Date: 9 September 2026
Time: 4pm BST | 11am ET | 8am PT | 5pm CEST
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?
Join us 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.
Can’t attend? Register anyway to receive the recording.
Meet the speakers
Matt Segall, PhD
CEO, Optibrium™
Matt has a Master of Science in Computation from the University of Oxford and a PhD in Theoretical Physics from the University of Cambridge.
As Associate Director at Camitro (UK), ArQule Inc. and then Inpharmatica, he led a team developing predictive ADME models and state-of-the-art intuitive decision-support and visualisation tools for drug discovery.
In January 2006, he became responsible for management of Inpharmatica’s ADME business, including experimental ADME services and the StarDrop™ software platform.
Following the acquisition of Inpharmatica, Matt became Senior Director responsible for BioFocus DPI’s ADMET division and, in 2009, led a management buyout of the StarDrop™ business to found Optibrium™.
Prashant Desai, PhD
Senior Fellow, DMPK, Genentech
Prashant Desai is a Senior Fellow at Genentech, where he leads the in silico Predictive ADME group within DMPK and helps advance the integration of AI/ML approaches into small-molecule drug discovery.
Over a career spanning more than 20 years, he has worked at the interface of in silico, in vitro, and in vivo ADME, previously leading Computational ADME, Mechanistic PK, and Investigational Drug Disposition groups at Eli Lilly.
He has contributed to the discovery of several clinical candidates, coauthored more than 65 publications and book chapters, and has co-chaired the IQ Consortium’s In Silico ADME Working Group for over a decade.
Gavin Milne, PhD
Principal Scientist, Sygnature Discovery
Gavin Milne is a Principal Scientist at Sygnature Discovery. Joining Sygnature Discovery in 2013, after undergraduate and postgraduate studies at the University of St. Andrews.
As a medicinal chemist Gavin has worked on projects from lead optimisation, hit to lead and combinatorial libraries.
Gavin’s work has contributed to 12 patent filings and 1 compound progressing to the clinic.
