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PFI-TT: Automated Platform for Drug Testing in Human Heart Cells Using Light

PFI-TT：利用光对人类心脏细胞进行药物测试的自动化平台

基本信息

批准号：
1827535
负责人：
Emilia Entcheva
金额：
$ 20万
依托单位：
George Washington University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2021-01-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1827535&HistoricalAwards=false
关键词：
PFI TT Automated Platform Drug

项目摘要

The broader impact/commercial potential of this PFI project on the economy and public health in the United States will be achieved by providing drug and stem-cell researchers and developers with a superior yet low-cost technology for detection of adverse effects on the heart to deliver cheaper, more effective, and safer drug treatments. Drug development is expensive ($2.6 billion per drug) and a high-risk process, where inadequate assessment of failures prior to clinical trials and market approval can result in loss of human life and come at great financial losses to investors, termination of employees, and potential outsourcing to developing countries. The proposed technology will improve failure prediction during early preclinical testing, where future adoption of the commercialized product will reduce drug development opportunity costs. It will also enable the pursuit of more challenging projects, including personalized therapies and therapies tailored for specific patient populations, e.g. considering sex, race or other characteristics when testing a new drug treatment. The female team behind the technology is committed to the successful establishment and growth of a company with a goal to help improve diversity in the STEM-related startup field, and serve as allies and role models for future STEM entrepreneurs from all backgrounds.The proposed project will develop technology for basic and translational work in cardiac electrophysiology. It will empower mechanistic studies of potentially lethal heart arrhythmias by yielding high-content high-quality information about cardiac electrical dysfunction, relevant for the discovery of new antiarrhythmic therapies. The integration of optogenetic methods and optical imaging offers high-throughput functional assessment and enables personalized solutions in drug screening. The unmet needs and advantages offered by the technology include compatibility with human stem-cell-derived cardiomyocytes and tissue constructs, provision of controlled pacing conditions while gathering multiparameter spatio-temporal information for better predictions of drug attrition, and low-cost. The following challenges in the translation to commercial applications are addressed: 1) determine the optimal optical configuration for a stand-alone prototype that is low-cost, compact, and customizable with user-friendly software; 2) establish the workflow for scientifically valid (double-blinded and controlled) assay designs using the system; 3) identify key measurements (biomarkers) and algorithms to predict how in vitro data translates to in vivo clinical outcomes (endpoints). This will result in a free-standing prototype that can be easily integrated into established workflows, an expanded library of compounds tested in a blinded, controlled study, and arrhythmia prediction software that utilizes measured data to stratify cardiotoxicity risk.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该PFI项目对美国经济和公共卫生的更广泛影响/商业潜力将通过为药物和干细胞研究人员和开发人员提供上级但低成本的技术来实现，用于检测对心脏的不良影响，以提供更便宜，更有效和更安全的药物治疗。药物开发是昂贵的（每种药物26亿美元）和高风险的过程，在临床试验和市场批准之前对失败的评估不足可能导致人类生命的损失，并给投资者带来巨大的经济损失，解雇员工，并可能外包给发展中国家。该技术将改善早期临床前测试期间的失败预测，未来采用商业化产品将降低药物开发机会成本。它还将使追求更具挑战性的项目成为可能，包括个性化治疗和为特定患者群体量身定制的治疗，例如在测试新药治疗时考虑性别，种族或其他特征。该技术背后的女性团队致力于成功建立和发展一家公司，目标是帮助提高STEM相关创业领域的多样性，并为来自各种背景的未来STEM创业者提供盟友和榜样。拟议项目将开发心脏电生理学基础和转化工作的技术。它将通过产生与发现新的抗心律失常疗法相关的关于心脏电功能障碍的高内容高质量信息来增强对潜在致命性心律失常的机制研究。光遗传学方法和光学成像的整合提供了高通量的功能评估，并实现了药物筛选的个性化解决方案。该技术提供的未满足的需求和优势包括与人类干细胞衍生的心肌细胞和组织结构的兼容性，提供受控的起搏条件，同时收集多参数时空信息以更好地预测药物损耗，以及低成本。解决了将其转化为商业应用的以下挑战：1）确定用于低成本、紧凑且可使用用户友好软件定制的独立原型的最佳光学配置; 2）建立科学有效的工作流程，使用该系统的（双盲和对照）试验设计; 3）确定关键测量（生物标志物）和算法，以预测体外数据如何转化为体内临床结果（终点）。这将产生一个独立的原型，可以很容易地集成到既定的工作流程，一个扩大的化合物库测试在一个盲，对照研究，和心律失常预测软件，利用测量数据分层心脏毒性风险。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。