Lead Generation and Candidate Realization (LGCR) - Analytical Sciences (AnSci) - SANOFI-AVENTIS R&D, France.
Int J Pharm. 2012 Nov 1;437(1-2):137-55. doi: 10.1016/j.ijpharm.2012.07.066. Epub 2012 Aug 4.
In the context of the Quantitative Structure-Activity Relationship (QSAR) for new drugs, knowledge and understanding of the behavior of the molecules in solution and simulated media are key points to provide the best formulated compounds. Current analytical determinations can give solubility data and dedicated techniques can provide other physico-chemical constants, such as pKa(s), logP and logD. All of these data represent the capability of the compound to enter into solutions, but correlations between solubility measurements and these constants are not frequently established, to confirm that the compound observed in solution is the expected one. The study presented here, shows how a dedicated software was elaborated and used in a large study of 41 compounds, to retrieve the dissociation constants, starting with the solubility and pH couples of data acquired.
在新药的定量构效关系（QSAR）的背景下，了解和掌握分子在溶液和模拟介质中的行为是提供最佳配方化合物的关键点。目前的分析测定可以提供溶解度数据，专用技术可以提供其他物理化学常数，如 pKa（s）、logP 和 logD。所有这些数据都代表了化合物进入溶液的能力，但溶解度测量值与这些常数之间的相关性并不经常建立，以确认在溶液中观察到的化合物就是预期的化合物。本文展示了如何精心设计和使用专用软件，从获得的溶解度和 pH 对数据开始，对 41 种化合物进行大量研究，以检索离解常数。
