UGM & Conference in North America

Central Nervous System Multi-Parameter Optimization (CNS MPO) Desirability: A Holistic Assessment of Drug Property and its Application in Discovery Projects

Xinjun Hou
Head of Neuroscience Computational Chemistry, Pfizer
(FRIDAY, June 23 - Scientific Presentations, 09:00-09:30)

Xinjun Hou, Travis T. Wager, Patrick R. Verhoest and Anabella Villalobos

Using six basic physicochemical properties commonly used in drug design, we developed CNS MPO Desirability score to holistically assess of druglikeness and identify compounds with optimal ADME attributes in one molecule (favorable permeability, minimizing P-glycoprotein efflux, increasing metabolic stability). Using retrospective data analyses and prospective application in real projects in last few years, we will show that he CNS MPO Desirability creates flexibility in design and expands design space, offering advantages over the use of single parameters or hard cutoffs for single or multiple parameters. The use of this tool has played a role in reducing the number of compounds submitted to exploratory toxicity studies and increasing the survival of our drug candidates through regulatory toxicology into First in Human (FIH) studies. Overall, the CNS MPO algorithm has helped to improve the prioritization of design ideas and the quality of the compounds nominated for clinical development.