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    Home » AI to Revolutionize Biopharmaceutical Manufacturing, Says Northeastern Professor
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    AI to Revolutionize Biopharmaceutical Manufacturing, Says Northeastern Professor

    techgeekwireBy techgeekwireMarch 4, 2025No Comments3 Mins Read
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    AI to Revolutionize Biopharmaceutical Manufacturing

    Many crucial modern treatments for serious diseases, including cancer, metabolic disorders and infectious diseases, depend on biopharmaceuticals. These medications, derived from biological sources like living cells, tissues, or biological substances such as proteins or nucleic acids, frequently offer enhanced effectiveness and fewer side effects.

    However, producing these biopharmaceuticals is a remarkably complex process, as explained by Wei Xie, an assistant professor of mechanical and industrial engineering at Northeastern University. The process involves numerous biological, physical, and chemical elements that are constantly changing and interacting at all levels from the molecular to the macroscopic. This complexity is further compounded by the limited availability and inconsistency of relevant data, especially as new treatments such as cell and gene therapies become more personalized.

    To address these critical challenges, Xie recently received a prestigious CAREER award from the National Science Foundation.

    AI-Driven Solutions

    Her research will focus on developing a fundamental methodology that utilizes artificial intelligence designed with an understanding of biological mechanisms to significantly improve innovations in biopharmaceutical manufacturing. “This project will help make lifesaving biopharmaceuticals more rapidly available by accelerating biomanufacturing systems integration and automation, significantly improving capabilities,” Xie states. “It will focus on mechanism-informed AI, a new frontier that will integrate scientific knowledge, including synthetic biology and biosystems, with intelligence and decision making under uncertainty.”

    Xie’s research aims to create fundamental AI for biomanufacturing. It will allow for the unified representation of knowledge across various manufacturing systems. This will enable AI to easily learn from a limited amount of data to understand underlying bioprocessing mechanisms. The end goal is to optimize control strategies within and across different scales of production.

    Xie and her team have previously showcased the potential of AI in large-scale manufacturing of pluripotent stem cells – cells with a natural ability to develop into different types of specialized cells (brain, blood, bone, or muscle cells). As part of this research, Xie and her team developed an innovative biological system-of-systems framework, or Bio-SoS. This modular model accounts for cell functions such as metabolic reactions, cell-to-cell interaction, and interactions between cell aggregates and their environment.

    The Future of Manufacturing

    The Bio-SoS model also enables the combining and fusion of data from various production systems, from lab to large-scale manufacturing. It also offers different strategies for cell growth and improved predictions. While Bio-SoS demonstrated the potential of AI in a specific setting, Xie’s CAREER-funded research seeks to establish a more general and fundamental methodology for biomanufacturing, reaching down to the molecular level.

    “Each biomolecule (such as proteins or RNAs), composed of atoms with charge, is a complex system and can have different structures,” Xie says. “How does that affect molecular interactions? If the structure changes, how can we leverage this information in the manufacturing process to guide sample-efficient and interpretable learning on fundamental mechanisms and optimal control policies?”

    For example, she notes how mRNA vaccines require adjustments for different virus mutations. Xie’s research will explore how to achieve such adaptability through new AI modeling and optimization methods. This technology would support flexible manufacturing and enable a quick response when facing pandemics.

    Xie also anticipates that emerging sensing technologies, which improve the monitoring of bioprocesses at molecular and cellular levels, will provide better insights that AI can use. This will help decode fundamental biological and physical mechanisms, boosting scientific understanding.

    Beyond research, Xie aims to help develop a world-leading biomanufacturing workforce through training the current workforce and educating students.

    AI biopharmaceuticals manufacturing Northeastern University research
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