FMSG:BIO: Integrating Artificial Intelligence with Bioprinting for Future Manufacturing of Organoids

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Human pluripotent stem cell (hPSC) derived organoids are highly valuable for disease treatment and therapeutic development. Translating organoids to practical use will require scalable and reproducible methods to produce high-quality organoids. This project will devise strategies exploiting three-dimensional (3D) bioprinting for scalable organoid manufacturing. Machine Learning (ML)/Artificial Intelligence (AI) techniques will be developed to rapidly assess organoid quality from microscopy images. The goal is to offer a pathway for large-scale manufacturing of tailored and patient-specific organoids by augmenting ML/AI techniques for 3D bioprinting. The research will provide trainees with multidisciplinary skill sets, encompassing bioprinting, organoid engineering, imaging, and AI methods. In addition, the project will integrate global and social outreach aspects into engineering curriculum, offering a holistic educational pathway to train the future, globally aware U.S. biomanufacturing workforce to lead the world in revolutionary manufacturing concepts.This proof-of-concept Future Manufacturing Seed Grant (FMSG) project aims to integrate beneficial mechano-signaling pathways for organoid manufacturing via ML/AI aided 3D bioprinting. In executing this approach, the goal is to develop non-invasive assays to measure organoid phenotype to meet the critical quality attributes of the manufacturing pipeline. The central hypothesis is that imposing cell confinement via encapsulation will induce favorable mechano-transduction pathways, which will enhance organoid differentiation by deactivating actin filaments. The resulting cytoskeletal modification from actin remodeling can be exploited to extract information about cell characteristics to predict phenotype. This hypothesis will be tested by developing techniques for (i) cell-confinement driven organoid derivation using 3D bioprinting; and (ii) predicting cell fate from cytoskeletal modifications using Artificial Intelligence (AI) models to identify features of organoid development in bright-field images. This FMSG project demonstrate the feasibility of integrating AI with 3D bioprinting in the organoid generation pipeline, with the long-term goal of enabling scalable manufacturing of organoids with stringent in-line quality control.This project is jointly funded by the Division of Chemical, Bioengineering, Environmental, and Transport Systems and the Division of Engineering Education and Centers in the Directorate for Engineering and the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences.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.