Key result
Advanced in vitro and in silico models show promise for predicting cancer therapy-related cardiotoxicity.
Why the study?
Cancer therapy-related cardiovascular toxicity remains a major cause of morbidity and mortality among cancer survivors, necessitating reliable preclinical models to understand and predict cardiotoxicity early.
This review outlines the evolving landscape of preclinical in vitro and in silico models to better predict, detect, and understand cancer therapy-related cardiovascular toxicity.
Answers are grounded in this paper and cite their sources.
Animal and review evidence on CTR-CVT mechanisms; leaves open translation to targeted human prevention strategies.
Cancer therapy-related cardiovascular toxicity (CTR-CVT) remains a major contributor to morbidity and mortality among cancer survivors. While advances in cancer therapy have significantly improved survival rates, many of these treatments come at the cost of unintended cardiovascular damage. This creates a complex and pressing challenge in cardio-oncology: how to treat cancer, while minimising harm to the heart effectively. A central goal in cardio-oncology is therefore not only to understand the mechanisms of therapy-induced cardiac injury, but also to develop reliable, and predictive approaches to detect and assess CTR-CVT as early as possible, ideally before irreversible damage occurs. This review aims to explore the major preclinical in vitro models used to understand and predict cardiotoxicities induced by anti-cancer treatments, from traditional cell culture to the most recent technologies, such as 3D-bioprinting, organoids, organs-on-a-chip and artificial intelligence-based in silico approaches. Advantages and limitations are addressed for each experimental model to help guide future studies in cardiooncology that might better translate findings from the bench to the bedside.
No takes yet. Share an insight, caveat, or question.
Fratard et al. (2026) conducted a review in Cancer therapy-related cardiovascular toxicity. Preclinical in vitro models was evaluated. This review explores major preclinical in vitro models, including 3D-bioprinting, organoids, and AI-based in silico approaches, to predict cancer therapy-related cardiovascular toxicity.
Synapse has enriched 10 related papers. Consider them for comparative context: