Physicochemical Property Analysis
（物理化学的性質分析学会）
物理的性質の最適化による創薬プロセスの改善
4月18-19日

生体内での吸収や分布にさまざまな影響を及ぼすことなどから、化合物の物理的な性質（物性）の最適化は、創薬プロセスの基本となっています。化合物の物性を調べることで、生体内での化合物の輸送プロセスに関する情報を得ることができ、物性を把握することで、所定の課題に対応する最適な化合物を選び出すことができるのです。また、開発段階に進む前の設計段階で化合物の分析を適正に行うことにより、経費と時間を節約することもできます。創薬プロセスでは、開発された医薬品の溶解度に対して化合物の疎水性が及ぼす影響や、化合物の投入量と輸送メカニズムによる吸収との相互作用といった問題を考慮することが重要になるからです。また、予測モデルを利用することも重要ですが、新たな化合物が持つ実際の物理化学的性質をきちんと考慮しないと、実態とは異なるデータに基づく分析になってしまう可能性があります。この学会では、精選された効果の高い化合物を開発し、その化合物の物理化学的性質を早期に分析して生物学的データを正しく理解するのに必要な要素をめぐって議論が展開されます。

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1日目 | 2日目

4月18日, 水曜日

12:30 pm Registration

1:30 Chairperson’s Opening Remarks

THE PATH AHEAD

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 Modulating Physicochemical Properties to Improve ADME Outcomes

Jan Wahlstrom, Ph.D., Principal Scientist, Amgen

Alterations of physicochemical properties such as molecular weight, log d, polar surface area or pKa may influence the absorption, distribution, metabolism or excretion (ADME) of a chemical series in a chemotype-dependent manner. Application of mechanistic approaches to solving ADME issues provides insight as to why a change in properties causes a desired outcome in some cases, while leading to poorer outcomes in others. This seminar will focus on case studies outlining common ADME issues faced during the drug discovery process and the approaches used to resolve them.

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.

INTERPRETING DATA

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

In this interactive session, several topics will be offered for discussions and delegates are invited to choose a breakout topic of interest and join the moderated discussion at hand. In this informal setting, participants are encouraged to share examples from their work, vet ideas with peers and be part of a group problem-solving endeavor. We emphasize that this discussion is an informal exchange amongst scientists and is not meant to be, in any way, a product discussion.

Topic 1: Challenges of Thermodynamic Analysis

Moderator: Ernesto Freire, Ph.D., Henry Walters Professor, Johns Hopkins University

Topic 2: Hydrophobicity in Drug Discovery: Measurement or Calculation: Which Moves Drug Discovery Forward?

Moderator: Alan P. Hill, Ph.D., Team Leder, PhysChem, Department of Analytical Chemistry, GlaxoSmithKline, Stevenage UK

• When is hydrophobicity important?
• Is calculation good enough?
• logP or LogD?

6:30 End of Day