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Presentation of a Structurally Diverse and Commercially Available Drug Data Set for Correlation and Benchmarking Studies

Supporting Info

Christian Sköld,^† Susanne Winiwarter,^‡ Johan Wernevik,^§ Fredrik Bergström,^§ Leif Engström,^‡ Ruth Allen, Karl Box, John Comer, Jon Mole, Anders Hallberg,^† Hans Lennernäs, Torbjörn Lundstedt,^† Anna-Lena Ungell,^‡ and Anders Karlén*^†

Division of Organic Pharmaceutical Chemistry, Department of Medicinal Chemistry, and Department of Pharmacy, BMC, Uppsala University, Sweden, Drug Metabolism and Pharmacokinetics & Bioanalytical Chemistry and Lead Generation; DMPK & Physical Chemistry, AstraZeneca R&D Mlndal, Sweden, and Sirius Analytical Instruments Ltd., Riverside, East Sussex, United Kingdom

J. Med. Chem., 2006, 49 (23), pp 6660–6671

DOI: 10.1021/jm0506219

Publication Date (Web): October 14, 2006

†

Division of Organic Pharmaceutical Chemistry, Department of Medicinal Chemistry, Uppsala University.

, ‡

Drug Metabolism and Pharmacokinetics & Bioanalytical Chemistry, AstraZeneca R&D.

, §

Lead Generation, DMPK & Physical Chemistry, AstraZeneca R&D.

Sirius Analytical Instruments Ltd.

Department of Pharmacy, Uppsala University.

, *

To whom correspondence should be addressed: phone +46-18-471-4293; fax +46-18-471-4474; e-mail anders.karlen@orgfarm.uu.se.

Abstract

A multivariate analysis of drugs on the Swedish market was the basis for the selection of a small, physicochemically diverse set of 24 drug compounds. Factors such as structural diversity, commercial availability, price, and a suitable analytical technique for quantification were considered in the selection. Lipophilicity, pK_a, solubility, and permeability across human Caco-2 cell monolayers were measured for the compiled data set. The results show that, by use of a physicochemically diverse data set, experimental responses over a wide range were obtained. The paper also shows how experimental difficulties due to the diversity of the data set can be overcome. We anticipate that this data set can serve as a benchmark set for validation of new experimental techniques or in silico models. It can also be used as a diverse starting data set for the development of new computational models.

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