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

HLS17-12美国FDA正在考虑建立一种新的心脏安全性评估方法 由称为“综合体外致心律失常测定（CIPA）"的新范例定义。的 CIPA将：1）使用高浓度- 通量测定离子通道测定，2）计算对复极化的净效应和 尖端扭转型室性心动过速（TdP），使用数学模型，以及3）通过以下方式确认计算预测： 测量药物对诱导多能干细胞（iPSC）衍生的动作电位的影响， 人心肌细胞（CM）。这种模式的转变，如果成功的话，可以降低成本， 心脏安全性分析，取代或降低要求，执行昂贵的（2 -4美元 在临床试验期间进行了全面的QT研究。保护消费者免受药物诱导 心律失常和猝死是一个至关重要的监管机构和制药 同时降低药物开发成本。 然而，许多心脏安全科学家对CIPA的方法持怀疑态度，因为CM来源于 来自人iPSC的细胞由于其不成熟而表现出差的兴奋-收缩偶联。在 此外，提出了一个CIPA数学模型，以模拟电生理学， 因此，实验系统和计算工具之间存在不匹配。 为解决这些问题，我们建议分两个阶段实现三个具体目标， 跟踪SBIR流程。I期可行性目标1将测量药物诱导的AP变化， 使用从人类供体分离的成人心脏切片进行CaT。在这里，我们将确认我们的 成功地处理和分析人类成人心脏切片，这将是基于最近的一个 由我们的合作者，乔治华盛顿大学的Igor Efimov博士发表的方案。在此之后 为了验证，我们将继续进行以下两项研究：目标2。比较药物诱导 在成人CM产生的NuHearts中AP和CaT的变化以及来自 相同的人类供体心脏; Aim 3.优化和改进计算模型， 人工智能预测未知化合物的心脏安全风险。 在我们成功完成建议的项目后，我们可以建立一个前所未有的心脏 安全评估平台，可以使用训练有素的人工智能预测安全问题，而无需 任何使用人类心脏切片的实验， 实验室或生物技术公司。

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.