Overcoming Raw-Material Variability Challenges for Autologous Adoptive Cell Therapies

Control of process and product quality is essential to ensuring the development and manufacture of safe and effective medicines. For autologous adoptive cell therapies, establishing control can be challenging due to significant raw material variability. The quality of patient cells, media formulations containing serum, and viral vectors used for gene delivery depends on numerous factors, not all of which can be easily controlled. Understanding the potential variabilities and how they may impact cell therapy process and product quality is therefore essential.^1-3

Adopting a risk-based, phase‑appropriate control strategy that identifies critical raw materials, qualifies suppliers, defines functional specs and testing (including safety), and predefines adaptive controls is essential to minimize negative impacts on product identity, purity, potency, and safety, according to Chy-Anh Tran, head of science and technology with FUJIFILM Biotechnologies California. Establishing to the degree possible standardized manufacturing practices that are still sufficiently flexible to accommodate raw material variability is equally important.²

Many Drivers of Variability

Starting material variability arises from several factors. The most consequential source, observes Cellares COO Ossama Eissa, is the starting material itself. “Patient apheresis quality is shaped by disease state, prior treatments, and collection method, and you simply cannot standardize it away,” he states.

Prior systemic therapies to which patients have been exposed significantly impact T cell fitness and functionality, adds Chantale Bernatchez, senior director of cell therapy process development at CTMC. “This consideration applies equally to hematologic malignancies and solid tumors, therefore influencing the performance of multiple T cell–based therapeutic modalities, including chimeric antigen receptor (CAR)-T, T-cell receptor (TCR)-engineered T cells, and tumor-infiltrating lymphocyte (TIL) therapies,” she says.

The collection method, encompassing device, protocol settings, anticoagulant type, operator technique, timing relative to the last treatment, and use of mobilization agents, can introduce variability as well, Tran says. Handling conditions for patient-derived cellular raw materials, including transport temperature and time, fresh versus cryopreserved workflows, and storage duration, can compound the variabilities, according to Tran.

Variability in viral vectors and media components, especially if media is uncharacterized or not chemically defined, further compounds the challenge, notes Eissa. Downstream manipulations can also magnify raw material variabilities.³ “All these factors combined make a flexible, data-rich manufacturing system essential,” he concludes.

Creating Numerous Process Development and Manufacturing Challenges

The consequences of not effectively managing raw material variability for autologous adoptive cell therapies can be severe.Failure to incorporate clinically representative starting material during process development introduces substantial risk to manufacturing robustness. “This gap frequently manifests as unanticipated variability or elevated batch failure rates during clinical production, ultimately necessitating reactive process re-design and delaying program progression,” says Bernatchez. In the worst-case scenario, failure of a production batch means the patient, who has been waiting for perhaps several weeks, does not receive what likely is a last-line treatment.² The drug maker also suffers lost revenues.

During process development, differences in raw materials make it hard to assess true process effects, so assay results can be highly variable, Tran notes. “For instance, healthy donor data may not always predict patient cells. As a result, teams have to adjust on the fly, which makes runs harder to compare and adds time, effort, and cost,” she comments.

For good manufacturing practice (GMP) manufacturing, Tran goes on to note that variability drives unreliable yields and cycle times, elevating out-of-specification rates and deviations. “Here again, operators must make more real-time adjustments, straining scheduling, capacity, and logistics,” she says.

Eissa agrees: “Compounding the inherent, unavoidable variability of patient cells during early development stages with avoidable variability from manufacturing processes makes it nearly impossible to distinguish true process signals from noise, leading to parameters that don't hold in GMP and ultimately driving batch failures.”

In addition, supplier lot differences require prequalification/bridging and widen critical quality attribute (CQA) spread, challenging release and regulatory justification, according to Tran.

It is therefore imperative, emphasizes Eissa, to eliminate avoidable variability through chemically defined media and well-characterized processes, so that the unavoidable biological variability from patient material can be isolated and managed on its own terms. “Equally important,” he observes, “is to systematically and progressively characterize patient material variability through GMP manufacturing and across clinical phases, building the knowledge needed to predict its impact at commercial scale and design a process robust enough to succeed across most or the full spectrum of patients it will serve.”

Use a Multi-pronged Approach to Enhance Control of Cellular Variability

To accommodate the variability inherent to patient-derived raw materials, it is necessary to enhance overall process robustness. That can be achieved by, instead of using donor cells, using patient-derived material during process development, according to Bernatchez.“This approach enables early characterization of variability across key process parameters under conditions that reflect the intended clinical starting material,” she explains.

In addition, because not all unit operations are equally sensitive to variability in starting materials, Bernatchez notes that it is important to also systematically identify those most impacted by patient-to-patient heterogeneity so that optimization efforts can be targeted. She highlights optimization of ex vivo T-cell expansion processes because it can partially mitigate deficits in T-cell function that otherwise limit viral transduction efficiency and proliferative capacity.

In this context, Bernatchez says longitudinal data trending from development studies through clinical manufacturing are critical, particularly in cases where development activities relied predominantly on healthy donor material. “Continuity in data analysis enables the early detection of out-of-trend performance and supports timely implementation of corrective process adjustments,” she observes.

