A novel cardiovascular systems model to quantify drugs effects on the inter‐relationship between contractility and other hemodynamic variables

Abstract

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 shortterm 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.

A tutorial for model‐based evaluation and translation of cardiovascular safety in preclinical trials

“…As an alternative, mechanistic models are being developed to capture the intricate relationships between CV parameters and mechanisms of action of a drug 6,7,43 . Extensive validation and application of a quantitative systems model may eventually improve our ability to reliably predict the CV safety between animals and humans.…”

“…As an alternative, mechanistic models are being developed to capture the intricate relationships between CV parameters and mechanisms of action of a drug. 6 , 7 , 43 Extensive validation and application of a quantitative systems model may eventually improve our ability to reliably predict the CV safety between animals and humans. Despite the shortcomings, empirical PK/PD modeling continues to play a vital part in integrated CV safety assessment, allowing for quantitative assessment of CV risk prior to FIH trials, enabling design of dose escalation, and planning of appropriate monitoring and management strategies for CV safety in clinical trials.…”

“…However, based on our experience and historical data, identifying more than two cosine functions is challenging. 6 , 7 , 43 Furthermore, the second circadian variation function has notably shorter period (~2 h) and amplitude (~12%), contributing little toward the accuracy of further predictions and, arguably, could be ignored.…”

An In Silico Platform to Predict Cardiotoxicity Risk of Anti-tumor Drug Combination with hiPSC-CMs Based In Vitro Study

“…Notably, it has allowed us to gain insights into various aspects of cardiovascular health. For instance, in the context of peripheral arterial disease, multiscale models have elucidated the dynamic process of perfusion recovery post-ischemia, providing valuable information for potential therapeutic interventions [ 59 ]. Additionally, integrated cardiorenal models have provided crucial insights into adaptive cardiac remodeling in response to pressure and volume overload, shedding light on the interplay between cardiac and renal function [ 60 ].…”

Quantitative approaches to drug safety: The 2022 PSP special issue

“…By using this model to examine PI3‐kinase inhibitors that have differential selectivity for various PI3‐kinase isoforms, they suggest ways to avoid colitis in patients through targeting of particular isoforms. Similarly, Fu et al 14 expand on previous research from their group by presenting a QSP model of the cardiovascular system that accounts for interactions among relevant biomarkers, such as heart rate, arterial blood pressure, and cardiac output. Through validating the model with a proof‐of‐concept drug, the β‐blocker atenolol, they establish a platform that can be used to minimize the possibility that developmental compounds may cause adverse cardiac events.…”