Cell therapy process control requires a rethink, says expert

Autologous cell therapy production is a challenge and control strategies developed for protein drugs may not work, says an expert.

Gareth Macdonald

December 8, 2020

3 Min Read
Cell therapy process control requires a rethink, says expert
Image: iStock/relif

Autologous cell therapy production is a challenge and control strategies developed for protein drugs may not work, says an expert.

The biopharmaceutical industry has been making therapeutic proteins for forty years. The unit operations and methods are well established and effective. Firms know how to control production to ensure the finished medicine is of appropriate quality.

Industry has less experience making therapies from cells harvested from patients and this is a problem according to Rachel Yost, senior process engineer at Bristol Myers Squibb.

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Image: iStock/relif

She told delegates at the Cell and Gene Therapy Bioprocess and Commercialization virtual event process control techniques developed for protein drug production are not always applicable to cell therapies.

“The cell therapy industry is evolving and we’re continually learning about these products,” she said, adding “The standard approach to development for biologics does not always apply to cell therapy programs.”

Variability

Variability is the major challenge according to Yost, who explained that cells from which therapies are made differ patient to patient and harvest to harvest which makes setting critical quality attributes (CQAs) very difficult.

“For biologics the link between the product and process is typically well defined and CQAs can be well characterized. Whereas in contrast with cell therapy programs – autologous cell therapy programs in particular – patient material is the critical starting material and the biology is complex and variable.

“Therefore the clinical outcomes may vary by patient input and patient population, so preliminary CQAs may be established but the correlation between these products and clinical outcomes are in early stages of understanding.”

Variability also creates other difficulties Yost said. “The starting material being the patient material also complicates process characterization and analytical development as well as comparability, stability and other process validation enabling requirements

Solutions

To address these issues, cell therapy developers need to go back to first principles and identify the parameters needed to develop process control strategies rather than relying on those developed for biologics according to Yost.

“Many traditional control strategies employ three tiers for classification or process parameters where a middle tier is often called a key process parameter, or KPP. KPPs are used to describe parameters that do not impact product quality but may impact process performance, such as yield.

“For an autologous cell therapy products yield relates to the number of cells that are available for dose and this may be more in line with CQA classification as it impacts the patient’s ability to receive product.

“Therefore things that impact yield may be more in line with critical process parameters for autologous cell therapies. This is something to consider for your process parameter classification for your process control strategies as a simple two tier may be more appropriate.

She added that when classifying process attributes many traditional processes use in-process controls (IPCs) to monitor process performance – this a check made during production that may be used to adjust the process if necessary

“Cell therapy processes will probably have IPCs as well but for autologous cell therapy variability in the incoming material often requires the process to read and react to process performance. During control strategy development there may be a need for many of these process control points that allow the process to adapt to the behaviour of the cells.”

Examples of potential IPCs include an adaptive media feed strategy that is based on growth rate Yost said, explaining “Batch to batch growth rate may depend on incoming donor variability and the media seed strategy should have a PCP to adjust for this.

“In conclusion we’re trying to reduce all sources of variability so the process control strategy should be designed to control what we can.”

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