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Robotic Systems Emerge for Cell and Gene Therapy Manufacturing

A September 2024 Cytotherapy paper describes a robotic cluster designed to automate manual steps in cell therapy manufacturing. Additional reviews published in 2019 and 2026, along with commentary from Genetic Engineering and Biotechnology News, discuss automation and AI as tools being explored for the cell and gene therapy manufacturing sector.

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By MarketScale Newsroom · Cell TherapyGene TherapyManufacturing AutomationRobotics
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Robotic Systems Emerge for Cell and Gene Therapy Manufacturing

Key takeaways

01

A robotic cluster combining a robotic arm with customized modules can handle standard cell therapy equipment (incubators, bioreactors, reagent bags) without requiring entirely new manufacturing platforms.

02

The system produced human CD8+ T cells with cell yields, viability and identity comparable to manual cultures while maintaining sterility, according to the Cytotherapy paper.

03

Manufacturing automation and AI are cited in industry analysis as potential solutions to skilled labor shortages and production scaling challenges, particularly for allogeneic therapies manufactured at larger scale.

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Researchers have described a robotic system built to automate steps in cell therapy manufacturing, according to a paper published in the journal Cytotherapy in September 2024. The system, developed by a team including authors affiliated with academic and industry labs, is presented as a way to adapt existing manual production methods without requiring an entirely new manufacturing platform.

What the robotic cluster does

According to the Cytotherapy paper, the robotic cluster combines a robotic arm with customized modules that allow it to handle standard cell therapy equipment, including incubators, bioreactors and reagent bags. The authors report that robotic cultures of human CD8+ T cells produced cell yields, viability and identity comparable to manually performed cultures, while the system maintained culture sterility during testing.

The paper states that commercial production of autologous cell therapies, such as chimeric antigen receptor T-cell products, currently relies on complex manual processes. The authors write that skilled labor costs and challenges in scaling manufacturing have contributed to high prices for these therapies. The paper describes the robotic system as one possible approach to supporting scale-up and scale-out of cell therapies originally developed with manual laboratory methods.

Automation and AI in broader industry discussion

Genetic Engineering and Biotechnology News reported on a separate analysis, published in Cytotherapy by researchers affiliated with the International Society for Cell & Gene Therapy and the European Society for Blood and Marrow Transplantation, that discussed manufacturing bottlenecks in the cell and gene therapy sector. That analysis, according to GEN's reporting, pointed to growing demand for skilled production personnel as new advanced therapy products gain regulatory approval, and suggested automation and artificial intelligence could play a role in addressing production challenges, particularly for allogeneic therapies that can be manufactured at larger scale than patient-specific treatments.

A 2019 review in Biotechnology Letters, available via PubMed Central, examined the history and prospects of automation in cell and gene therapy manufacturing. That review described manual, planar culture-based production as labor-intensive and prone to batch-to-batch variability, and outlined existing automated platforms, including robotic arm and incubator systems, that have been used in academic and commercial settings for cell expansion tasks.

A separate review published in Pharmaceutics in March 2026 examined the broader application of artificial intelligence and machine learning across cell and gene therapy development, from construct design through manufacturing and regulatory processes. That review is a single research paper's synthesis of the field rather than an independently verified industry count, and its figures on clinical trial numbers and market size projections are cited here only as the authors' stated estimates, not as confirmed facts.

What this means for manufacturing decisions

MarketScale analysis: For plants evaluating automation investments, the available published evidence points to modular robotic systems designed to work with existing standard equipment, rather than fully bespoke platforms, as one option under consideration in the field. Buyers considering automation should look for evidence of validated performance data, such as comparisons of cell yield and viability against manual processes, before making purchasing decisions.

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Deloitte's Biopharma AI Value Estimates Come With a Timing Catch

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  • 01Deloitte estimates $5–7B peak AI value for top-10 biopharma firms over five years, with cost reductions appearing in 1–2 quarters and revenue gains taking 3–4 quarters.
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CPC Biotech, Multiply Labs Develop Robot-Ready Cell Therapy Connector

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CPC Biotech, part of PSG and Dover, announced on May 27, 2026 that it is collaborating with Multiply Labs to develop an aseptic connector designed for robotic operation. The companies said the connector combines CPC's MicroCNX Nano Series with a proprietary interface engineered for robotic grippers, giving robots a consistent contact point during aseptic fluid transfers in Multiply Labs' closed cell and gene therapy processing systems.

  • 01Robotic grippers can reliably handle rigid parts but struggle with soft materials like bags and tubing, driving demand for robot-compatible connectors in sterile processing.
  • 02Commercial cell therapy production was under 5,000 doses per year in 2023 while global demand was estimated in the millions, creating manufacturing constraints.
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  • 01The bottleneck in automation is often the handoff, instrument to middleware to LIMS, so sensitivity and throughput gains depend on interfaces and downstream review as much as the instrument spec.
  • 02Waters’ “5x greater sensitivity” positioning and LabCollector’s AI Co-Scientist both point to integration work, sample prep, calibration and QA, middleware rules, and LIMS result review, as the gating factor for ROI.
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