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NOBEL PRIZE 2026

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NIHFOOD AND DRUG ADMINISTRATION

AI-Enabled Echocardiographic Biomarkers and Real-World Data for Predicting Cancer Therapy-Related Cardiac Dysfunction

Active
Institution
KAISER FOUNDATION RESEARCH INSTITUTE, CA
Principal investigator
Elizabeth Marjorie Cespedes Feliciano
Funding
$1.5M
Duration
2025–2028
Open portfolio

Moonbase score

Still being scored

Abstract

Abstract: Cancer survivors have up to a 42% higher risk of cardiac dysfunction than non-cancer populations, in part due to sequelae of cardiotoxic cancer therapies—collectively termed cancer therapy–related cardiac dysfunction (CTRCD). Yet current surveillance strategies suffer from low sensitivity, poor reproducibility, and lack of personalization. This proposal aims to transform cardio-oncology care by integrating FDA-cleared artificial intelligence (AI) echocardiographic biomarkers with real-world electronic health record (EHR) data to improve early detection and risk stratification of CTRCD. Leveraging a diverse cohort of over 34,000 patients treated with cardiotoxic therapies within an integrated healthcare system with comprehensive data, we will apply validated AI models to archived echocardiograms to identify subclinical cardiac dysfunction and develop predictive models that guide personalized surveillance. Specific aims include: (1) evaluating AI-derived biomarkers for early and standardized detection of CTRCD, and (2) developing and validating multimodal predictive models combining AI-echo and EHR data. This work will generate regulatory-grade evidence to inform FDA guidance, improve clinical outcomes, and establish a scalable framework for cardio-oncology surveillance in real-world settings.

Research team

  • Andrew Patrick AmbrosyPI
  • Elizabeth Marjorie Cespedes FelicianoPI
  • David OuyangPI

LOADING MOONBASE SCORE

FOOD AND DRUG ADMINISTRATIONU01Special Emphasis Panel[ZFD1 OCE-P (01)]dysfunctioncardiacsurveillancepredictive modelscardiac dysfunctionehr dataehrreal-world

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