Collaborative Research: CPS: Medium: AI-Boosted Precision Medicine through Continual in situ Monitoring of Microtissue Behaviors on Organs-on-Chips

癌症是全世界最主要的死亡原因之一，估计每年死亡人数接近1 000万人。尽管在开发有效的癌症诊断和治疗方法方面做出了重大努力，但预测患者对抗癌治疗药物的反应的能力仍然难以捉摸。这是一个重要的里程碑，因为及早选择正确的治疗方法可能意味着更好的抗肿瘤效果和更高的生存率，而错误的选择意味着肿瘤复发、耐药性的产生、副作用没有预期的益处，以及治疗成本的增加。一个网络物理系统，可以准确预测患者肿瘤对抗癌治疗的反应；也就是说，实现实时精准医疗，不仅可以对健康结果产生变革性影响，还可以对治疗成本产生变革性影响。因此，该项目的目标是开发一种工程网络物理系统，该系统将先进的生物模型与最先进的人工智能方法相结合，用于预测、自动筛选抗癌药物并优化其剂量。这将推动科学朝着实现长期期望的精准医学范式的方向发展，从而产生重大的社会影响。该项目具有额外的社会影响，包括通过增加对工程人类癌症和心脏组织模型系统的采用，将过去几年围绕动物使用的指数增长的伦理问题降至最低。该计划将提供机会，向K-12学生推广STEM教育，培训学生，特别是来自弱势群体的学生，并向公众传播科学和工程知识。研究人员将利用他们在生物制造、组织工程、微流体、生物分析和人工智能方面的专业知识，开发一个通用的、自我剂量优化的“多传感器集成多器官芯片”平台，该平台可用于准确预测该项目中抗癌方案的有效性和安全性。第一个创新是采用三维生物打印技术生成血管化导管癌模型和血管化心脏组织模型，从而构建真正的仿生人体心肌，用于评估药物毒性。这两种生物打印模型对微流体系统的适应也是一项重大创新。此外，对关键生物物理化学参数的实时无创监测将生成大规模多维数据，从而实现准确的数据驱动预测建模。此外，该平台将通过一种新的联合贝叶斯模型实现芯片的自我剂量优化，该模型由两个深度学习模型实现，能够分别解决多实例学习和多维数据序列的依赖关系。该项目将使用一系列商用单元来构建模型，并进行初始平台开发和优化。预计在未来的迭代和其他癌症治疗、药物组合和抗癌方案剂量优化中，人类标本将作为快速和安全的试验台进行扩展。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Cancers are among the leading causes of death around the world, with an estimated annual mortality of close to 10 million. Despite significant efforts to develop effective cancer diagnosis and therapeutics, the ability to predict patient responses to anti-cancer therapeutic agents remains elusive. This is a critical milestone as getting the right choice of therapy early can mean superior anti-tumor outcomes and increased survival, while the wrong choice means tumor relapse, development of resistance, side effects without the desired benefit, and increased cost of treatment. An cyber-physical system that allows an accurate prediction of patient tumor responses to anti-cancer therapies; that is, enable real-time precision medicine, can have a transformative effect not only on health outcomes, but also on the costs of treatment. The goal of this project is therefore to develop an engineered cyber-physical system that combines advanced biological models with state-of-the-art artificial intelligence methods for predictive, automated screening of anti-cancer drugs and optimizations of their dosing. This will move science towards realizing the long-desired precision medicine paradigm leading to significant social impacts. The project has additional social impacts, including minimizing the exponentially growing ethical issues surrounding the use of animals in the past years through increased adoption of the engineered human cancer and heart tissue model systems. The project will provide opportunities to promote STEM education for K-12 students, train students, especially those from under-represented groups, and disseminate science and engineering knowledge to the public.The investigators will leverage their expertise in biofabrication, tissue engineering, microfluidics, bioanalysis, and artificial intelligence to develop a generalized, self-dose-optimizing "multi-sensor-integrated multi-organ-on-a-chip" platform, which can be used to accurately predict both efficacy and safety of anti-cancer regimens in this project. The first innovation is the adoption of three-dimensional bioprinting for generating the vascularized ductal carcinoma model and vascularized cardiac tissue model, leading to the construction of a truly biomimetic human myocardium for evaluating drug toxicity. The adaptation of both of the bioprinted models to microfluidic systems is also a major innovation. Additionally, the real-time yet non-invasive monitoring of key biophysicochemical parameters will generate large-scale multi-dimensional data to enable accurate data-driven predictive modeling. Moreover, the platform will enable self-dose-optimization on the chips through a novel joint Bayes modeling implemented by two deep learning models capable of addressing multiple-instance learning, and dependency in sequences of multi-dimensional data, respectively. The project will use a range of commercially available cells to construct models and pursue the initial platform development and optimizations. Extensions are anticipated for human specimens in future iterations and other cancer treatment, drug combination, and dose optimization in anti-cancer regimens as a rapid and safe testing-bed.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.