SynBioBeta Speaker
Pardis Sabeti
Harvard
Professor
Pardis Sabeti is a professor at Harvard University and a core institute member of the Broad Institute. Her lab has pioneered technologies for detecting, tracking, and countering deadly pathogens, including Ebola, Zika, and SARS-CoV-2. They have also created some of the most powerful algorithms and molecular tools to characterize the human genome and transformative methods for gene delivery of new biomedicines.
Sabeti co-founded the African Center of Excellence for Genomic of Infectious Disease (ACEGID), training frontline scientists from 53 of 54 African countries. She has taught countless students through popular courses in genetics, statistics and outbreak science. She co-founded SHERLOCK Biosciences and serves on their foundation’s board to bring at-cost diagnostics to low and middle income countries.
Sabeti’s many honors include TIME magazine’s “Person of the Year” as one of the Ebola fighters, 100 Most Influential People, and Impact award. She is a National Academy of Medicine member and Howard Hughes Medical Institute investigator, and holds a B.S. from MIT, D.Phil. from the University of Oxford as a Rhodes Scholar, and M.D. from Harvard Medical School summa cum laude.
SynBioBeta 2026 Tickets are Live
Confirmed Speakers
Sessions Featuring
Pardis
This Year
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From Outbreak Response to Planetary Intelligence: The Sentinel Model for Pandemic Defense in the Age of AI
Emerging infectious diseases remain a growing global threat, yet most outbreaks are still detected only after widespread transmission. In this visionary talk, Pardis Sabeti introduces Sentinel, a locally led, globally connected pandemic prevention network designed to shift biosurveillance from reactive response to real-time planetary intelligence. Sentinel integrates rapid molecular diagnostics, metagenomics, and environmental surveillance with scalable cloud infrastructure and AI-driven analytics. Real-time phylogenetics, transmission reconstruction, and sequence-based modeling enable early detection of unusual biological signals, rapid pathogen characterization, and accelerated countermeasure development. These continuous data streams feed interoperable dashboards and shared analytic platforms that connect laboratories, clinicians, and public health agencies across regions. By embedding advanced technologies within regional centers and pairing them with sustained local capacity, Sentinel operates as a distributed, continuously learning system that transforms biology into actionable intelligence, enabling earlier intervention and a more equitable, proactive model for global outbreak prevention.
Purchase Pass
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From Outbreak Response to Planetary Intelligence: The Sentinel Model for Pandemic Defense in the Age of AI
Emerging infectious diseases remain a growing global threat, yet most outbreaks are still detected only after widespread transmission. In this visionary talk, Pardis Sabeti introduces Sentinel, a locally led, globally connected pandemic prevention network designed to shift biosurveillance from reactive response to real-time planetary intelligence. Sentinel integrates rapid molecular diagnostics, metagenomics, and environmental surveillance with scalable cloud infrastructure and AI-driven analytics. Real-time phylogenetics, transmission reconstruction, and sequence-based modeling enable early detection of unusual biological signals, rapid pathogen characterization, and accelerated countermeasure development. These continuous data streams feed interoperable dashboards and shared analytic platforms that connect laboratories, clinicians, and public health agencies across regions. By embedding advanced technologies within regional centers and pairing them with sustained local capacity, Sentinel operates as a distributed, continuously learning system that transforms biology into actionable intelligence, enabling earlier intervention and a more equitable, proactive model for global outbreak prevention.
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Session lineup still growing
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Featuring
Speaker Coming Soon
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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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Featuring
Speaker Coming Soon
