Validation of Early Human Dose Prediction: A Key Metric for Compound Progression in Drug Discovery

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• 作者：Ken M. Page
• 刊名：Molecular Pharmaceutics
• 出版年：2016
• 出版时间：February 1, 2016
• 年：2016
• 卷：13
• 期：2
• 页码：609-620
• 全文大小：584K
• ISSN：1543-8392

文摘

Human dose prediction is increasingly recognized as an important parameter in Drug Discovery. Validation of a method using only in vitro and predicted parameters incorporated into a PK model was undertaken by predicting human dose and free C_max for a number of marketed drugs and AZ Development compounds. Doses were compared to those most relevant to marketed drugs or to clinically administered doses of AZ compounds normalized either to predicted C_min or C_max values. Average (AFE) and absolute average (AAFE) fold-error analysis showed that best predictions were obtained using a QSAR model as the source of Vss, with F_abs set to 1 for acids and 0.5 for all other ion classes; for clearance prediction no binding correction to the well stirred model (WSM) was used for bases, while it was set to Fu_p/Fu_p^0.5 for all other ion classes. Using this combination of methods, predicted doses for 45 to 68% of the C_min- and C_max-normalized and marketed drug data sets were within 3-fold of the observed values, while 82 to 92% of these data sets were within 10-fold. This method for early human dose prediction is able to rank, identify, and flag risks or optimization opportunities for future development compounds within 10 days of first synthesis.