Next Generation Preclinical Models for Cardiovascular Drug and Therapy Development: Integrating Organoids, Organ-on-Chip, and Computational Approaches

Cardiovascular disease remains the leading cause of death worldwide, yet drug development in this field still suffers from one of the highest attrition rates in pharmaceutical research. A large share of candidate molecules that perform well in two-dimensional cell cultures or rodent models fail in human trials, often because traditional preclinical systems poorly recapitulate human cardiac and vascular physiology, sex differences, comorbidities, and off-target toxicities. Closing this translational gap requires a new generation of preclinical platforms that better mirror human biology and that connect early discovery chemistry to predictive functional readouts.Recent advances in human induced pluripotent stem cell (hiPSC) biology, cardiac and vascular organoids, heart-on-chip and vessel-on-chip microphysiological systems, multi-organ chips, and bioprinted tissues are reshaping how cardiovascular drug candidates are evaluated. In parallel, computational pipelines (structure- and ligand-based virtual screening, molecular dynamics, free-energy methods, AI- and machine learning-driven property prediction, physiologically based pharmacokinetic modelling, and quantitative systems pharmacology) are accelerating lead identification, optimization, and early toxicity triage. The convergence of medicinal chemistry, in silico discovery, and human-relevant preclinical models offers a promising route to safer, more effective cardiovascular therapeutics, and supports regulatory momentum toward New Approach Methodologies under initiatives such as the FDA Modernization Act 2.0.Subtopics include, but are not limited to:• Cardiac, vascular, and multi-tissue organoids and assembloids for disease modelling and pharmacological screening;• Heart-on-chip, vessel-on-chip, and multi-organ microphysiological systems for efficacy, pharmacokinetic, and pharmacodynamic profiling;• hiPSC-derived cardiomyocytes, endothelial, smooth muscle, and immune cells for patient-specific and stratified pharmacology;• 3D bioprinted cardiovascular tissues and engineered heart tissues for contractility, electrophysiology, and mechanobiology studies;• Medicinal chemistry-driven design and lead optimization of small molecules, peptides, and PROTACs targeting cardiovascular pathways;• In silico drug discovery, including structure- and ligand-based virtual screening, molecular dynamics, and free-energy calculations;• AI and machine learning for hit identification, ADMET prediction, polypharmacology, and repurposing in cardiovascular indications;• Predictive cardiotoxicity assessment, including pro-arrhythmia (CiPA-aligned), contractile, mitochondrial, and vascular toxicity readouts;• Quantitative systems pharmacology and physiologically based pharmacokinetic modelling to bridge in vitro, in vivo, and clinical data;• Integration of multi-omics, high-content imaging, and electrophysiological data from advanced models for mechanism-of-action studies;• Benchmarking and qualification of next generation models against animal data and clinical outcomes;• Regulatory science perspectives on New Approach Methodologies for cardiovascular drug submissions. Topic editors: Ashish D Patel, Ghanshyam Ratilal Parmar, Svetlana Morozkina Source: https://www.frontiersin.org/research-topics/83700/next-generation-preclinical-models-for-cardiovascular-drug-and-therapy-development-integrating-organoids-organ-on-chip-and-computational-approaches