Quality Assurance in AI-Enabled Manufacturing: Governance, Validation, and GxP Controls for Cell and Gene Therapy

AI technologies are considerably changing biopharmaceutical manufacturing and will continue to influence the operational environment for CGT manufacturing. With the integration of AI-enabled systems in deviation trending, batch record review, environmental monitoring, and automated decision support, QA will have an important role in governing, validating, and monitoring the systems with which they work. The production of cell and gene therapy (CGT) presents unique challenges affecting the deployment of artificial intelligence (AI) methods due to high biological variability, limited shelf life of products, and manual handling in an aseptic environment. Contributing to the growing body of knowledge in this space, this article reviews recent advancements in AI governance in GxP-regulated environments and proposes a framework for Quality Assurance leaders to adopt AI methods in GxP-regulated environments. Benefits such as reduced human error, expedited batch release, and process consistency will be identified, alongside challenges including algorithmic bias, model drift, explainability, and regulatory uncertainties. A realistic phased approach for implementation will be proposed to enable industry stakeholders to scale their digital capabilities. Central to the industry transformation are the imperatives to ensure product quality, patients' safety, and regulatory compliance throughout the transformation process.