Assessing Tyrosine Kinase Inhibitors-induced Cardiotoxicity with an Organoid-AI System

PROJECT SUMMARY Tyrosine kinase inhibitors (TKIs) are specified small-molecule inhibitors of the activity of tyrosine kinases and have shown therapeutic impact on treating cancers. Despite being a prevalent class of drugs in the pharmaceutical industry, their development and clinical application are frequently hindered by a wide range of

cardiovascular complications: QT prolongation/arrhythmia, left ventricular dysfunction, congestive heart failure, ischemia, myocardial infarction, and hypertension. Cardiotoxicity's repercussions impede the advancement of novel TKIs for cancer therapy and furthermore cause failures in preclinical drug discovery and clinical

development. Therefore, there is an urgent need to assess cardiotoxicity induced by TKIs used in cancer patients' treatment. However, there is still no targeted and effective preclinical trial due to a) only focusing on anti-tumor effects without systematic examination of coexisting cardiovascular effects, b) limited efficiency and

accuracy of cardiotoxicity prediction, and c) inter-species differences between animals and humans on cardiotoxic responses. To address this unmet need, a new in vitro human model for comprehensively assessing TKIs-indued cardiotoxicity is proposed here. Recently, human pluripotent stem cell (hPSC)-derived vascularized

cardiac organoids (VCOs) developed in PI’s and other labs have shown great promise in emulating the human heart in both cardiovascular structure and function, which makes it an ideal in vitro drug toxicity evaluation system targeting cardiovascular cells by TKIs. However, three significant challenges remain in applying hPSC-derived

VCOs to cardiotoxicity evaluation: 1) insufficient and uncoupled assessment of organoid structural and functional properties; 2) continuous generation of large datasets from multifaceted characterizations that requires more integrated analysis without human bias; 3) low efficiency with more individual hPSC lines. It is hypothesized that

artificial intelligence (AI)-driven biomedical data featuring and predicting address the challenges for accurately assessing TKI-induced cardiotoxicity by phenotyping the cardiovascular structure and function of VCOs. The central goal is to establish an organoid-AI system to assess TKI-induced cardiotoxicity efficiently and accurately

with three specific aims: Aim 1. Predict TKI-induced toxicity on cardiovascular structure in VCOs by Generative AI algorithm; Aim 2. Phenotype TKI-induced cardiovascular dysfunction in VCOs; Aim 3. Establish a TKI-induced cardiotoxicity assessment system with an organoid-AI system. Upon completion of the proposed project, a

comprehensive human organoid-AI system for assessing TKI-induced cardiotoxicity will be established to increase the efficiency and accuracy of preclinical drug safety evaluation of TKIs on human cardiotoxicity on both cardiovascular structure and function.