ArticleBiotechnology journal2026
Capacitance Technology Enables Automated Feeding, Improved Expansion, and Higher Throughput of CAR-T Cell Stirred-Tank Bioreactor Cultures.
Article in Biotechnology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
Funding
Abstract
Chimeric antigen receptor (CAR) T cells present a novel and transformative approach to treat certain haematological malignancies. However, CAR-T cell expansion methods are still under development and often rely on manual, low-control culture methods. The transition to bioreactors would allow for greater process control and scalability and is a key focus of research in the field. Despite this, there are few methods to determine culture progression without the need for manual cell sampling which risks introducing errors and heightening contamination risks. In this article, we assessed whether capacitance technology could deliver reliable, on-line cell concentrations by comparing T cell, and CAR-T cell bioprocesses with Chinese hamster ovary (CHO) cultures-widely used in biotechnology and with established capacitance usage. Finding that capacitance technology could accurately measure CAR-T cell concentrations, we then demonstrated the automation of feeding using capacitance-derived triggers which improved bioprocess performance in terms of cell concentration and throughput. We anticipate that this study will expand avenues of investigation regarding capacitance as a suitable process analytical technology (PAT) to enable monitoring and control of CAR-T cell manufacture, and potentially other cell and gene therapy products. It may also enable remote monitoring of multiple batches, harvest control, and the generation of large collections of process data for modelling, which will further progress the field.
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