Automation and AI Will Drive Next-Gen CAR T Manufacturing

The remarkable clinical success of CAR T therapies in blood cancers has validated the promise of engineered cell therapies. But according to Adam Janvier, PhD, head of cell therapy at eXmoor Pharma, the industry faces a crucial challenge: transforming highly personalized, labor-intensive manufacturing into scalable, commercially viable production systems.

“The next big thing that really needs to come through is how we can start tackling solid tumors,” Janvier says. “Until solid tumor is truly tackled, we’re always going to be missing that key next step of what CAR T has the promise to do.”

Although scientific hurdles remain, Janvier emphasizes that manufacturing constraints are equally pressing. Today’s autologous CAR T therapies rely on harvesting a patient’s own immune cells, engineering them outside the body, and reinfusing them after a manufacturing process that can stretch to two weeks. For critically ill patients, that timeline can prove devastating.

“We might fail a process because the donation just isn’t good enough,” he explains, referring to inconsistent starting material collected from heavily pretreated cancer patients. “Then we’ve got a four to six week vein-to-vein time due to manufacturing, testing, and logistics, where the patient might pass away during the period.”

The dual risks of manufacturing failure and lengthy turnaround times are pushing developers and contract development and manufacturing organizations (CDMOs) toward alternative strategies. Among the most promising are allogeneic, or off-the-shelf, CAR T therapies and emerging in vivo approaches that could eliminate ex vivo manufacturing altogether.

“There’s a lot of work going on now with in vivo CAR T,” Janvier says. “Instead of taking a blood donation as starting material, there is growing evidence that we could use the reprogramming technology directly with the patient, generating functional CAR T cells in situ.” Although such approaches remain early-stage, they represent a potential paradigm shift by reducing manufacturing time, simplifying logistics, and lowering costs.

Analytics and quality control also remain major bottlenecks. Current CAR T testing workflows rely heavily on expensive, time-consuming assays, including flow cytometry, qPCR, and tests to confirm the quality and safety of the lentivirus. Janvier believes that AI could eventually streamline many of these processes.

“One of the exciting technologies coming out is AI-based flow-cytometry approaches,” he says, pointing to emerging platforms that use label-free imaging and machine learning to characterize cells without fluorescent antibodies. “All of a sudden, you’re removing the need for antibodies and fluorophores, reducing the cost,” he says.

Still, Janvier argues that automation might ultimately become the defining factor in whether CAR T therapies can achieve widespread commercial adoption. Current cleanroom manufacturing remains highly manual, requiring specialized staff and flexible—but inefficient—facility layouts. “Once we approach commercial scale, batch costs need to have substantially decreased,” he says. “Automation can really support that.”

Janvier envisions future CDMOs operating sophisticated robotic manufacturing platforms capable of running around the clock while minimizing operator variability and contamination risk. However, implementing such systems will require substantial capital investment and new technical expertise. “These are not going to be inexpensive methods to implement into facilities,” he notes. “They’re going to be a large capital investment, and also a large people investment.”

Beyond manufacturing hardware, Janvier believes structural changes must begin much earlier in therapy development. Many CAR T programs originate in academic laboratories focused primarily on biological innovation rather than manufacturability or commercial scalability. “What can be missed there is the translation starting at the very beginning,” he says. “You need to start with the end in mind.”

That means considering GMP compatibility, scalability, cost-of-goods analysis, and automation readiness long before therapies enter clinical trials. Investors, Janvier adds, are increasingly demanding evidence that therapies can ultimately be manufactured at scale—not simply that the science is compelling.

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