Day Two

• Leveraging structural information to establish computational screening methods
• Disclosure of an inactive state structure of MRGPRX2 in complex with multiple ligands
• Identification of a clinical candidate DA003 as a potent selective antagonist of MRGPRX2

• Reducing manual intervention across sample preparation, data collection and structure determination to improve efficiency and reproducibility
• Identifying key workflow limitations and implementing scalable approaches to increase cryo-EM throughput and accelerate structure generation
• Leveraging optimized workflows and facility capabilities to deliver structural insights faster and support more efficient drug discovery decisions

• Advancing microfluidic sample preparation and multiplexed cryo-EM workflows to increase sample-processing capacity and enable the analysis of multiple antibody–antigen specificities from a single sample
• Applying cryo-EM for polyclonal epitope mapping to rapidly resolve heterogeneous antibody responses, identify distinct antigenic specificities and reduce the need for extensive downstream monoclonal antibody screening
• Automating cryo-EM data collection and processing workflows to accelerate structure determination, standardize analysis and generate actionable outputs across larger numbers of samples

As cryo-EM becomes increasingly important for structure-based drug discovery, the field is facing a fundamental throughput challenge. Long data collection times, limited microscope access, difficult sample preparation, computationally intensive analysis, and manual structure building can restrict the number of structures that can be delivered to discovery teams. Join structural biology leaders, cryo-EM specialists, and technology developers as they discuss how to scale cryo-EM workflows to meet the growing demands of modern drug discovery by:

• Overcoming access and throughput limitations, examining how companies are managing constrained microscope capacity, external facilities, CRO access, and the need to generate sufficient structures to support increasingly large discovery pipelines
• Improving sample preparation and data quality, discussing how grid development, alternative sample preparation approaches, additives, and better understanding of sample-specific behaviour can reduce failed experiments and increase the probability of obtaining high-quality structures
• Automating the cryo-EM workflow, exploring how advances in instrumentation, AI-enabled data processing, automated structure building, and improved computational infrastructure can reduce manual intervention and increase the number of actionable structures delivered to drug discovery teams

• C4 Therapeutics’ Molecular Glue discovery platform has identified novel degrader hits for several targets of high therapeutic interest
• Structural characterization revealed several non-canonical binding modes, expanding the potential target space beyond the prototypic G- and RT-loop motifs
• Early structure enablement accelerated molecular glue development into potent degrader molecules with optimal properties for further drug development

• Applying NMR to characterize higher-order structure and conformational integrity of protein therapeutics to generate detailed structural insights that complement traditional analytical methods and increase confidence in product quality attributes
• Leveraging NMR for product characterization assessments to detect structural changes arising from manufacturing, formulation, process modifications, or storage conditions that may impact therapeutic performance
• Integrating NMR-derived structural data into regulatory strategies and submissions to support higher-order structure evaluation throughout product development and lifecycle management