Cresset

Our CSO Mark Mackey presenting on Agentic AI at #BioTechX today. Mark's talk explores the potential of agentic AI to orchestrate workflows and unify data across platforms - for better connected teams, technologies, and workflows. If you're at BioTechX this week, stop by booth 339 to learn more about our enterprise-ready Flare AI Client released today - enabling you to use natural language to execute workflows, write scripts and analyze results.

No new AI platform to adopt. No new provider to govern. Just a practical way to use natural language for computational chemistry. The Flare AI Client lets scientists connect a company-approved AI provider directly to Flare's molecular design, modeling and analysis capabilities. When a scientist asks Flare to launch a calculation, analyse results or generate a report, the relevant project information is sent to the selected AI provider, not to Cresset.

Flare V13 is out today, and I'm really proud of what the team has delivered. The headline for me is the Flare AI Client, which connects the AI assistant you already use directly to Flare. That connection opens a lot of possibilities. You can ask Flare to find a protein structure and a set of known actives from public sources and load (and display) them directly, no downloads, files to open or other boring tasks. You can set up an FEP calculation (or any other computational method) by describing what you want rather than clicking through every step. And because the AI assistant you already use is already connected to your other in-house tools, results can flow into the next step or out, whether thats a summary for the upcoming project meeting, a comparison against your in-house data or slides for the team. I think the most exciting part is that we don't yet know all the ways scientists will use it. Computational chemistry workflows are diverse and the Flare AI Client can help you automate, or skillify all of them. Equally, adding connections or skills to your corporate AI Assistant makes those available in Flare, widening those workflows even further. Please give it a try and tell us what you build.

Launching Flare™ V12 with major advances in FEP. This release strengthens both the scope and performance of Flare, enabling: - New transformation types, including ring-breaking in a single pathway - >2x faster calculations with the new SOMD2 engine and two-system links - Improved predictive accuracy through replica exchange and GCMC sampling - Expanded MD applicability for covalent ligands and non-standard protein residues Together, these updates allow teams to model more complex chemistry, generate results faster and make more confident decisions across drug discovery workflows. Get in touch for your evaluation.

Want to learn fast, effective approaches for hit and lead optimization? Join our upcoming online workshop where you’ll learn how to: • Explore the active site and key molecular interactions • Generate new molecule ideas • Visualize electrostatic interactions to inform binding modes, SAR, and selectivity • Prioritize designs with docking & MPO Register now to accelerate your design workflows and improve project outcomes: https://lnkd.in/eViskQgP Sessions available at 10am GMT and 3pm GMT so please choose the time that suits you best.

Every R&D leader we speak with is already using AI. Many point out they’ve been applying versions of machine learning for decades. What they want now is AI that delivers measurable value. The strongest signals we heard: • Combining AI and physics based methods is the most promising avenue for progress in drug discovery. • R&D leaders want to be more data driven in how they focus wet chemistry, using simulation insights to prioritise promising compounds. • Discovery teams want tools that better connect computational and medicinal chemists. Read the full customer insights article: https://lnkd.in/etjC7rPv #AIADME #ADMET