Rodgers Trudy, Rowland Malcolm
Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, The University of Manchester, England.
J Pharm Sci. 2006 Jun;95(6):1238-57. doi: 10.1002/jps.20502.
A key component of whole body physiologically based pharmacokinetic (WBPBPK) models is the tissue-to-plasma water partition coefficients (Kpu's). The predictability of Kpu values using mechanistically derived equations has been investigated for 7 very weak bases, 20 acids, 4 neutral drugs and 8 zwitterions in rat adipose, bone, brain, gut, heart, kidney, liver, lung, muscle, pancreas, skin, spleen and thymus. These equations incorporate expressions for dissolution in tissue water and, partitioning into neutral lipids and neutral phospholipids. Additionally, associations with acidic phospholipids were incorporated for zwitterions with a highly basic functionality, or extracellular proteins for the other compound classes. The affinity for these cellular constituents was determined from blood cell data or plasma protein binding, respectively. These equations assume drugs are passively distributed and that processes are nonsaturating. Resultant Kpu predictions were more accurate when compared to published equations, with 84% as opposed to 61% of the predicted values agreeing with experimental values to within a factor of 3. This improvement was largely due to the incorporation of distribution processes related to drug ionisation, an issue that is not addressed in earlier equations. Such advancements in parameter prediction will assist WBPBPK modelling, where time, cost and labour requirements greatly deter its application.
基于生理学的全身药代动力学(WBPBPK)模型的一个关键组成部分是组织与血浆的水分配系数(Kpu值)。已针对大鼠脂肪、骨骼、大脑、肠道、心脏、肾脏、肝脏、肺、肌肉、胰腺、皮肤、脾脏和胸腺中的7种极弱碱、20种酸、4种中性药物和8种两性离子,研究了使用机理推导方程预测Kpu值的能力。这些方程纳入了在组织水中溶解以及分配到中性脂质和中性磷脂中的表达式。此外,对于具有高碱性官能团的两性离子,纳入了与酸性磷脂的结合,对于其他化合物类别,则纳入了与细胞外蛋白质的结合。对这些细胞成分的亲和力分别根据血细胞数据或血浆蛋白结合来确定。这些方程假设药物是被动分布的,且过程是非饱和的。与已发表的方程相比,所得的Kpu预测更为准确,84%的预测值与实验值相符,误差在3倍以内,而之前的方程只有61%。这种改进主要是由于纳入了与药物电离相关的分布过程,这是早期方程未涉及的问题。参数预测方面的此类进展将有助于WBPBPK建模,因为时间、成本和劳动力需求极大地阻碍了其应用。