Artificial intelligence, machine learning, and digitalization systems in the cell and gene therapy sector: a guidance document from the ISCT industry committees.
Journal:
Cytotherapy
Published Date:
Aug 1, 2025
Abstract
As artificial intelligence (AI), machine learning (ML) and other digital tools gain prominence across industries, their application in cell and gene therapy (CGT) has become a topic of increasing interest. Discussions at recent meetings of the International Society of Cell and Gene Therapy (ISCT), including the 2024 ISCT Commercialization Signature Series (CSS), highlight the potential of these tools to help optimize CGTs. Through real-world case studies, including applications in smart bioprocessing and advanced analytics, we examine how these technologies can enhance manufacturing efficiency and increase market access. We also provide guidance definitions for the evolving automation and digitalization activities in CGT, emphasizing the importance of standardized language to facilitate progress in the field. The development of tools and methodologies for AI validation and standardization, alongside a faster evolution of the regulatory framework, remain some of the outstanding hurdles to a faster adoption. Ultimately, we caution these advancements with potential risks of data misinterpretation arising from limitations such as poor quality and size of datasets, and the use of inappropriate statistical models. Using these case studies alongside data gathered from a widely distributed public survey, we aim to clarify terminology and promote best practices as automation and digitalization shape the future of cell and gene therapies.
