics and production-scale AI systems, Hamza brings a practitioner’s perspective to building AI for biology—grounded in real data, real users, and real constraints. He regularly works with pharma and biotech teams to move graph-based AI beyond demos and into production, enabling scientists to explore evidence, connect concepts, and generate insights at scale.
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Ontology-backed GraphRAG: Injecting biomedical logic in LLMs for drug discovery.
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.
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