More specific steps noted by Eissa that can be taken include the following:

• Use of automated manufacturing and quality control testing, chemically defined media, standardized apheresis handling (collection, transport, timing), and well-characterized unit operations to eliminate avoidable variability and remove confounding factors so patient biology can be studied clearly.
• Profile incoming apheresis material and collate the information as a database progressively across clinical phases, spanning diverse patient populations, disease states, and treatment histories to thoroughly characterize patient material and identify which starting material attributes predict process performance and product quality.
• Integrate electronic batch records and laboratory information management systems for real-time data capture and analysis to further connect process data to starting material attributes and product outcomes.
• Apply multivariate modeling and statistical process control to predict batch performance from incoming material profiles and use a design-of-experiment approach during development to separate patient-driven signals from process noise.
• Collaborate with clinical sites and apheresis centers to create a structured apheresis checklist that captures all relevant starting material attributes at the point of collection and educates clinical staff on what matters and why, flags patients whose material may not meet ideal criteria before manufacturing begins, and provides critical context when process or testing issues arise downstream.

On the latter point, Eissa observes that “even when collection proceeds outside ideal parameters, the checklist creates an early indicator of where the process may struggle, turning what would otherwise be an unexpected deviation into an anticipated and manageable variable.”

With respect to patient material characterization, Eissa believes it should be treated as a core development deliverable. “The knowledge built through clinical phases should make the commercial process predictably robust across the full patient population, not just ideal donors,” he notes.

Minimize Variability in Media and Viral-Vector Raw Materials

While variability in patient-derived cellular starting materials often dominates the discussion of raw material variability in the development of autologous cell therapies, use of serum-containing media formulations and, for adoptive cell therapies that require genetic modification, batch-to-batch variability of viral vectors can exacerbate the challenges posed by the variability of cellular starting materials. Using well-characterized and defined regents can help minimize these issues.¹

For media formulations, variability can, according to Bernatchez, be reduced through the use of chemically defined media supplemented with serum replacement components. “The increasing availability of GMP-grade, chemically defined media may enable greater control and consistency in cell therapy manufacturing processes,” she comments.

When it comes to viral vectors, a key issue can be variably potency due to different concentrations of functional infectious particles from batch to batch. A key objective of process development is, therefore, to define the optimal ratio of viral particles to T cells required to achieve a target transduction efficiency, according to Bernatchez. “Once established using a reference viral-vector lot, it is generally assumed that maintaining a constant particle-to-cell ratio across subsequent lots of the same construct will yield comparable T-cell engineering outcomes,” she explains.

This assumption does not consistently hold, however, because variability introduced during viral vector production and purification can significantly affect particle infectivity and functional potency. “As such,” says Bernatchez, “reliance solely on particle counts or nominal multiplicity of infection may be insufficient to ensure process consistency.”

The development and implementation of advanced analytical methods to more accurately characterize viral vector quality and infectivity are therefore essential. “These approaches enable more robust definition of CQAs and support improved standardization of viral-vector manufacturing processes, ultimately ensuring consistent production of T-cell therapy products that meet predefined specifications,” she concludes.

Decentralized Manufacturing Can Make a Difference

A big change with significant potential to help reduce and manage raw material variability for autologous adoptive cell therapies is to switch from a centralized to a decentralized manufacturing strategy. “Decentralized and point-of-care manufacturing approaches offer the possibility to mitigate risks associated with logistical delays during the transport of patient-derived materials, including starting material (e.g., apheresis products or tumor tissue) and final drug product, that have the potential to adversely affect cell viability and functional quality,” notes Bernatchez.

Cold-chain and logistics variability are real and underappreciated sources of risk, agrees Eissa. However, he emphasizes that decentralized manufacturing only reduces these risks at scale if it involves deployment of a standardized, automated platform consistently across sites. “It is essential to achieve decentralized manufacturing without sacrificing the process consistency that patient outcomes depend on,” he states.

Collaboration with Vendors Is Essential to Success

Vendors have an important role to play in helping to minimize raw material variability. Developers and manufacturer of autologous, adoptive cell therapies therefore have the best chance of managing raw material variability by collaborating closely with vendors, including media suppliers, viral-vector producers, and hospitals and apheresis centers.

In fact, Eissa believes the latter group should be considered as key participants in the first step of the manufacturing process. That means engaging clinical sites early and working to help them understand how apheresis quality impacts manufacturing success and patient outcomes; codeveloping the apheresis checklist mentioned above; providing guidance on patient selection and pre-apheresis conditioning, especially timing relative to prior treatment; and qualifying and auditing apheresis centers as supply chain partners, with periodic retraining and performance trending across sites.

“The earlier clinical sites [and suppliers of media and viral vectors] are engaged as partners with shared accountability, the more predictable and manageable starting material variability becomes,” Eissa concludes.

References

1. Regalo G. From research to reality: how raw materials, media composition and process decisions shape T-cell therapies. RegMedNet, January 13, 2026. Accessed July 7, 2026. https://www.regmednet.com/from-research-to-reality-how-raw-materials-media-composition-and-process-decisions-shape-t-cell-therapies_fujifilm/
2. Life Science Connect Editorial Staff. How to promote batch-to-batch consistency in CAR-T therapies. Cell & Gene. March 18, 2024. Accessed July 7, 2026. https://www.cellandgene.com/doc/how-to-promote-batch-to-batch-consistency-in-car-t-therapies-0001
3. Challener CA. Managing raw material variability for autologous cell therapies. BioPharm International 2023 36 (12), pp. 16-19 . https://www.biopharminternational.com/view/managing-raw-material-variability-for-autologous-cell-therapies

About the Author

Cynthia A. Challener, PhD, is a contributing editor to PharmTech.