Building Cell Therapy the Right Way

The development of robust analytical methods that support process development through commercialization and product release is essential for cell therapy approval. Assay development underpins successful cell therapy programs by enabling accurate and precise assessment of critical process parameters and product quality attributes, ensuring therapeutic product consistency, safety, and effectiveness. With many cell therapy programs receiving expedited approval designations, it can be challenging to meet the need for efficiency and speed early in development while still ensuring analytical robustness.

Building analytical strategies from the outset of a cell therapy development program that are designed to exceed regulatory expectations simplifies decision-making, aligns early development with long-term commercialization goals, and reduces risk. Use of a design-of-experiment (DoE) approach to accelerate development of optimal, robust assays saves time, materials, and money while supporting improved decision-making. Approaching development as a series of milestones and stage gates allows for phase-appropriate analytical control, thereby mitigating quality and compliance risks as cell therapy programs move toward early clinical validation.  

Early investment in analytical development thus enables data-driven process changes and enhances understanding of both processes and products, ultimately guiding cell therapy programs throughout their entire lifecycles.

Benefit from a DoE Approach tO Analytical Method Development

Robust assays are a cornerstone of cell therapy program success across all phases from process development through commercialization and product release, making efficient and effective assay development essential. Achieving accurate and precise assessment of critical process parameters ensures therapeutic product consistency and effectiveness. 

Proper assay development, particularly for complex cell-based assays, can, however, involve significant investment in time and cost, which can be prohibitive for early-phase programs. Using a DoE approach can help minimize that investment by accelerating method development. Rather than exploring one factor at a time, as was traditionally done, DoE studies support the assessment of multiple parameters simultaneously, increasing resource efficiency and effectively reducing the cost and time required for analytical method development. DoE studies also lead to improved decision-making in the development of robust analytical methods for cell therapy programs, which, in turn, enable more-informed decision-making across the overall program.

Given the nature of cell therapies, critical quality attributes (CQAs) include, but are often not limited to, the purity and identity of the cell population (typically determined using flow cytometry). Because many different process parameters (e.g., multiplicity of infection (MOI), a given set of cytokines over a range of concentrations, expansion duration, etc.) can impact these CQAs and often influence one another, ensuring selected parameters support the target product profile (TPP) requires a deep understanding of both the product and process and relevant analysis conditions.

This knowledge is used to establish efficient DoE studies that will, when performed using material from a single donor, provide the data needed to evaluate the impact of multiple process parameters and support method development activities with less upfront experimentation. Large-scale runs using identified, optimized conditions and methods can then be performed with material from numerous donors to confirm the appropriateness of the defined process design space and analytical assays. 

Such an approach minimizes the experimentation, testing, time, and cost needed for both process and method development by reducing the impact of starting material variability while providing the necessary means to measure and understand it. It also results in the determination of an analytical control strategy comprising both release and characterization tests that ensures assessment of important potential changes and supports a robust IND-enabling package.

Reducing Risk Through Analytical Control

Development timelines are shrinking for all cell therapies, and particularly those with accelerated approval designations. Decisions made at the earliest stages of a project, including analytical method and control strategy choices, directly impact the feasibility of scaling to commercial production and lay the foundation for success—or create roadblocks—across the entire development lifecycle. They may also limit the data available to support future process changes, requiring costly comparability studies. 

Risk management should thus begin in early-stage development. Decisions are prioritized by approaching development as a series of milestones and stage gates. Mitigation strategies are then defined a priori as part of the product development lifecycle. This approach supports simplified decision-making, proactive risk management, and alignment of early development with long-term commercialization goals. Overall, risk-based stage gates enable teams to mitigate uncertainties early, optimize processes and analytical methods for scalability, and maintain regulatory compliance—all while keeping commercialization in focus.

Specifically, considering analytical methods, they should be optimized with every clinical batch to enhance understanding and product quality. Tests should therefore be refined, aligned with CQAs and critical process parameters (CPPs), and prepared for method validation in accordance with ICH guidelines. Meeting these milestones ensures the development of an adequate control strategy, thereby assuring product safety and efficacy and avoiding delays in product approval.

Using a phase-appropriate analytical control strategy, meanwhile, is essential for mitigating quality and compliance risks as cell therapy programs move toward early clinical validation. It allows developers to ensure product quality, begin understanding inevitable patient variability within a trial’s overall scheme, and establish an early path into the clinical trial setting.  

Furthermore, reliable analytics, coupled with a well-thought-out retention strategy, help define and enable the process changes needed to support later-stage clinical studies without significantly slowing overall development of a cell therapy program. As processes mature, analytical and characterization insights will efficiently guide the effort, making comparability studies much easier, more efficient, and more interpretable.

Accelerate the Path to IND with Early Investment in Analytics

Phase-appropriate method development, however, does not mean taking shortcuts. Early decisions—such as selecting raw materials, designing robust processes, and prioritizing analytical development—therefore shape the success of a product’s journey from research to commercialization. Well-constructed analytics are the foundation for any cell therapy program, as without trustworthy data, informed, defensible process changes cannot be made. Under the pressure of expedited timelines and tight budgets, however, deferring the implementation of system-suitability controls and method qualification often occurs, leading to the generation of unreliable data.

