Day One

• Explore how combining complementary assays (SPR, ITC, NMR, crystallography, DSF, native MS, and DEL screening) enables robust validation of binding events
• Learn how multi-technique strategies can identify novel binding sites, confirm fragment hits, and map allosteric mechanisms, even for RNA-binding or otherwise difficult proteins
• Gain insight into how solution-based, structural, and label-free techniques can converge to tell a consistent story that strengthens confidence in hit identification, characterization, and progression

Get in touch at [email protected]!

Discussion Points Include:

• Explore strategies for prioritizing which biophysical assays to deploy first across diverse target classes
• Discuss how to balance high-throughput screens with deeper mechanistic assays to build confidence in early hits
• Examine how to define “confidence” in binding and progression decisions for challenging modalities, including fragments, PROTACs, intrinsically disordered proteins, and RNA-binding targets
• Share insights into managing conflicting or ambiguous data and deciding which hits to advance

Seize this opportunity to engage with a diverse spectrum of biophysicists from the biopharmaceutical industry, this is your chance to forge connections, exchange ideas, and build collaborative networks. Don’t miss this chance to expand your network and explore the synergies that arise from diverse perspectives in the world of biophysics.

• Learn how focal molography enables direct measurement of biomolecular interactions with native protein working with complex media such as serum, cell lysates or other biofluids serving as native matrices
• Explore how this method complements classical tools such as SPR, uncovering differences invisible in purified systems

• Explore how native mass spectrometry and tailored chemistries enable interrogation of proteins in near-physiological conditions
• Understand strategies to correlate reductionist assay data with cellular or in vivo behavior
• Learn practical approaches to validate and translate binding and functional insights from purified systems to complex biological contexts

Despite advances in high-resolution and high-sensitivity techniques, many biophysical assays still struggle to accurately reflect the complexity of physiological environments. This roundtable allows you to openly discuss with your industry colleagues the persistent challenge of bridging purified, reductionist assay data with meaningful biological and in vivo outcomes.

Participants will explore:

• Where reductionist assays fall short: common sources of artefacts, over-simplification, and false confidence when moving from purified systems to native biological matrices
• Practical strategies to increase physiological relevance: working with biofluids, complex media, membrane mimetics, or intact protein assemblies
• Translational alignment: how teams correlate SPR/ITC/HDX/native MS/focal molography data with cellular, phenotypic, or in vivo readouts
• Operational realities: assay design trade-offs, throughput vs. realism, material constraints, and when “good enough” biophysical insight is truly enough
• Future opportunities: what technologies, workflows, or cross-disciplinary partnerships could help close the reductionist–physiological gap

• Address key obstacles in SPR analysis of membrane proteins, including protein instability on the sensing surface and interference from detergent micelles
• Showcase strategies for optimal detergent selection and membrane-protein stabilization to preserve activity during SPR experiments
• Demonstrate how these optimized conditions enable reliable interaction profiling between small molecules and diverse membrane-protein classes

• Evaluate emerging label-free and solution-based techniques suited for membrane proteins
• Discuss how new detection formats improve signal quality and stability for hydrophobic systems
• Learn how to select orthogonal assays that overcome traditional immobilization limitations

In a relaxed atmosphere explore the latest breakthroughs and innovations in biophysics for drug discovery at our dedicated poster session. Take the opportunity to showcase your own cutting-edge research, receive feedback and gain recognition for your thought leadership! Don’t miss the opportunity to connect, learn, and exchange insights during this dynamic relaxed session.

• Explore the design and triage of proteins with customised and biased functional properties using structure-guided molecular design and iterative design–test–qualify cycles to accelerate early engineering decisions
• Integrate biochemical and biophysical techniques to validate structural hypotheses, ensure reagent fitness, and uncover mechanistic insights through emerging hybrid biophysics approaches
• Deploy a holistic, modality-agnostic biophysics strategy across soluble and membrane proteins, multi-target systems, and diverse modalities to de-risk hit validation and drive high-confidence early discovery

• Show how integrated biophysical and analytical platforms generate model-ready datasets across discovery and development
• Share strategies for combining NMR, SPR/BLI, solution-phase measurements, and developability profiling to power ML-driven cycles
• Discuss practical considerations for data quality, reproducibility, and workflow scalability in AI-enabled drug discovery

• Explore how generative AI models can predict molecular behaviour and biophysical properties from protein stability, ligand-binding trends, and formulation success
• Understand challenges and best practices for validating AI predictions in wet lab experiments
• Explore real-world case study of how AI is accelerating discovery in biophysics

Artificial intelligence and machine learning are transforming the way biophysical data is generated, interpreted, and applied. But beyond the day-to-day integration of AI into experimental workflows, what are the broader opportunities, challenges, and limitations?

This interactive panel brings together leading experimentalists, computational biophysicists, and AI specialists to explore the bigger picture and provides you the opportunity to have honest conversations with your industry colleagues about hype vs. value.

Key Discussion Themes:

• Where can AI add true value in biophysics beyond data processing? Predictive modelling, hit triaging, protein design?
• Which areas of drug discovery are most ready for AI adoption and where should caution succeed?
• The challenges of AI adoption including data curation, standardization, reproducibility, interpretability, and integration with lab workflows
• The evolving role of experimental validation alongside AI predictions, how to ensure we maintain scientific rigor

Blue Sky Thinking & Audience Feedback: In 5 years, what do you hope AI/ML has enabled / transformed the way you do something?