Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York, 452 Kapoor Hall, Buffalo, NY 14260, USA.
J Pharmacokinet Pharmacodyn. 2012 Dec;39(6):683-710. doi: 10.1007/s10928-012-9279-8. Epub 2012 Nov 27.
This investigation evaluated the utility of a physiologically based pharmacokinetic (PBPK) model, which incorporates model parameters representing key determinants of monoclonal antibody (mAb) target-mediated disposition, to predict, a priori, mAb disposition in plasma and in tissues, including tumors that express target antigens. Monte Carlo simulation techniques were employed to predict the disposition of two mAbs, 8C2 (as a non-binding control mouse IgG1 mAb) and T84.66 (a high-affinity murine IgG1 anti-carcinoembryonic antigen mAb), in mice bearing no tumors, or bearing colorectal HT29 or LS174T xenografts. Model parameters were obtained or derived from the literature. (125)I-T84.66 and (125)I-8C2 were administered to groups of SCID mice, and plasma and tissue concentrations were determined via gamma counting. The PBPK model well-predicted the experimental data. Comparisons of the population predicted versus observed areas under the plasma concentration versus time curve (AUC) for T84.66 were 95.4 ± 67.8 versus 84.0 ± 3.0, 1,859 ± 682 versus 2,370 ± 154, and 5,930 ± 1,375 versus 5,960 ± 317 (nM × day) at 1, 10, and 25 mg/kg in LS174T xenograft-bearing SCID mice; and 215 ± 72 versus 233 ± 30, 3,070 ± 346 versus 3,120 ± 180, and 7,884 ± 714 versus 7,440 ± 626 in HT29 xenograft-bearing mice. Model predicted versus observed 8C2 plasma AUCs were 312.4 ± 30 versus 182 ± 7.6 and 7,619 ± 738 versus 7,840 ± 24.3 (nM × day) at 1 and 25 mg/kg. High correlations were observed between the predicted median plasma concentrations and observed median plasma concentrations (r (2) = 0.927, for all combinations of treatment, dose, and tumor model), highlighting the utility of the PBPK model for the a priori prediction of in vivo data.
本研究评估了生理药代动力学(PBPK)模型的实用性,该模型纳入了代表单克隆抗体(mAb)靶介导处置关键决定因素的模型参数,以预先预测 mAb 在血浆和组织中的分布,包括表达靶抗原的肿瘤。采用蒙特卡罗模拟技术预测了两种 mAb(8C2 作为非结合对照鼠 IgG1 mAb)和 T84.66(高亲和力鼠 IgG1 抗癌胚抗原 mAb)在无肿瘤或结直肠 HT29 或 LS174T 异种移植小鼠中的分布。模型参数从文献中获得或推导得出。将 (125)I-T84.66 和 (125)I-8C2 给予 SCID 小鼠组,并通过伽马计数测定血浆和组织浓度。PBPK 模型很好地预测了实验数据。T84.66 的群体预测与观察的血浆浓度-时间曲线下面积(AUC)的比较结果为:LS174T 异种移植荷瘤 SCID 小鼠 1、10 和 25mg/kg 时分别为 95.4±67.8 对 84.0±3.0、1859±682 对 2370±154 和 5930±1375 对 5960±317(nM×天);而在 HT29 异种移植荷瘤小鼠中分别为 215±72 对 233±30、3070±346 对 3120±180 和 7884±714 对 7440±626。模型预测与观察到的 8C2 血浆 AUC 分别为:1 和 25mg/kg 时分别为 312.4±30 对 182±7.6 和 7619±738 对 7840±24.3(nM×天)。观察到预测的中位血浆浓度与观察到的中位血浆浓度之间存在高度相关性(所有治疗、剂量和肿瘤模型组合的 r(2)=0.927),这突出了 PBPK 模型用于预先预测体内数据的实用性。