Novel high/low solubility classification methods for new molecular entities

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• 作者：Rutwij A. Dave ; Marilyn E. Morris ; ^{memorris@buffalo.edu" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Solubility ; High throughput technologies ; Analytical chemistry ; Computational ADME ; In silico modeling ; Computer aided drug design ; ROC curve analysis
• 刊名：International Journal of Pharmaceutics
• 出版年：2016
• 出版时间：10 September 2016
• 年：2016
• 卷：511
• 期：1
• 页码：111-126
• 全文大小：674 K

文摘

This research describes a rapid solubility classification approach that could be used in the discovery and development of new molecular entities. Compounds (N = 635) were divided into two groups based on information available in the literature: high solubility (BDDCS/BCS 1/3) and low solubility (BDDCS/BCS 2/4). We established decision rules for determining solubility classes using measured log solubility in molar units (MLogS_M) or measured solubility (MSol) in mg/ml units. ROC curve analysis was applied to determine statistically significant threshold values of MSol and MLogS_M. Results indicated that NMEs with MLogS_M > ⿿3.05 or MSol > 0.30 mg/mL will have ⿥85% probability of being highly soluble and new molecular entities with MLogS_M ⿤ ⿿3.05 or MSol ⿤ 0.30 mg/mL will have ⿥85% probability of being poorly soluble. When comparing solubility classification using the threshold values of MLogS_M or MSol with BDDCS, we were able to correctly classify 85% of compounds. We also evaluated solubility classification of an independent set of 108 orally administered drugs using MSol (0.3 mg/mL) and our method correctly classified 81% and 95% of compounds into high and low solubility classes, respectively. The high/low solubility classification using MLogS_M or MSol is novel and independent of traditionally used dose number criteria.