Fu Yu, Taghvafard Hadi, Said Medhat M, Rossman Eric I, Collins Teresa A, Billiald-Desquand Stéphanie, Leishman Derek, van der Graaf Piet H, van Hasselt J G Coen, Snelder Nelleke
Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
GlaxoSmithKline, Collegeville, Pennsylvania, USA.
CPT Pharmacometrics Syst Pharmacol. 2022 May;11(5):640-652. doi: 10.1002/psp4.12774. Epub 2022 Mar 18.
The use of systems-based pharmacological modeling approaches to characterize mode-of-action and concentration-effect relationships for drugs on specific hemodynamic variables has been demonstrated. Here, we (i) expand a previously developed hemodynamic system model through integration of cardiac output (CO) with contractility (CTR) using pressure-volume loop theory, and (ii) evaluate the contribution of CO data for identification of system-specific parameters, using atenolol as proof-of-concept drug. Previously collected experimental data was used to develop the systems model, and included measurements for heart rate (HR), CO, mean arterial pressure (MAP), and CTR after administration of atenolol (0.3-30 mg/kg) from three in vivo telemetry studies in conscious Beagle dogs. The developed cardiovascular (CVS)-contractility systems model adequately described the effect of atenolol on HR, CO, dP/dtmax, and MAP dynamics and allowed identification of both system- and drug-specific parameters with good precision. Model parameters were structurally identifiable, and the true mode of action can be identified properly. Omission of CO data did not lead to a significant change in parameter estimates compared to a model that included CO data. The newly developed CVS-contractility systems model characterizes short-term drug effects on CTR, CO, and other hemodynamic variables in an integrated and quantitative manner. When the baseline value of total peripheral resistance is predefined, CO data was not required to identify drug- and system-specific parameters. Confirmation of the consistency of system-specific parameters via inclusion of data for additional drugs and species is warranted. Ultimately, the developed model has the potential to be of relevance to support translational CVS safety studies.
基于系统的药理学建模方法已被证明可用于表征药物对特定血流动力学变量的作用模式和浓度-效应关系。在此,我们(i)利用压力-容积环理论,通过将心输出量(CO)与收缩性(CTR)整合,扩展先前开发的血流动力学系统模型;(ii)以阿替洛尔作为概念验证药物,评估CO数据对识别系统特定参数的贡献。先前收集的实验数据用于开发系统模型,这些数据包括在清醒的比格犬体内进行的三项遥测研究中,给予阿替洛尔(0.3 - 30mg/kg)后心率(HR)、CO、平均动脉压(MAP)和CTR的测量值。所开发的心血管(CVS)-收缩性系统模型充分描述了阿替洛尔对HR、CO、dP/dtmax和MAP动态的影响,并能够高精度地识别系统和药物特定参数。模型参数在结构上是可识别的,并且可以正确识别真实的作用模式。与包含CO数据的模型相比,省略CO数据并未导致参数估计值发生显著变化。新开发的CVS-收缩性系统模型以综合和定量的方式表征了药物对CTR、CO和其他血流动力学变量的短期影响。当预先定义总外周阻力的基线值时,识别药物和系统特定参数不需要CO数据。有必要通过纳入其他药物和物种的数据来确认系统特定参数的一致性。最终,所开发的模型有可能支持转化性CVS安全性研究。