Paola Cecchini

By Paola Cecchini, Ph.D.
Senior Principal Scientist, Analytical Development

 

Robust and reliable potency assays are fundamental to the drug lifecycle and represent a key critical quality attribute. By applying DoE, we efficiently optimize assay conditions, reduce variability, and accelerate development with high scientific confidence.

“Why I like working with Customers? It's truly inspiring to provide CDMO services for our customers’ innovative biologics, and it makes me proud to know I have contributed to the progression of these promising therapeutics.” — Paola

 

Primer: The Importance of Potency Assays for Biologics

Potency assays are a cornerstone of product quality and patient safety. These assays provide a direct measure of a biologic’s functional activity, ensuring that the therapeutic performs as intended.

Potency is recognized as a critical quality attribute (CQA) because it reflects the biological mechanism of action and underpins key decisions throughout the product lifecycle. Whether you're working with monoclonal antibodies, bispecifics, or fusion proteins, well-designed potency assay development is essential for:

  • Measuring biological activity and efficacy
  • Demonstrating the mechanism of action (MoA)
  • Ensuring batch-to-batch consistency
  • Monitoring stability and shelf-life
  • Meeting regulatory expectations and gaining approval
  • Supporting early development and process changes

In summary, potency assays are indispensable tools that guide development, ensure consistency, and safeguard therapeutic performance. They provide the confidence that complex biologics will deliver their intended effect - safely, effectively, and consistently - for every patient, every time.

 

Application of Quality by Design Principles

For my work in potency assay development, we utilize a Quality by Design (QbD) approach that provides a structured, science- and risk-based framework that helps ensure assays are not only robust at launch but remain reliable throughout their lifecycle. Guided by ICH guidelines (Q8–Q10 and Q14), QbD encourages a deep understanding of assay performance and the factors that influence it—right from the start. At its core, QbD for potency assays involves multiple steps:

Defining the Analytical Target Profile (ATP)

This is the “start with the end in mind” step. The ATP outlines the intended purpose of the assay and sets clear performance expectations—such as accuracy, precision, specificity, linearity, robustness, and stability-indicating capability.

Identifying Critical Method Parameters (CMPs)

While potency is a critical quality attribute (CQA) of the drug product, the assay itself has Critical Method Attributes (CMAs)—variables like cell seeding density, incubation time, and temperature — that can significantly impact performance.

Establishing the Method Operable Design Region (MODR)

By evaluating these CMPs through a Design of Experiments (DoE) approach, we define the MODR—a multidimensional "safe zone" where the assay is proven to meet all ATP requirements, ensuring that minor variations in lab conditions do not compromise results.

By applying QbD principles, we move away from reactive, trial-and-error development and toward a proactive, knowledge-driven process. This not only improves assay robustness and reproducibility but also supports method lifecycle management - enabling smoother validation, transfer, and adaptation as products or processes evolve.

In short, Quality by Design (QbD) helps us build in quality from the beginning, ensuring that potency assays consistently deliver fit-for-purpose data across development, commercialization, and beyond.

Figure 1: Quality by Design Approach

 

Design of Experiments for Robust Assay Development

Assay development is a critical process in pharmaceutical and biological research, often dictating the speed and reliability of drug discovery and manufacturing. Traditionally, this process relies on a "one-factor-at-a-time" (OFAT) approach, where one variable is tested while all others are held constant. While simple in concept, OFAT is time-consuming, resource-intensive, and often fails to identify the complex interactions between different parameters that can affect an assay's performance.

Design of Experiments (DoE) offers a smarter, more efficient alternative. By varying multiple factors simultaneously- such as incubation time, temperature, and reagent concentrations - DoE enables a systematic, data-driven exploration of the experimental design space. This approach not only reduces the number of experiments needed but also provides a deeper understanding of how critical method parameters influence key assay attributes like accuracy, precision, and robustness.

