Cambridge Healthtech Institute’s Inaugural
Physicochemical Property Analysis
Improving the Drug Discovery Process by Optimizing Physical Properties
April 18-19
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The optimization of physical properties of a compound is fundamental to the drug discovery process, mainly due to their influence on absorption and distribution in vivo. This provides insight into the in vivo transport processes and knowing the properties will help with choosing the optimal compounds for the task. It saves costs and time when compounds are being properly analyzed in the design stage before they are moving into development, as it is important to consider questions such as how hydrophobicity will affect the solubility of a drug down the line or how the charge of the compound interacts with the absorption by a transport mechanism. Also, the use of predictive models is important, but again, without consideration of the actual physical chemical property of the new compound, the analyses will be based on a different set of data. This meeting will discuss what it takes to create selective and efficacious compounds and to understand the biological data by analyzing the physicochemical properties early on.
WEDNESDAY, APRIL 18
12:30 pm Registration
1:30 Chairperson’s Opening Remarks
1:40 Getting Physical in Drug Discovery; Where Next for Property Profiling and Predictive Methods?
Robert J. Young, Ph.D., GlaxoSmithKline
A growing body of evidence indicates that much of the attrition in drug discovery can be attributed to the sub-optimal physical properties of experimental molecules, especially in pre-clinical activities. Molecules that are overly lipophilic and/or highly aromatic have been shown to posses greatly increased risk in studies to assess developability and promiscuity profiles; with impact over and above the inherent correlation between logP and #Ar rings. This led to the so-called property forecast indices, (PFI = log P or log DpH7.4 + #Ar), simplistic yet powerful predictors of risk; these are enhanced by the utilisation of improved lipophilicity measures and estimates based on chromatographic methods. Data illustrating these principles will be discussed, posing questions for future predictive methods. Successful molecules can be further discriminated when PFI is taken together with ligand efficiency measures, pointing to a useful indicator of likely success in drug discovery.
2:55 Getting Physical in Drug Discovery: A Suite of Physicochemical Methods to Enable Successful Drug Discovery
Alan P. Hill, Ph.D., Team Leder, PhysChem, Department of Analytical Chemistry, GlaxoSmithKline, Stevenage UK
Physicochemical measurements are key enablers for successful medicinal chemistry. However to maximise the likelihood of a success, it is essential that assays offered provide data that is appropriate to the stage of the project and additionally have sufficient capacity to meet demands. The presentation will provide an overview of a cohesive approach to physicochemical measurement (as applied within GSK) that effectively guides medicinal chemistry projects to produce robust candidate molecules with optimal physicochemical properties.
3:10 Sponsored Presentations (Opportunity Available)
3:40 Networking Refreshment Break in Exhibit Hall with Poster Viewing
4:20 Practical Concepts in Fragment-Based Drug Ddiscovery
Marcel Verdonk, Ph.D., Director, Computational Chemistry and Informatics, Astex Therapeutics, Inc.
4:50 The Intricacies of Interpreting Pharmaceutical Data
Terry Stouch, Ph.D., President, R&D, Science for Solutions, LLC
Pharmaceutical research data that is extremely valuable within context could be worthless outside of that context or when lumped with other data. We will discuss these issues supported by many practical examples from several pharmaceutical companies, commercial and open source databases, and the literature. Diverse types of pharmaceutical data will be discussed including physicochemical properties such as solubility, logP, logD, Caco-2, and pKa. The vital meta data, its importance in the proper use of the data, the mistakes and problems that arise from ignoring it, and the reasons it is often ignored, will be outlined. Recommendations that will ameliorate these problems and enhance data use and value will be offered for better data capture and data basing and for holistic data presentation that will aid interpretation.
5:20 Interactive Breakout Discussions
6:30 End of Day
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