Collaborative Research: E-RISE: Center for AI-Driven Bioprocess Control for Cell Manufacturing

The Center for AI-Driven Bioprocess Control for Cell Manufacturing (CAPCell) aims to establish Puerto Rico’s first AI-powered hub for cell manufacturing, addressing critical challenges in bioprocessing to optimize the production of mesenchymal stem cells (MSCs) and their bioactive byproducts, such as extracellular vesicles (EVs). By integrating artificial intelligence, machine learning, biosensors, IoT, and bioprocess control, CAPCell seeks to advance precision biomanufacturing, enhance yields, reduce production costs, and improve the quality of biological products. The initiative is driven by a collaboration among the University of Puerto Rico at Mayaguez, the University of Puerto Rico-Rio Piedras (UPRRP), theUniversidad Del Turabo (UDT), and the Puerto Rico-Science, Technology, and Research Trust (PR-STRT), and is focused on developing scalable AI-enabled bioreactor platforms, noninvasive sensing technologies, and AI tools such as digital twins and large language models (LLMs) for biomanufacturing optimization. CAPCell will also drive workforce development through K-12 outreach, undergraduate and graduate training, and professional education programs, cultivating a future-ready STEM workforce. With a strong emphasis on research, innovation, and commercialization, CAPCell will leverage Puerto Rico’s robust life sciences ecosystem to foster academia-industry partnerships, launch startups, and contribute to the jurisdiction’s economic growth. By addressing critical knowledge gaps and advancing AI-driven solutions, CAPCell aims to position Puerto Rico as a national leader in intelligent, sustainable, and affordable biomanufacturing. The research aim of Center for AI-Driven Bioprocess Control for Cell Manufacturing (CAPCell) is to integrate Artificial Intelligence (AI), machine learning, biosensors, the Internet of Things (IoT), and bioprocess control to optimize production of mesenchymal stem cells and their bioactive by-products. The fundamental research hypothesis is that by integrating real-time data from imaging, sensors, bioreactors, and quality control systems, AI can predict optimal culture conditions, detect anomalies, and adjust parameters to maximize yield and consistency. This hypothesis will be tested by achieving the following research goals: (1) develop a scalable, AI-enabled culture platform for manufacturing stem cells; (2) develop novel, noninvasive sensing methodologies for cell manufacturing monitoring; and (3) develop an integrated AI cyber-physical framework to optimize biomanufacturing through physics-informed digital twins, AI agents, and safety constrained AI decision-making. The educational and workforce development activities are devised to provide human capital in AI and cell manufacturing to the jurisdiction; they include seed funding to early and mid-career faculty, course-based, research and capstone activities for graduate and undergraduate students, and outreach activities targeting working professionals and K-12 student and teachers. This project is supported by the EPSCoR Research Infrastructure Improvement Program: EPSCoR Research Incubators for STEM Excellence (E-RISE). E-RISE supports the development of sustainable research infrastructure and capacity in EPSCoR jurisdictions through collaborative, hypothesis-driven, or problem-driven research and workforce development to improve competitiveness in selected STEM fields. 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.