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The expectation to apply quality by design (QbD) principles to new manufacturing processes has been voiced by regulatory authorities for over a decade (1, 2). They recognize that because of the generally low patient populations for emerging therapies, such as adeno-associated virus (AAV)-based therapeutics, available chemistry, manufacturing, and controls (CMC) information might not be as exhaustive as for other biologicals such as monoclonal antibodies (3, 4). Other challenges include the need for rapid development to address currently unmet medical needs and the availability of suitable raw materials.
Frameworks regarding CMC requirements for gene therapy applications have been published by the Alliance for Regenerative Medicine (ARM) and the National Institute for Innovation in Manufacturing Biopharmaceuticals (NIIMBL) (5). Pall also has produced a white paper on this subject (6). In that publication, the focus is on manufacturing AAV, outlining key steps for successful development of CMC information.
QbD depends heavily on prior knowledge, risk assessment, and detailed understanding of both product and process variables (1, 2, 7). Even when such information exists, gathering additional prior knowledge and process understanding will help to optimize AAV manufacturing. For addressing unmet medical needs, it is important to generate data, analyze them thoroughly, and interpret all process changes that could potentially affect a product.
The QbD journey starts by defining a quality target product profile (QTPP) based on specifications concerning the safety, purity, and efficacy of the drug product (1). However, for assurance of a product’s QTPP, identification and a deep understanding of critical quality attributes (CQAs) and how a process can affect those (and, ultimately, the QTPP) are essential. CQAs include levels of noninfectious AAVs, empty capsids, aggregated AAVs, and encapsulated host-cell DNA (5, 6).
We recommend a risk assessment following guidelines of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) to determine the criticality of each attribute and its potential impact on process and product (7). Those determinations can be ranked according to the likelihood of an adverse event and its severity to human health. From there, the rankings can distinguish between quality attributes and CQAs. A subset of CQAs is related to product- and process-related impurities and adventitious agents. It is necessary to understand what parameters are associated with process-related impurities because each process step will have its own parameters and multiple variables.
Pall’s white paper, Quality By Design (QbD) for Adeno-Associated Virus (AAV), identifies variables that can affect a CQA significantly. Variables that can be controlled in a manufacturing suite and that can directly affect CQAs are defined as critical process parameters (CPPs). Materials that typically are controlled outside of a manufacturing suite but that could compromise CQAs are considered to be critical material attributes (CMAs) (6).
The design space is defined as “the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality” (1). Therefore, it is critical to achieve a deep understanding of how the CPPs and CMAs interact and affect the CQAs. Generating data as early in process development as possible will enhance understanding of how CMAs specific to raw materials could compromise product quality.
After understanding and identifying the CPPs and CMAs, the next stage is to identify and establish a proven acceptable range (PAR) (1) and a normal operating range (NOR) (8) for each manufacturing step. PARs represent the limits of a process step, whereas NORs often are subsets of the PARs and reflect intended operating parameters. This assessment requires a comprehensive evaluation of a product and process at each stage of manufacturing and becomes a critical consideration when validating a design space for each process step.
Finally, control and testing strategies play an important role in QbD because they ultimately ensure the quality and safety of a final product. However, such strategies depend fully on the product and process parameters that have been developed and must be reevaluated during process scale-up. Testing during manufacturing confirms the suitability of controls and is required for final release of a gene therapy drug product. Additionally, trending process parameters and product quality through monitoring can strengthen reliance on a design space and process control during manufacturing. Such trending supports continued process verification as mandated by regulatory authorities (9, 10).
Despite multiple cell lines and culture types, the upstream production of AAVs is understood relatively well, and the industry is continuing to make great advances in this area. For downstream production, further work is required (e.g., separation of empty and partially full capsids, optimization of final AAV yields, and more robust techniques for removing adventitious agents). Following on the publication of its initial white paper to provide a holistic perspective of CMC requirements for AAV manufacturing, Pall is committed to using QbD principles to evaluate individual processing steps in the manufacture of AAV to facilitate development of CMC information for end users.
References
1 ICH Q8(R2): Pharmaceutical Development. US Fed. Reg. 71(98) 2009: https://database.ich.org/sites/default/files/Q8_R2_Guideline.pdf.
2 ICH Q11: Development and Manufacture of Drug Substances (Chemical and Biotechnological/Biological Entities). US Fed. Reg. 77(224) 2012: 69634–69635; https://database.ich.org/sites/default/files/Q11_Guideline.pdf.
3 Guidance for Industry. Chemistry, Manufacturing, and Control (CMC) Information for Human Gene Therapy Investigational New Drug Applications (INDs). US Food and Drug Administration (FDA) 2020; https://www.fda.gov/regulatory-information/search-fda-guidance-documents/chemistry-manufacturing-and-control-cmc-information-human-gene-therapy-investigational-new-drug.
4 Guideline on Quality, Non-Clinical and Clinical Aspects of Gene Therapy Medicinal Products. European Medicines Agency (EMA) 2019; https://www.ema.europa.eu/en/documents/scientific-guideline/draft-guideline-quality-non-clinical-clinical-requirements-investigational-advanced-therapy_en.pdf.
5 Project A-Gene: A Case Study–Based Approach to Integrating QbD Principles in Gene Therapy CMC Programs. The Alliance for Regenerative Medicine (ARM) and the National Institute for Innovation in Manufacturing Biopharmaceuticals (NIIMBL), 2021; https://alliancerm.org/wp-content/uploads/2021/06/ALL-PROJECT-AGENE-V6-FINAL.pdf.
6 Cashen P, Manser B. Quality by Design (QbD) for Adeno-Associated Virus (AAV). Pall Corporation White Paper, 2021; http://www.qbdpaper.com.
7 ICH Q9: Quality Risk Management. US Fed. Reg. 71(106) 2006: 32105–32106; https://database.ich.org/sites/default/files/Q9_Guideline.pdf.
8 European Medicines Agency. Questions and Answers: Improving the Understanding of NORs, PARs, DSp and Normal Variability of Process Parameters (2017); https://www.ema.europa.eu/en/documents/scientific-guideline/questions-answers-improving-understanding-normal-operating-range-nor-proven-acceptable-range-par_en.pdf.
9 ICH Q10: Pharmaceutical Quality System. US Fed. Reg. 74(66) 2009: 15990–15991; https://database.ich.org/sites/default/files/Q10_Guideline.pdf.
10 Guidance for Industry. Process Validation: General Principles and Practices. US Food and Drug Administration (FDA) 2011; https://www.fda.gov/files/drugs/published/Process-Validation–General-Principles-and-Practices.pdf.
Morven McAlister, PhD, is global senior director of the regulatory and validation consultancy at Pall Corporation; [email protected]. Parth Trivedi is a business development manager at Pall Corporation; [email protected].
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