SynBioBeta Speaker
Erum Azeez Khan
Messaginglab
Partner
Erum Azeez Khan is a biotech strategist, entrepreneur, and ecosystem builder working at the intersection of science, industry, and narrative. With a foundation in forensic chemistry and a career spanning Big Pharma R&D, global tech ecosystems, and policy advisory, she brings a rare cross-disciplinary lens to the business of biology.As a founding partner at Messaginglab, Erum helps biotech and life sciences companies shape the narratives that drive investment, partnerships, and market entry — translating complex science into compelling strategy for founders, investors, and industry leaders navigating the bioeconomy.Erum is the co-host of Grow Everything, the world's first weekly podcast dedicated to biology as technology. With 160+ episodes, listeners in 70+ countries, and guests drawn from the front lines of synthetic biology, biomanufacturing, and AI-driven discovery, the show has become a go-to resource for the global bioeconomy community.Earlier in her career, Erum co-founded Soundmind, a healthcare tech company she led as CEO through fundraising and a successful exit. She is a passionate advocate for building industries — not just companies — driven by synthetic biology, AI-driven drug discovery, and microbiome intelligence to transform human and planetary health. Based in Brooklyn, she loves discovering the "Brooklyn" of every city, supporting founders, and imagining a biotech-powered future — on Earth and beyond.
SynBioBeta 2026 Tickets are Live
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Erum Azeez
This Year
Session lineup still growing
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Human Health
From Cells to Patients: Solving the Scale Mismatch in Virtual Biology
Drug discovery often measures biology at the cell level while interventions work at the tissue, organ, or whole-patient scale. This mismatch can make accurate cell-level predictions irrelevant in the clinic. This session dives into strategies to bridge that gap: multiscale modeling that nests single-cell dynamics within organ-level simulations, spatial transcriptomics that preserve context, and surrogate models that translate cell-level outputs into clinical biomarkers. Speakers will ask: how do we ensure virtual biology reflects not just what cells do in isolation, but how biology behaves in the real complexity of patients?
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