How to get metabolism right in discovery:Clearance, new modalities & preclinical species translation

Most teams have P450-driven metabolism well in hand. The clearance problems that actually stall programmes tend to live somewhere else. For teams working across small molecules, peptides, and antibody-drug conjugates, that gap keeps widening. Pathways like amide hydrolysis, the difference between apparent and unbound intrinsic clearance, and species-specific liabilities can all look fine in a standard assay and still derail a programme down the line. The panel draws on the full range of tools discovery teams use to work through this, from in silico modelling and machine learning to in vitro assays and in vivo experiments, and on how metabolism gets weighed against other priorities like potency along the way. In this panel, Prashant Desai (Senior Fellow, Genentech) and Gavin Milne (Principal Scientist, Sygnature Discovery) join Optibrium™ CEO Matt Segall to talk through where metabolism science is genuinely being tested right now. Why do project teams still optimise the wrong clearance number? What changes when you move away from small molecules to peptides and antibody-drug conjugates (ADCs)? When does a predictive model earn enough trust to guide a project’s next step, and when do you still need to test it directly? And, in a deliberately provocative turn, which pre-clinical species’ metabolism should actually be guiding a project’s decisions? Watch the recording to hear what these two experienced DMPK leaders have seen first-hand, even after years of published research on these questions, and what actually separates a dependable clearance prediction from one that just looks convincing. Who should attend: metabolism scientists and project leads at organisations of any size or experience level, from teams building out their DMPK capabilities to established groups looking to sharpen their approach.