Garcia-Cremades Maria, Pitou Celine, Iversen Philip W, Troconiz Iñaki F
Pharmacometrics and Systems Pharmacology, Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, and Navarra Institute for Health Research (IdiSNA), University of Navarra, Pamplona, Spain (M.G.-C., I.F.T.); Global Pharmacokinetic/Pharmacodynamics and Pharmacometrics, Eli Lilly and Company, Windlesham, Surrey, United Kingdom (C.P.); and Lilly Research laboratories, Eli Lilly and Company, Indianapolis, Indiana (P.W.I.).
Pharmacometrics and Systems Pharmacology, Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, and Navarra Institute for Health Research (IdiSNA), University of Navarra, Pamplona, Spain (M.G.-C., I.F.T.); Global Pharmacokinetic/Pharmacodynamics and Pharmacometrics, Eli Lilly and Company, Windlesham, Surrey, United Kingdom (C.P.); and Lilly Research laboratories, Eli Lilly and Company, Indianapolis, Indiana (P.W.I.)
J Pharmacol Exp Ther. 2017 Mar;360(3):445-456. doi: 10.1124/jpet.116.237610. Epub 2016 Dec 27.
In this work, a semimechanistic tumor growth-response model for gemcitabine in pancreatic (administered as single agent) and ovarian (given as single agent and in combination with carboplatin) cancer in mice was developed. Tumor profiles were obtained from nude mice, previously inoculated with KP4, ASPC1, MIA PACA2, PANC1 (pancreas), A2780, or SKOV3×luc (ovarian) cell lines, and then treated with different dosing schedules of gemcitabine and/or carboplatin. Data were fitted using the population approach with Nonlinear Mixed Effect Models 7.2. In addition to cell proliferation, the tumor progression model for both types of cancer incorporates a carrying capacity representing metabolite pool for DNA synthesis required to tumor growth. Analysis of data from the treated groups revealed that gemcitabine exerted its tumor effects by promoting apoptosis as well as decreasing the carrying capacity compartment. Pharmacodynamic parameters were cell-specific and overall had similar range values between cancer types. In pancreas, a linear model was used to describe both gemcitabine effects with parameter values between 3.26 × 10 and 4.2 × 10 L/(mg × d). In ovarian cancer, the apoptotic effect was driven by an E model with an efficacy/potency ratio of 5.25-8.65 L/(mg × d). The contribution of carboplatin to tumor effects was lower than the response exerted by gemcitabine and was incorporated in the model as an inhibition of the carrying capacity. The model developed was consistent in its structure across different tumor cell lines and two tumor types where gemcitabine is approved. Simulation-based evaluation diagnostics showed that the model performed well in all experimental design scenarios, including dose, schedule, and tumor type.
在这项研究中,建立了一种半机制性的吉西他滨在小鼠胰腺癌(单药给药)和卵巢癌(单药给药及与卡铂联合给药)中的肿瘤生长反应模型。肿瘤模型取自先前接种了KP4、ASPC1、MIA PACA2、PANC1(胰腺)、A2780或SKOV3×luc(卵巢)细胞系的裸鼠,然后用不同给药方案的吉西他滨和/或卡铂进行治疗。使用非线性混合效应模型7.2的群体方法对数据进行拟合。除了细胞增殖外,两种癌症的肿瘤进展模型都纳入了一个代表肿瘤生长所需DNA合成代谢物池的承载能力。对治疗组数据的分析表明,吉西他滨通过促进细胞凋亡以及降低承载能力区室来发挥其肿瘤效应。药效学参数具有细胞特异性,总体而言,不同癌症类型之间的范围值相似。在胰腺癌中,使用线性模型描述吉西他滨的两种效应,参数值在3.26×10至4.2×10 L/(mg×d)之间。在卵巢癌中,细胞凋亡效应由E模型驱动效价/效能比为5.25 - 8.65 L/(mg×d)。卡铂对肿瘤效应的贡献低于吉西他滨所发挥的反应,并在模型中作为对承载能力的抑制纳入。所建立的模型在不同肿瘤细胞系和两种已批准使用吉西他滨的肿瘤类型中结构一致。基于模拟的评估诊断表明,该模型在所有实验设计场景中,包括剂量、给药方案和肿瘤类型,都表现良好。