Date: 18 August 2026 (Tuesday)
Time: 4pm BST | 11am EDT | 8am PDT | 5pm CEST
A prediction looks convincing. Is that actually a reason to trust it?
For most discovery teams working with structure prediction tools like AlphaFold and Boltz-2, that’s becoming a regular judgement call, and getting it wrong can mean chasing a lead that never had a chance.
Essam Metwally, Scientific Director at Merck Research Laboratories, has spent more than 20 years on both sides of that question, first solving structures experimentally, now leading modelling, AI/ML and data science teams. That combination gives him an expert, grounded view of when these tools earn a team’s trust and when they don’t.
In this fireside chat, Essam joins Nathan Brown for a candid conversation about the state of the latest AI methods in drug discovery. When does a prediction earn the right to change what a team does next, rather than simply looking convincing? Why do promising models so often disappoint once they meet real data and real objectives? And as automation advances, what should scientists never hand over?
Join us to learn where leaders should focus their effort to capture real value rather than chase the hype.
Plus, you’ll be able to pose your own questions and challenges directly to Essam.
Can’t attend? Register anyway to receive the recording.
Meet the speakers
Nathan Brown, PhD
Director of Science, Optibrium
Nathan Brown leads Optibrium’s Research and Application Science teams, developing new methods while ensuring customer feedback directly shapes R&D priorities. He was previously Director of Digital Chemistry at Healx, where he led the development of AI-powered computational methods for rare disease drug discovery, and before that led the Cheminformatics team at BenevolentAI and founded the In Silico Medicinal Chemistry team at The Institute of Cancer Research, delivering significant impact on drugs in active clinical trials. A globally recognised thought leader in cheminformatics and computational chemistry, Nathan is a Fellow of the Royal Society of Chemistry and sits on the Editorial Advisory Boards of the Journal of Chemical Information and Modeling and ChemMedChem. He invented the first multi-objective de novo molecular design system, published in 2004, and has authored over 50 peer-reviewed papers and four books. He won the 2017 Corwin Hansch Award for his outstanding contributions to the field.
Essam Metwally, PhD
Scientific Director, Modeling/Informatics, AI ML and Data Science, Merck Research Laboratories
Essam has been at Merck Research Laboratories since 2018. He brings over twenty years of experience across modelling and informatics in drug discovery, including ten years at Certara/Tripos and six years at Chemical Computing Group. Having worked both in the lab and in silico, he combines hands-on experimental grounding with computational expertise.
Essam holds a PhD in Medical Science, specialising in gastrointestinal medicine, and a BSc (Hons) in Biochemistry from the University of Calgary, and his educational background also includes Scripps Research.
