Singh Aman P, Krzyzanski Wojciech, Martin Steven W, Weber Gregory, Betts Alison, Ahmad Alaa, Abraham Anson, Zutshi Anup, Lin John, Singh Pratap
Department of Pharmaceutical Sciences, University at Buffalo, Kapoor Hall, Buffalo, New York, USA.
AAPS J. 2015 Mar;17(2):389-99. doi: 10.1208/s12248-014-9690-8. Epub 2014 Dec 3.
Prediction of human pharmacokinetics (PK) can be challenging for monoclonal antibodies (mAbs) exhibiting target-mediated drug disposition (TMDD). In this study, we performed a quantitative analysis of a diverse set of six mAbs exhibiting TMDD to explore translational rules that can be utilized to predict human PK. A TMDD model with rapid-binding approximation was utilized to fit PK and PD (i.e., free and/or total target levels) data, and average absolute fold error (AAFE) was calculated for each model parameter. Based on the comparative analysis, translational rules were developed and applied to a test antibody not included in the original analysis. AAFE of less than two-fold was observed between monkey and human for baseline target levels (R 0), body-weight (BW) normalized central elimination rate (K el/BW(-0.25)) and central volume (V c/BW(1.0)). AAFE of less than three-fold was estimated for the binding affinity constant (K D). The other four parameters, i.e., complex turnover rate (K int), target turnover rate (K deg), central to peripheral distribution rate constant (K pt) and peripheral to central rate constant (K tp) were poorly correlated between monkey and human. The projected human PK of test antibody based on the translation rules was in good agreement with the observed nonlinear PK. In conclusion, we recommend a TMDD model-based prediction approach that integrates in vitro human biomeasures and in vivo preclinical data using translation rules developed in this study.
对于表现出靶点介导的药物处置（TMDD）的单克隆抗体（mAb），预测其人体药代动力学（PK）具有挑战性。在本研究中，我们对一组多样的六种表现出TMDD的单克隆抗体进行了定量分析，以探索可用于预测人体PK的转化规则。利用具有快速结合近似的TMDD模型拟合PK和PD（即游离和/或总靶点水平）数据，并计算每个模型参数的平均绝对倍数误差（AAFE）。基于比较分析，制定了转化规则并应用于原始分析中未包含的测试抗体。对于基线靶点水平（R0）、体重（BW）归一化的中央消除率（Kel/BW(-0.25)）和中央体积（Vc/BW(1.0)），在猴子和人类之间观察到AAFE小于两倍。对于结合亲和常数（KD），估计AAFE小于三倍。其他四个参数，即复合物周转率（Kint）、靶点周转率（Kdeg）、中央到外周分布速率常数（Kpt）和外周到中央速率常数（Ktp），在猴子和人类之间相关性较差。基于转化规则预测的测试抗体的人体PK与观察到的非线性PK良好吻合。总之，我们推荐一种基于TMDD模型的预测方法，该方法使用本研究中制定的转化规则整合体外人体生物测量和体内临床前数据。
