La Gamba Fabiola, Jacobs Tom, Geys Helena, Ver Donck Luc, Faes Christel
Janssen Research & Development, Turnhoutseweg 30, Beerse, B-2340, Belgium.
I-BioStat, Hasselt University, Agoralaan building D, Diepenbeek, B-3590, Belgium.
Pharm Stat. 2018 Nov;17(6):674-684. doi: 10.1002/pst.1887. Epub 2018 Jul 19.
Coadministration of 2 or more compounds can alter both the pharmacokinetics and pharmacodynamics of individual compounds. While experiments on pharmacodynamic drug-drug interactions are usually performed in an in vitro setting, this experiment focuses on an in vivo setting. The change over time of a safety biomarker is modeled using an indirect response model, in which the virtual pharmacokinetic profile of one compound drives the effect of the other. Several experiments at different dose level combinations were performed sequentially. While a traditional frequentist analysis consists of estimating the model parameters based on all the data simultaneously, in this work, we consider a Bayesian inference framework allowing to incorporate the results from a historical dose-response experiment.
两种或更多化合物的共同给药可能会改变各个化合物的药代动力学和药效学。虽然药效学药物-药物相互作用的实验通常在体外环境中进行，但本实验聚焦于体内环境。使用间接响应模型对安全生物标志物随时间的变化进行建模，其中一种化合物的虚拟药代动力学概况驱动另一种化合物的效应。依次进行了不同剂量水平组合的多个实验。传统的频率论分析是基于所有数据同时估计模型参数，而在本研究中，我们考虑一个贝叶斯推理框架，该框架允许纳入历史剂量-反应实验的结果。
