SynBioBeta 2026
The Era of Programmable Biology

For the first time, AI is enabling us to imagine medicines that “think” — turning on only inside diseased cells or under specific physiological conditions. This session explores how neural networks, trained on RNA and protein data, are unlocking programmable therapies with unprecedented precision. Imagine cancer drugs that remain inert until they meet tumor markers, or RNA vaccines that adapt to evolving viral landscapes in real time. The future of medicine isn’t static molecules — it’s intelligent, adaptive therapeutics

The next frontier of biology isn’t in predicting a single static protein structure, but in capturing how proteins move, fold, and interact across time and environments. This session explores how AI can illuminate protein conformations and dynamics, and extend those insights into virtual multi-cellular or tissue models. Experts will discuss the challenge of integrating heterogeneous datasets and instruments, and how breakthroughs in dynamic modeling could reshape drug design, disease understanding, and biomanufacturing. Can we build models that reflect the living, breathing complexity of biology—not just snapshots, but motion?

Scaling bio-based products requires integrated technical collaboration across strain engineering, fermentation, downstream processing, and analytics. Full-stack approaches—where startups, CDMOs, and platform technology providers align early on—can optimize yield, reduce variability, and lower cost of goods (COGS) at commercial scale. This session explores case studies of cross-company collaboration, from co-development of microbial strains and bioreactor designs to shared process analytics and predictive modeling. Hear how teams are breaking down technical silos to accelerate scale-up, improve reproducibility, and create competitive, sustainable manufacturing solutions that bring synthetic biology products from the lab to the market efficiently.

Cells are often described as bags of chemistry—but they are better understood as finely tuned physical systems. Within each one, DNA is packed into nanoscopic volumes, enzymes race at turnover rates rivaling jet engines, and molecular collisions happen billions of times per second. This session explores the cell as a physical object—its limits of size, speed, and efficiency. How fast can information move from genome to protein? How does diffusion constrain cell size and shape? How do energy flows through metabolism define what life can and cannot do? By examining the physics that underpins biology, this session challenges us to see cells not as mysterious black boxes, but as programmable systems operating under universal rules. This perspective may hold the key to engineering biology with the same rigor as physics and computer science.