When analytics are unreliable, decisions lack a solid foundation, increasing the likelihood of optimizing for inappropriate endpoints or critical quality attributes. Because timely and robust process characterization is a critical foundation for meeting regulatory and safety requirements for commercialization, failing to thoroughly characterize a cell therapy process early sets off a chain reaction of technical and regulatory difficulties that are challenging to rectify. Without data-driven insight into how each unit operation behaves, critical parameters drift from loosely defined values in the lab to poorly controlled targets in GMP production. Unfortunately, repercussions generally grow with scale, such as quality teams being unable to defend product-release criteria.

The disconnect between early development and commercial requirements can jeopardize promising therapies without early alignment, necessitating costly, time-consuming method redevelopment, comparability studies, and IND revisions. The tension between speed and analytical robustness, in fact, sits at the heart of many Complete Response Letters (CRLs) that have recently delayed some cell therapies from reaching the market.

Investing early in robust analytical methods and a clear CMC roadmap enables teams to anticipate and mitigate risks while allowing for flexibility as knowledge deepens. Generation of the meaningful data needed to enable process characterization can, in fact, only be achieved by investing early in analytical development. This approach also avoids weaknesses in assay qualification, such as a lack of specificity, concerns about reproducibility, and poorly defined acceptance criteria, all of which are frequent sources of regulatory questions and clinical delays. As a result, early investment in robust analytical methods minimizes uncertainty and builds a foundation for scalability and product consistency.

For instance, early development release assays designed to establish identity, purity, potency, and safety are often insufficient to ensure a complete understanding of the product. It is therefore important to invest in characterization assays designed to interrogate additional aspects of the product. These assays include assessments of phenotype, metabolomics, transcriptomics, additional potency assays, and other product-specific assays.

These assays do not have specifications and, in addition to being used to increase product knowledge, may be employed to introduce new technology or testing techniques, confirm observations via parallel testing routes, or address stability concerns or other product-specific questions. They may eventually replace release tests as they are developed over time and elevated from characterization to release tests once data are compiled and specifications can be determined.

Indeed, refining analytical control strategies by tightening specifications and elevating critical characterization assays to release tests as data accumulates ensures consistent product quality. Specific actions include:

• Tightening test specifications as data on method performance and manufacturing history grows.
• Elevating informative characterization tests to release tests.
• Establishing reference standards for commercial production.
• Optimizing methods for the long-term analytical control strategy.
• Developing a coherent potency assurance strategy in line with FDA guidance.
• Preparing for method validation, conducted per ICH guidelines (e.g., ICH Q2R2).

Science-First Cell Therapy Development

Risk management in cell therapy development is about avoiding setbacks and creating the best possible foundation for success. A well-thought-out analytical strategy is one essential component for meeting rapidly evolving regulatory expectations and ensuring programs advance to commercialization. By leveraging early investment in analytics alongside a DoE approach, stage gates, and expert resources, innovators can confidently navigate the complexities of process and analytical method development and deliver high-quality, transformative therapies that improve patient outcomes globally. Working collaboratively, trusted contract development and manufacturing organization (CDMO) partners can support these efforts by reducing risk and creating a smoother path to commercialization.

Kincell Bio applies a science-first approach to analytical development, helping cell therapy developers establish robust testing strategies that support process understanding, product characterization, and regulatory readiness throughout clinical development. Our early-stage analytical strategies include:

• System-suitability controls and method qualification, avoiding future assay redesign and method comparability studies due to unreliable data generated from suboptimal analytical methods.
• Emphasis on precision and accuracy, particularly for methods such as cell count and viability, as this foundation supports dose escalation studies. 
• Building potency and characterization matrices aligned with the mechanism of action to connect quality with biology, account for variability, support comparability, and correlate with outcomes, guiding development decisions and building regulatory confidence for IND submissions.
• For allogeneic programs, donor qualification and correlation of donor attributes with potency and clinical outcomes.
• Understanding of the uniqueness of each cell therapy and the implications for model fitting/assay development.

By investing early in analytical development, Kincell Bio establishes testing solutions that support enhanced process and product understanding, enabling cell therapy programs to be guided throughout their entire life cycles. Using a DoE approach accelerates the development of optimal, robust assays, saving time, materials, and money while supporting improved decision-making. Using a stage-gate approach, meanwhile, allows for phase-appropriate analytical control, thereby mitigating quality and compliance risks as cell therapy programs move toward early clinical validation. Indeed, the analytical methods we develop enable accurate, precise assessment of CPPs and product CQAs, and they evolve with our clients’ programs, streamlining the development process while ensuring the safety, potency, and consistency of their drug substances and drug products.

Roger Herr leads analytical development at Kincell Bio, supporting scalable assay strategies for cell therapy programs from early development through commercialization. He previously held leadership roles at several biologics-focused organizations and has extensive experience in analytical development and assay design.

Patrick Kellish, Ph.D. is a Senior Scientist in Analytical Development at Kincell Bio, supporting analytical activities across cell therapy development and manufacturing. His work focuses on assays for cell identity, potency, safety, and product characterization.