Redefining Quality Assurance in Decentralized Cell Therapy Manufacturing: A Data-Driven Framework for the Future of ATMPs..

Abstract

The landscape of advanced therapy medicinal products is undergoing a profound transformation as cell and gene therapies transition from centralized manufacturing facilities to decentralized, hospital-based, and point-of-care production models throughout the United States. This shift, driven by the unique requirements of autologous therapies and enabled by advances in automation and closed-system technologies, promises to revolutionize patient access by reducing treatment timelines and expanding geographic availability. However, decentralized manufacturing introduces unprecedented quality assurance challenges that traditional biopharmaceutical frameworks struggle to address effectively. Maintaining consistent oversight across geographically dispersed sites, standardizing operator training when local teams possess vastly different backgrounds, achieving real-time visibility into manufacturing performance, and ensuring product comparability across multiple facilities all demand fundamentally reimagined quality systems. This article examines these challenges through detailed case studies from pioneering academic medical centers that have implemented innovative approaches to decentralized quality assurance. The University of Pennsylvania's centralized control site model demonstrates how remote coaching and harmonized deviation governance can maintain consistency across distributed networks. MD Anderson Cancer Center's behavioral quality framework reveals how integrating psychological safety principles and coaching-based reviews reduces error recurrence while enhancing operator accountability. Stanford Medicine's digital quality dashboard illustrates the power of predictive analytics and real-time monitoring to enable proactive interventions before quality failures occur. Drawing from these real-world implementations and emerging regulatory guidance, this article proposes an integrated data-driven quality assurance framework that combines centralized regulatory oversight, digital infrastructure, behavioral intelligence, modular training ecosystems, and predictive analytics. This framework positions quality assurance not as a compliance gatekeeping function but as a strategic enabler of therapeutic innovation—one that makes decentralized manufacturing models scalable, sustainable, and capable of delivering life-saving advanced therapies to patients who need them most, regardless of geographic location or institutional resources..