Artificial intelligence and multi-modality collaborative models can modernize cardiotoxicity detection, protect patients, and sustain benefits in oncology care.
Abstract Cancer therapeutics account for a significant proportion of new drug development, reflecting advances in diagnosis, treatment, and disease control. However, with this trend comes a responsibility to ensure patient safety both in the near term and over the long term. Among these considerations, cardiovascular safety is a priority. Downsizing and resource constraints within regulatory agencies, particularly the United States Food and Drug Administration (FDA) threaten safety oversight capacity, increasing the need for automation, structured data standards, common data elements and shared analytics. Public health policy, public–private partnerships, big data capabilities, and the FDA Oncology Center of Excellence (OCE) provide avenues to strengthen Cardio-Oncology safety through cross-center coordination, technology advances, guidance development, and methodological innovation. In this third offering of a 3-part series, the objective is to outline public–private partnerships and collaborative oversight models, linking sponsors, regulators, health systems, payers, and patient groups to operationalize continuous surveillance, standardized cardiac endpoints, and transparent data sharing. Building on existing scientific and regulatory foundations, there is a pressing need to leverage contemporary technologies and creative, interdisciplinary thinking to advance predictive models, monitoring strategies, and mitigation frameworks. A strategic forecasting and preparedness framework is proposed that includes embedding fit-for-purpose cardiac safety endpoints early in development; interoperable, real-time safety data pipelines across pre- and post-marketing phases; deploying artificial intelligence (AI)-enabled signal detection with human-in-the-loop adjudication; using real world evidence (RWE) to confirm clinical benefit-risk under accelerated approvals; and pre-specifying label-update triggers tied to cardiac signal thresholds. Together, these policy and technology innovations can modernize cardiotoxicity detection, protect patients, and sustain benefits in oncology care.
Richard C. Becker (Fri,) conducted a review in Cardiotoxicity in cancer therapeutics. Artificial intelligence and collaborative models was evaluated. Artificial intelligence and multi-modality collaborative models can modernize cardiotoxicity detection, protect patients, and sustain benefits in oncology care.