Daublain Pierre, Feng Kung-I, Altman Michael D, Martin Iain, Mukherjee Suman, Nofsinger Rebecca, Northrup Alan B, Tschirret-Guth Richard, Cartwright Mark, McGregor Caroline
Discovery Pharmaceutical Sciences, MRL, Merck & Co., Inc. , Boston, Massachusetts 02115, United States.
Discovery Pharmaceutical Sciences, MRL, Merck & Co., Inc. , Rahway, New Jersey 07065, United States.
Mol Pharm. 2017 May 1;14(5):1634-1645. doi: 10.1021/acs.molpharmaceut.6b01118. Epub 2017 Apr 3.
The purpose of this research was to assess variability in pharmacokinetic profiles (PK variability) in preclinical species and identify the risk factors associated with the properties of a drug molecule that contribute to the variability. Exposure data in mouse, rat, dog, and monkey for a total of 16,592 research compounds studied between 1999 and 2013 were included in the analysis. Both in vivo study parameters and in silico/experimental physicochemical properties of the molecules were analyzed. Areas under the plasma concentration vs time curves (AUC) were used to assess PK variability. PK variability was calculated as the ratio of the highest AUC within a defined set of AUC values (AUC) over the lowest AUC within that set (AUC). Both intra- and inter-animal variability were analyzed, with intra-animal exposures found to be more variable than inter-animal exposures. While several routes of administration were initially studied, the analysis was focused on the oral route, which corresponds to the large majority of data points and displays higher variability than the subcutaneous, intraperitoneal, or intravenous routes. The association between inter-animal PK variability and physical properties was studied, and low solubility, high administered dose, high preclinical dose number (PDo), and pH-dependent solubility were found to be associated with high variability in exposures. Permeability-as assessed by the measured permeability coefficient in the LLC-PK1 cell line-was also considered but appeared to only have a weak association with variability. Consistent with these findings, BCS class I and III compounds were found to be less prone to PK variability than BCS class II and IV compounds. A modest association of PK variability with clearance was observed while the association with bioavailability, a higher PK variability for compounds with lower bioavailability, appeared to be more pronounced. Finally, two case studies that highlight PK variability issues are described, and successful mitigation strategies are presented.
本研究的目的是评估临床前物种药代动力学特征的变异性（PK变异性），并确定与导致变异性的药物分子特性相关的风险因素。分析纳入了1999年至2013年间研究的总共16592种研究化合物在小鼠、大鼠、狗和猴子中的暴露数据。对分子的体内研究参数和计算机模拟/实验物理化学性质均进行了分析。血浆浓度-时间曲线下面积（AUC）用于评估PK变异性。PK变异性计算为一组定义的AUC值中的最高AUC（AUC）与该组中的最低AUC（AUC）之比。分析了动物内和动物间的变异性，发现动物内暴露比动物间暴露更具变异性。虽然最初研究了几种给药途径，但分析集中在口服途径，该途径对应于绝大多数数据点，并且比皮下、腹腔内或静脉内途径显示出更高的变异性。研究了动物间PK变异性与物理性质之间的关联，发现低溶解度、高给药剂量、高临床前给药次数（PDo）和pH依赖性溶解度与暴露的高变异性相关。还考虑了通过LLC-PK1细胞系中测得的渗透系数评估的渗透性，但它似乎与变异性仅具有弱关联。与这些发现一致，发现BCS I类和III类化合物比BCS II类和IV类化合物更不易出现PK变异性。观察到PK变异性与清除率之间存在适度关联，而与生物利用度的关联，即生物利用度较低的化合物具有更高的PK变异性，似乎更为明显。最后，描述了两个突出PK变异性问题的案例研究，并提出了成功的缓解策略。
