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