Explore the Agenda
8:30 am Registration & Morning Coffee
Workshop A
9:00 am Maximizing the Potential of Cryo-EM: Ensuring Structural Data is Useful Across Discovery Teams
Cryo-EM is now a routine part of many discovery pipelines, yet misunderstanding around how data is generated, what its limitations are, and how long it takes, continue to create friction between structural biologists and the wider discovery team.
This workshop is designed to give non-specialists and structural scientists working cross-functionally; a clear, realistic understanding of the Cryo-EM workflow, from sample preparation and data collection through to model interpretation, without turning the session into a technical training course. The goal is not to teach attendees how to run a microscope or process raw data, but to help them understand what is happening behind
the scenes, why certain experiments succeed or fail, and how that impacts timelines
and decision confidence.
By building shared literacy across structural biology, computational chemistry, medicinal chemistry, and biology, this workshop aims to improve feedback cycles, reduce unnecessary structural effort, and help teams ask better questions of Cryo-EM, before, during, and after data generation.
Workshop Highlights:
- A high-level walkthrough of sample preparation, data collection, and reconstruction, focused on why these steps matter for timelines, resolution, and interpretability
- Understanding the limits of Cryo-EM data and how this can affect downstream design decisions
- Exploring how the availability of predictive models changes when experimental structures are needed, and when cryo-EM is essential to resolving uncertainty
- Helping non-Cryo specialists understand what they can (and cannot) conclude from Cryo-EM data to improve overall communication between structural biologists, chemists and modelers
Workshop B
12:30 pm Integrating the Structural Biology Toolbox: Designing Fit-for-Purpose Workflows in Modern Drug Discovery
As structural biology capabilities expand, drug discovery teams face a more complex challenge: not just generating structures, but deciding which structural and biophysical methods to deploy, when, and for what decision impact.
This interactive workshop moves beyond technique comparison to explore how X-ray crystallography, cryo-EM, cryo-ET, NMR, HDX-MS, native MS, SPR, ITC, and computational modelling integrate into coherent, decision-driving workflows.
Participants will examine how teams balance resolution, cost, speed, and interpretability
while ensuring structural outputs meaningfully inform molecule design, modality selection, and candidate advancement.
Workshop Highlights:
- Explore real-world case studies to learn how other teams integrate structural, biophysical, and computational data streams to manage conformational heterogeneity, validate binding hypotheses, and ensure experimental outputs are fit-for-purpose within discovery programs
- Exploring how X-ray, cryo-EM, NMR, HDX-MS, native MS, SPR/ITC and modelling outputs can be combined into a cohesive workflow that strengthens confidence in binding mode, mechanism, and optimization strategy
- Understanding the value proposition of different discovery teams and how they can best support each other to drive efficiency in discovery workflows
Workshop C
3:30 pm Designing for Success in Biologics Discovery: Structure-Guided & Machine Learning Approaches to Antigen Design & Antibody Engineering
As high-resolution cryo-EM becomes routine for biologics characterization, structure-guided protein design/engineering, increasingly augmented by machine learning, is transitioning from a specialized capability to a core accelerator of R&D timelines. However, many teams continue to encounter common bottlenecks: construct design decisions made too late in the process, inconsistent solubility/stability outcomes, and limited ability to engineer specific properties reliably without repeated iteration cycles.
This practical workshop will equip attendees with a structure-first, ML-informed framework for biologics engineering, emphasizing developability as critical gatekeepers for downstream success. Using literature-based examples and widely accessible tools such as Pymol, the session will demonstrate how structural biologists assess targets, select constructs, and propose engineering strategies achievable within industrial timelines.
Workshop Highlights:
- Construct Selection Strategies: Practical approaches to selecting constructs early in the design process including domains, truncations, linkers, and formats to enhance expression and structural tractability
- Integrated Feedback Loops: How experimental, data science, and ML teams collaborate to transform structural and biophysical data into fewer design iterations
- Hands-On Demonstrations: Step-by-step walkthroughs using published structures and common tools, complemented by peer discussion on how attendees approach similar decisions in their own work