Drug discovery often measures biology at the cell level, while therapies must ultimately work across tissues, organs, and whole patients. This scale mismatch means that even highly accurate cellular predictions can fail to translate in the clinic. This session explores strategies to bridge that gap. How do we connect single-cell dynamics to organ-level physiology and patient outcomes? How do we preserve biological context while scaling models? And how do we ensure that virtual biology does not stop at simulation, but informs real therapeutic decisions? Speakers will discuss multiscale modeling that links molecular and cellular systems to higher-order biology; spatial and high-dimensional phenotypic data that retain context; and integrated computational–experimental loops that translate cellular signals into clinically meaningful biomarkers. Together, we ask: how do we ensure virtual biology reflects not just what cells do in isolation, but how biology behaves in the full complexity of patients?

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 to commercial production requires balancing technical readiness with market and financial realities. This session examines the capital investments, regulatory planning, and supply chain strategies necessary to move beyond the pilot stage. Experts will share lessons on aligning production capacity with demand forecasts, managing operational risk, and structuring partnerships that unlock funding and market access. Attendees will gain practical insights into navigating investor expectations, scaling efficiently without compromising quality, and making strategic decisions that ensure products can succeed commercially while meeting evolving market needs and sustainability goals.

Why do so many in silico models fail when moved to the lab or clinic? Too often, they’re trained on incomplete, non-human, or non-representative datasets. This session tackles the “data gap” head-on: from interoperability bottlenecks and the black box problem to the limits of current virtual cell simulations (~50 million perturbations vs. the billions biology demands). Panelists will explore how to create “human-first” datasets that reflect real biology, unlock mechanistic interoperability, and close the discovery–development divide. The goal: build AI tools that can directly identify viable drug candidates instead of stalling in silico.

For over a century, antivenoms have relied on serum extraction from animals — a process that’s costly, inconsistent, and limited to specific snake species. Today, advances in synthetic biology and antibody engineering are pointing toward a different future: a universal antivenom capable of neutralizing toxins across the world’s deadliest snakes. This session dives into the science and story behind this breakthrough — from the man who endured more than 200 bites to generate a unique immune response, to the researchers using those antibodies to design broad-spectrum, recombinant therapies. Together, they’re charting the path from survival experiment to programmable immunity.

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.

Biology is entering an era where AI agents don’t just analyze data — they co-design, plan, and execute experiments. Multi-agent systems like CRISPR-GPT demonstrate how AI can act as a true lab co-pilot: decomposing complex genome editing projects into stepwise workflows, selecting tools, troubleshooting, and even drafting protocols that allow junior researchers to perform sophisticated edits on their first attempt . Beyond CRISPR, new systems like BioMARS integrate reasoning agents with robotics, while biotech companies are testing “AI lab assistants” that monitor and adjust experiments in real time. This session explores how multi-agent copilots are making biology more reproducible, democratizing complex workflows, and pushing the boundaries of lab autonomy. The central question: when AI can plan, troubleshoot, and validate experiments end-to-end, how should scientists and institutions govern this new power?

Biology is entering an AI-driven era, but most experimental infrastructure still produces data designed for individual experiments, not for learning at scale. As a result, much of today’s data is useful in the moment but poorly suited for training robust, long-lived models. This session will explore what biological data matters most today, what data needs to be generated now to support future models, and how leading teams are closing that gap. Panelists will discuss how automation, metadata discipline, and standardized testing pipelines can turn artisanal lab workflows into continuous experiment-to-learning systems. The focus will be on infrastructure and experimental design, highlighting practical bottlenecks, emerging best practices, and what becomes possible when biology produces abundant, high-quality, model-ready data by default.

Plant-based food sales may be slowing, but that doesn’t mean innovation on the plate is stalling. Instead, momentum is shifting toward breakthrough technologies and smarter ingredient combinations. Cultured meat and precision fermentation are driving the next wave of sustainable ingredients, from proteins to cultured fats that bring authentic flavor and texture. This session highlights advances in cell culture, fermentation platforms, and scale-up strategies, along with the partnerships moving products from R&D to dining tables. Hear how food innovators are combining biology and culinary creativity to build a resilient, delicious, and sustainable future for global diets.

As biology becomes programmable and AI accelerates discovery, startups are generating breakthrough innovations at unprecedented speed. Yet translating these advances into real-world therapies still depends on effective collaboration with global pharmaceutical organizations. This session explores how the innovation ecosystem connects early-stage breakthroughs to scalable development, bringing together leaders from startup incubation, external innovation, and pharma strategy. Speakers will examine how AI-native biotech companies engage with pharma today: how startups become “pharma-ready,” how external innovation teams evaluate and structure partnerships, and what collaboration models are emerging as biology and computation converge. From early ecosystem support and venture building to strategic alliances and co-development pathways, the discussion will provide a practical look at how ideas move from discovery to patient impact in the AI era.

Reading, writing, and editing DNA were just the prelude. The next frontier is composition, designing complex genetic systems and large DNA architectures from first principles using AI-driven models and scalable synthesis technologies. As datasets grow and design tools mature, biology is shifting from incremental editing toward intentional genome-scale engineering. This new paradigm treats DNA not simply as a sequence to modify but as a programmable substrate where genes, regulatory elements, and entire genomic regions can be composed, tested, and iterated like engineered systems. Advances in generative design, large-scale DNA assembly, and precision integration technologies are enabling researchers to construct increasingly complex genetic structures with higher predictability and functional intent. From next-generation recombinases and genome restructuring platforms to AI-guided design workflows that bridge computation and physical DNA construction, the emerging toolkit is redefining how biological complexity is created. The session explores how compositional genome engineering could unlock new capabilities across therapeutics, industrial biology, and synthetic life design.

Biotech is no longer behind the scenes—it’s on our shelves, in our homes, and part of our daily routines. From sustainable haircare to household cleaning, and high-performance materials, bio-based innovations are redefining everyday consumer experiences. This session explores what drives adoption, how brands communicate the value of biology, and why trust, transparency, and performance are key to building loyalty. Join us to hear from the companies making biology irresistible, accessible, and seamlessly integrated into daily life—and learn what it takes to create bio-products consumers truly love.