Physiologically based pharmacokinetic modeling 1: Predicting the tissue distribution of moderate-to-strong bases
Physiologically based pharmacokinetic modeling 1: Predicting the tissue distribution of moderate-to-strong bases
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DOI：
10.1002/jps.20322
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发表时间：
2005-06-01
影响因子：
3.8
通讯作者：
Rowland, M
中科院分区：
文献类型：
--
作者：
Rodgers, T;Leahy, D;Rowland, M
组织与血浆的水分配系数 (Kpu) 是全身生理药代动力学 (WBPBPK) 模型的组成部分。本研究旨在通过开发一个机械方程来提高中强碱 (pK(a)>= 7) 的 Kpu 值的可预测性，该方程适应此类药物与组织酸性磷脂的独特静电相互作用，其中这种相互作用的亲和力很容易从药物血细胞结合数据中估计出来。其他模型成分包括药物分配为中性脂质和中性磷脂，以及药物在组织水中的溶解。该方程的主要假设是静电相互作用占主导地位，药物被动分布，并且非饱和条件占主导地位。 28 个中强碱基的 Kpu 预测结果明显比已发表的方程更准确，89% 的预测结果在大鼠脂肪、骨骼、肠道、心脏、肾脏、肝脏、肌肉、胰腺、皮肤、脾脏和胸腺实验值的三倍之内，而预测结果为 45%。大鼠大脑和肺部的预测不太准确，可能是由于涉及未纳入方程的其他过程。预测方面的整体改进应有助于 WBPBPK 模型的进一步应用，其中与实验确定 Kpu 相关的时间、成本和劳动力要求在很大程度上阻碍了其应用。 (C) 2005 Wiley-Liss, Inc. 和美国药剂师协会。
Tissue-to-plasma water partition coefficients (Kpu's) form an integral part of whole body physiologically based pharmacokinetic (WBPBPK) models. This research aims to improve the predictability of Kpu values for moderate-to-strong bases (pK(a)>= 7), by developing a mechanistic equation that accommodates the unique electrostatic interactions of such drugs with tissue acidic phospholipids, where the affinity of this interaction is readily estimated from drug blood cell binding data. Additional model constituents are drug partitioning into neutral lipids and neutral phospholipids, and drug dissolution in tissue water. Major assumptions of this equation are that electrostatic interactions predominate, drugs distribute passively, and non-saturating conditions prevail. Resultant Kpu predictions for 28 moderate-to-strong bases were significantly more accurate than published equations with 89%, compared to 45%, of the predictions being within a factor of three of experimental values in rat adipose, bone, gut, heart, kidney, liver, muscle, pancreas, skin, spleen and thymus. Predictions in rat brain and lung were less accurate probably due to the involvement of additional processes not incorporated within the equation. This overall improvement in prediction should facilitate the further application of WBPBPK modeling, where time, cost and labor requirements associated with experimentally determining Kpu's have, to a large extent, deterred its application. (C) 2005 Wiley-Liss, Inc. and the American Pharmacists Association.