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HLS-Cardiac Safety AI Trained Human Heart and Micro Heart Model

HLS-心脏安全 AI 训练的人类心脏和微心脏模型

基本信息

批准号：
9764845
负责人：
Tetsuro Wakatsuki
金额：
$ 88.17万
依托单位：
INVIVOSCIENCES, INC.
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-06-15 至 2021-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9764845
关键词：
3-Dimensional Action Potentials Address Adult Arrhythmia Artificial Intelligence Biological Assay Biomedical Research Biotechnology Calcium Cardiac Cardiac Myocytes Cardiotoxicity Cells Clinical Clinical Trials Communities Computer Analysis Computer Simulation Contracts Coupling DNA Sequence Alteration Data Development Dose Drug Costs Drug Industry Electrophysiology (science)Exhibits Expert Systems Fibroblasts Gene Expression Generations Genetic Genetic Predisposition to Disease Guidelines Heart Human In Vitro Individual Ion Channel Laboratories Libraries Marketing Measures Methods Michigan Mitochondria Modeling Pharmaceutical Preparations Pharmacologic Substance Pharmacology Phase Phenotype Physiology Population Heterogeneity Preclinical Testing Probability Process Productivity Protocols documentation Publishing Pump Reproducibility Risk Running Safety Sample Size Sampling Scientist Shipping Ships Slice Small Business Innovation Research Grant Statistical Data Interpretation Stem cells Sudden Death System Testing Tissues Training Universities Validation Washington Work base cardiac tissue engineering commercialization computerized tools cost cost effective drug candidate drug development drug discovery experimental analysis experimental study heart cell heart preservation high throughput screening human data improved in vitro Assay induced pluripotent stem cell mathematical model novel therapeutics personalized medicine response safety assessment screening side effect simulation success

项目摘要

HLS17-12. The US FDA is considering to establish a new cardiac safety assessment approach defined by a new paradigm called, “Comprehensive in vitro Proarrhythmia Assay (CIPA)”. The CIPA will 1) assess drug effects on each cardiac ion channel type individually using a high- throughput assay ion channel assays, 2) compute net effect on repolarization and risks for torsade pointes (TdP) using a mathematical model, and 3) confirm the computational prediction by measuring the drug’s effects on action potentials in induced pluripotent stem cell (iPSC) derived human cardiac myocytes (CMs). This paradigm shift, if successful, could reduce the cost of cardiac safety analyses by replacing or lowering the requirement to perform an expensive ($2-4 million) thorough QT study during clinical trials. Protecting consumers from drug induced arrhythmia and sudden deaths is a paramount importance for the regulators and pharmaceutical companies as well as lowing the cost of drug development. Many cardiac safety scientists, however, are skeptical about CIPA’s approach since CMs derived from human iPSCs exhibit a poor excitation-contraction coupling due to their immaturity. In addition, a proposed CIPA mathematical model was developed to simulate electrophysiology of human adult CMs, so there is a mismatch between experimental system and computational tool. To address these concerns, we proposed three specific aims in tw0 phases by following Fast- Track SBIR processes. Phase I feasibility Aim 1 will measure drug-induced changes in AP and CaT using human adult heart slices isolated from human donors. Here we will confirm our successful handling and analyzing human adult heart slices, which will be based on a recently published protocol by our collaborator, Dr. Igor Efimov, at George Washington University. After this validation, we will move on to perform the following two studies: Aim 2. Compare drug-induced changes in AP and CaT in NuHearts generated from adult CMs and cardiac fibroblasts from same human donor hearts; Aim 3. Validate and improve the computational models and train an artificial intelligence to predict cardiac safety risks of unknow compounds. After our successful completion proposed projects, we can establish an unprecedented cardiac safety assessment platform that can predict safety issues using a well-trained AI without doing any experiments using human heart slices that are rarely accessible for most of the safety laboratories or biotech firms.

HLS17-12。美国FDA正在考虑建立一种新的心脏安全性评估方法