Day Two

Beyond technical expertise, career progression in biophysics-driven drug discovery and development often depends on visibility, networking, and navigating the evolving landscape between academia, biotech, and pharma. This roundtable creates an open forum for early-career scientists to share experiences, ask questions, and gain insights from senior industry and academic leaders.

• Join a candid, interactive discussion with scientists at different career stages sharing their journeys from the bench to leadership
• Gain practical advice on transitioning between academia, biotech, and pharma, and how to build interdisciplinary expertise across biophysics, chemistry, and computation
• Discover strategies for mentorship, visibility, and professional growth to shape your long-term impact in biophysics and drug discovery.

• Explore strategies to measure binding and functional engagement in cellular or complex protein environments
• Learn how chemoproteomics complements biophysical screening to validate hits and guide compound selection
• Discuss how these approaches inform later-stage translational decisions

• Explore the fundamental challenges of studying proteins that lack a fixed 3D structure and how conformational heterogeneity and how it complicates affinity determination and stoichiometry
• Discuss approaches like NMR, HDX-MS, SAXS, smFRET, and cryo-EM for resolving structural ensembles and learn which is best suited to detect weak and transient interactions
• Learn strategies to interpret biophysical data when no single static structure exists

• Exploring the additional complexities involved in studying dynamic protein degraders
• Understand how biophysics can guide degrader design by revealing ternary complex stability and lifetime
• Discuss design of in vitro systems that better predict cellular degradation outcomes to enhance predictive ability of assays
• Specific methods employed to tease apart affinities and cooperativity in protein complexes and how these insights contribute to the selection and optimization of degrader molecules

• Address complexities of simultaneously engaging multiple targets, including aggregation, crosslinking, and kinetic heterogeneity
• Explore orthogonal biophysical approaches to fully characterize binding stoichiometry, cooperativity, and functional consequences
• Learn practical approaches to design cascades that de-risk false positives and ensure robust candidate selection
• Discuss data interpretation challenges, avidity effects, asymmetric binding, and epitope competition

• Interrogate the unique structural and dynamic challenges of RNA–protein complexes, from disorder and charge density to multi-component assemblies with shifting stoichiometry
• Explore biophysical and biostructural methods adapted for RNP systems including strategies to minimize artefacts, probe conformational heterogeneity, and capture transient or cooperative interactions
• Discuss how hybrid approaches strengthen characterization of RNP behavior, revealing functional mechanisms and improving targetability for emerging therapeutic modalities

• How biophysical tools and insights can translate across the discovery to development interface
• Explore how a collaborative, non-siloed approach can prevent delays and allows for smoother handoff from discovery from IND/CMC stage

Discussion Objectives:

• Examine how discovery, biophysics, and development groups can better align on data expectations, assay design, and molecule risk profiles
• Explore what “good” looks like for a unified biophysical strategy that flows through hit-to-lead, lead optimization, candidate nomination, and IND-enabling stage
• Identify practical quick wins, e.g., earlier aggregation screens, shared risk registers, unified CQAs, or establishing translational biophysics checkpoints, to reduce rework and late-stage surprises

Outcome:

Participants leave with a clearer understanding of how to operationalize an integrated discovery-to-development continuum and actionable ideas for improving their own internal workflows, governance models, and biophysical data strategies.

This interactive, session explore the key lessons, tools, and strategies shared across the summit, and invites participants to reflect on what they will take back to their organizations. This session brings together experimentalists, computational biophysicists, and AI specialists to explore the bigger picture providing you the opportunity to have honest conversations with your industry colleagues about the biggest opportunities for biophysics to evolve across discovery, screening, and analytical development.

Key Discussion Themes:

• What did you learn that will meaningfully change your approach to biophysics, in screening, characterization, or developability?
• Which techniques, workflows, or decision-making frameworks will you apply immediately in your own programs?
• Where are the biggest gaps in current biophysical capabilities and what innovations do we want to see from vendors, academia, and internal R&D in the next 3–5 years?
• How can discovery and analytical groups collaborate more effectively to reduce friction, avoid rework, and increase translational success?
• Which complex targets or modalities remain ‘unsolved,’ and what new tools or cross-functional integrations are needed to unlock them?

Blue Sky Thinking & Audience Feedback: What does the ideal future-state biophysical toolbox look like? High-throughput? Label-free? More physiologically relevant? AI-integrated?