I-Corps: Simulation-based Decision Support Platform for Regenerative Medicine Manufacturing and Distribution

这个I-Corps项目更广泛的影响/商业潜力是开发一个基于模拟的决策支持平台，以帮助再生医学制造商，包括细胞，基因和组织工程产品。 该技术旨在解决再生医学产品制造和分销所面临的挑战。 其目标是帮助制造商在早期和整个制造过程中识别问题。该平台的建立将有助于改善获取途径、提高产品质量并降低成本，从而使数百万患有晚期疾病以及需要组织和器官移植的患者受益。I-Corps项目旨在开发一个模拟平台，为再生医学制造商提供决策支持。该仿真平台旨在创建单个制造设施或整个大区域的制造网络的数字孪生模型。该平台包含两种类型的制造模式：自体产品的患者特定个性化制造工艺和同种异体产品的批量制造工艺。该平台使制造商能够制定系统级决策，以改进设施设计，并预测“假设”情景，以应对意外中断。所提出的技术可以通过解决广泛的挑战来增强再生医学制造，供应链，监管和决策科学领域的知识。 这项技术可以帮助确保制造和分销过程的准确性、可靠性和及时性。该奖项反映了NSF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。

The broader impact/commercial potential of this I-Corps project is the development of a simulation-based decision-support platform to assist regenerative medicine manufacturers, including cell, gene, and tissue-engineered products. The proposed technology aims to address the challenges facing the manufacturing and distribution in regenerative medicine products. The goal is to assist manufacturers in the identification of problems early on and throughout the overall manufacturing process. The proposed platform may lead to improved access, improved quality of the product, and reduced costs, which may benefit the millions of people suffering from terminal diseases as well as those in need of tissue and organ transplants.This I-Corps project is based on the development of a simulation platform to provide decision support for regenerative medicine manufacturers. The simulation platform is designed to create digital twins of a single manufacturing facility or a manufacturing network throughout a large region. The platform incorporates two types of manufacturing modes: a patient-specific, personalized manufacturing process for autologous products and a batch manufacturing process for allogeneic products. The platform enables manufacturers to devise system-level decisions to improve facility design and predicts “what if” scenarios to plan for unexpected disruptions. The proposed technology may enhance knowledge in regenerative medicine manufacturing, supply chain, regulatory, and decision science realms by addressing a wide range of challenges. The proposed technology may help to ensure accuracy, reliability, and timeliness in the manufacturing and distribution processes.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.