SynBioBeta Speaker
David Virant
Acies Bio
Department Head
David Virant is the Head of Industrial Biotechnology at ACIES Bio, where he directs the development of next-generation microbial cell factories and metabolic engineering initiatives. With a primary focus on sustainable biomanufacturing, his core expertise lies in harnessing C1 feedstocks. He leads the development of novel methodologies for the OneCarbonBio methanol fermentation platform, engineering methylotrophic organisms to convert renewable carbon sources into value-added chemicals.He earned his PhD in 2019 at the Max Planck Institute for Terrestrial Microbiology, where he developed tools and algorithms for super-resolution microscopy to image multi-protein complexes. Building upon degrees in microbiology and post-genome biology, this background provides him with a multi-scale understanding of cellular behavior, from biophysical interactions at the single-molecule level to high-density fermentation dynamics. At ACIES Bio, David applies this blend of deep biological intuition and bioinformatics expertise to build scalable microbial platforms that drive the transition toward a sustainable bioeconomy.
SynBioBeta 2026 Tickets are Live
Confirmed Speakers
Sessions Featuring
David
This Year
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AIxBIO
Rewriting Enzyme Performance: Next-Gen Platforms for AI-Driven Protein Screening
AI is rapidly transforming how therapeutic enzymes and protein drug candidates are discovered, engineered, and validated. Generative models can now propose millions of novel variants optimized for specificity, stability, and target engagement. But the true bottleneck is no longer design, it is screening at scale. As model-generated libraries expand exponentially, the need for faster, more predictive experimental systems has become critical to translate computational insights into clinically relevant performance. This session explores the emerging generation of integrated platforms that combine AI-guided design, high-throughput functional screening, automation, and advanced analytics to accelerate therapeutic protein discovery. From self-driving labs and multiplexed cellular assays to adaptive screening strategies that prioritize pharmacologically meaningful readouts over simple activity metrics, speakers will examine how next-gen infrastructure is reshaping enzyme optimization for drug development.
Purchase Pass
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AIxBIO
Rewriting Enzyme Performance: Next-Gen Platforms for AI-Driven Protein Screening
AI is rapidly transforming how therapeutic enzymes and protein drug candidates are discovered, engineered, and validated. Generative models can now propose millions of novel variants optimized for specificity, stability, and target engagement. But the true bottleneck is no longer design, it is screening at scale. As model-generated libraries expand exponentially, the need for faster, more predictive experimental systems has become critical to translate computational insights into clinically relevant performance. This session explores the emerging generation of integrated platforms that combine AI-guided design, high-throughput functional screening, automation, and advanced analytics to accelerate therapeutic protein discovery. From self-driving labs and multiplexed cellular assays to adaptive screening strategies that prioritize pharmacologically meaningful readouts over simple activity metrics, speakers will examine how next-gen infrastructure is reshaping enzyme optimization for drug development.
Purchase Pass
Session lineup still growing
Purchase Pass
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