In my opinion, the real strength of DoE lies in its ability to define an optimal design space - a robust operating range where the assay performs reliably, even in the face of minor variations that the assay may be exposed to day to day. This proactive approach builds quality into the assay from the start, reducing the need for troubleshooting and re-development later on. As a result, DoE accelerates development timelines, improves reproducibility, and supports long-term method sustainability of cell-based assays.

In short, Design of Experiments (DoE) transforms assay development from a reactive process into a strategic enabler of quality and speed, making it an indispensable tool for modern biopharmaceutical analytics.

 

Demonstrating DoE in Action: Optimizing a T-Cell Activation Bioassay

In the current era of advanced biologics—such as bispecific antibodies and fusion proteins—T-cell activation bioassays have become indispensable tools. These assays not only confirm the intended therapeutic mechanism but also detect potential off-target immune responses, ensuring both the efficacy and safety of these novel immunotherapies.

In one recent example, our team applied QbD and the DoE approaches to rapidly develop and assess the robustness of a T-cell activation bioassay prior to qualification and validation. Using TCR/CD3 Effector Cells (NFAT) and Raji Target cells in culture combined with by Bio-Glo Luciferase assay output, we tested the potency of two Blinatumomab (Blincyto) and Glofitamab (Columvi) , bispecific monoclonal antibodies used in treating B-cell cancers.

We used a split-plot DoE design to evaluate the impact of five intra-assay operating conditions on assay variability. The experiments were conducted in a 384-well plate format using the semi-automated pipetting robot. Remarkably, we were able to show that in a single development run, this structured approach successfully identified the critical method attributes (CMAs) and defined a robust control space for the assay - demonstrating that, when the principles of DoE are applied with a clear understanding of key operational variables, the intended outcomes can be achieved.

By integrating DoE with a 384-well format and semi-automated pipetting, the development process became significantly faster, more reliable, and scalable.

Figure 2: DoE on T-cell Activation Assay. A. DoE dose response curves; B. Defining a robust control space from DoE analysis

 

Conclusion: A Scalable Framework for Potency Assay Success

The combined application of Quality by Design (QbD) and Design of Experiments (DoE) offers a powerful, scalable framework for developing robust potency assays - whether for T-cell activation or other complex cell-based assay (CBA) formats.

What makes this approach especially valuable is its ability to systematically evaluate multiple interacting variables, which are often at the heart of assay variability and performance. This methodology is broadly applicable to a range of CBA formats, including reporter gene assays, cytotoxicity assays, proliferation assays, and receptor signaling assays.

I find DoE fascinating because it reveals the hidden 'why' behind assay performance, turning complex interactions into a clear, visual map. Pairing this with a 384-well format is particularly exciting as it allows me to rapidly define a robust MODR, ensuring the method is fail-proof from the start. For Lonza’s customers, this means moving beyond trial-and-error to a method that is mathematically guaranteed to be reliable and scalable.

By clearly defining performance goals, identifying critical method parameters, and using structured experimentation, our teams can accelerate development, reduce variability, and ensure long-term assay sustainability. Ultimately, this enables faster, more confident decision-making across the lifecycle of biologics - supporting both scientific excellence and patient impact for our customers.

 

About the author:

Paola studied Industrial Biotechnology at University of Padua, Italy. She also has a PhD in Biotechnologies (Immunology) and performed a Post Doc in Protein Chemistry, both at the University of Padua. In 2015, Paola started her career in the UK research industry, working on a new anti-infective HSPs Streptococcus pneumoniae vaccine and the study of its mechanism of action in human cells. After that, her work focused on cell-based assay development, tech transfer, GMP qualification and validation. Paola started working in Lonza in 2021 in the Analytical Development team working on the development, optimization and pre-validation of potency assays. She has been pivotal in implementing the use of Design of Experiment (DoE) for a quicker and most robust development of cell-based potency assay (CBA).

 

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* The presented information was correct and current at the time of publication.
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