Day One

• Compare different AI/ML tools and platforms across enzyme classes and use cases
• Selecting the right computational approach for your specific workflow
• Understand how to combine AI with directed evolution and traditional methods effectively

• Identify key limitations in current enzyme discovery approaches that hinder the implementation of biocatalysis
• Explore how emerging computational approaches are enabling smarter selection of enzyme sequences from vast sequence space
• Learn how to design diverse yet functional libraries to maximize success across multiple transformations

Elevate your networking experience by joining the speed networking session tailored for biocatalysis and enzyme engineering experts, like yourselves, to connect with industry peers and facilitate rapid yet meaningful exchanges of insights and expertise.

• Leveraged AI/ML tools to engineer a KRED capable of dynamic kinetic resolution, achieving ~1,500-fold improvement in enzymatic performance relative to wild-type
• Accelerated enzyme evolution using an ML-guided algorithm, requiring over an order of magnitude fewer variants screened compared to traditional directed evolution
• Conducted a retrospective analysis of ML programs applicable to biocatalysis using data from this campaign; key learnings will be shared

• Understand how accessible AI-driven platforms are enabling faster and more efficient enzyme optimization without extensive coding expertise
• Explore strategies for combining sequence-based, structure-based, and coevolutionary models to improve multiple enzyme properties like expression, activity, and stability
• Learn how computationally guided workflows are reducing screening burden and accelerating biocatalyst development for scalable manufacturing applications

• Identify the key barriers to generating and sharing high-quality enzyme engineering datasets, including standardization, IP constraints, and experimental variability
• Explore approaches for creating robust, industrially relevant datasets that improve model predictability, benchmarking, and decision-making
• Discuss how organizations can leverage automation, high-throughput experimentation, and collaborative data initiatives to accelerate AI-enabled enzyme engineering

• Discuss practical approaches to balancing data sharing with protection of proprietary information
• Share experiences on collaborating with external partners while maintaining competitive advantage
• Identify actionable solutions to unlock data access without compromising commercial interests

Witness the latest cutting-edge research in enzyme engineering and biocatalysis from leading academics, pharma, biotech, and service providers in this dedicated spotlight poster session.

• Explore how biocatalysis and enzyme engineering are enabling more efficient and scalable approaches to new modalities
• Discuss current challenges in enzymatic process development, including reaction optimization, selectivity, and process scalability
• Share perspectives on emerging opportunities for integrating enzymatic strategies into industrial biocatalysis manufacturing workflows

• Explore how photoexcitation is being used to unlock non-native enzyme reactivity and access new catalytic pathways beyond natural biocatalysis
• Discuss emerging strategies for carbon–carbon bond formation via high-energy intermediates within engineered protein active sites
• Highlight recent advances in photoenzymatic catalysis and the potential to streamline the synthesis of complex, biologically relevant molecules