Quality by design (QbD) in bio manufacturing

Concept of Quality by design (QbD) in bio manufacturing

Quality by design (QbD) is the standard approach used for demonstrating and achieving consistent, high quality product. Rather than relying on just the post production testing, QbD practice rather encourages to improve quality at every stage of the process, from project inception to commercialization of the product. QbD facilitates amplification of the quality into the product. US FDAhas acknowledged the fact that testing does not always result in higher product quality. Encouraging to have one of the main goal in manufacturing as product by quality using QbD approach, ICH has introduced it in the documentations ICH Q8 (R2), Q9, Q10 & Q11 with ICH Q8/Q9/Q10 Questions & Answers along with additional ICH Q1 WG (emphasizing on the product specifications). In order to implement the QbD proposed in the documents, initially few objective were laid which are as follows:

1) To achieve clinical performance based product quality

2) To improve process design in order to reduce product variability

3) To boost product development progress & manufacturing efficiency

4) More effective root cause analysis (RCA) & post-approval change management

For proper implementation of these objectives, it is crucial to get a grip of the elements of the QbD. In the pharmaceutical industry's QbD approach to product development, a candidate identifies patient-centered traits deemed crucial to quality, transforms them into drug product critical quality attributes (CQAs), and alongside determines an association between formulation/manufacturing variables and CQAs to safely provide a drug product with such CQAs to the patient. The elements of QbD are outlined below:

1) A quality target product profile (QTPP) that lists the pharma product's CQAs

2) Understanding and designing products, including identifying critical material attributes (CMAs)

3) Understanding and designing processes, particularly identifying critical process parameters (CPPs), fully grasping scale-up principles, and connecting critical material attributes (CMAs), CPPs,and CQAs

4) A control plan with requirements for the drug substance(s), excipient(s), and drug product as well as controls for each stage of production

5) Process capabilities and continuous improvement

QTPP is the foundation of quality by design (QbD), ensuring that drug products are consistently manufactured to the desired quality, safety, and efficacy. It defines the critical quality attributes (CQAs) of the drug product, which are the physical, chemical, biological, or microbiological properties or characteristics that should be within an appropriate limit, range, or distribution to ensure the desired product quality. The QTPP also identifies the critical process parameters (CPPs) that control these attributes. By understanding the relationship between CQAs, CPPs, container closing systems, pharmacokinetics and patients outcomes, companies can identify and mitigate potential problems early on, which can save time and money also that this can help to improve the efficiency and effectiveness of product development and manufacturing. These are therefore considered essential elements of QTPP.[1]

For example, the QTPP for a new ibuprofen tablet formulation might identify dissolution, purity, and stability as CQAs identifier. Also the manufacturing process for the ibuprofen tablet formulation might be designed to control the particle size and distribution of the ibuprofen powder, which are CPPs that affect the dissolution of the tablet and using in-process testing to ensure that the dissolution rate of the tablets meets the QTPP specification.

ICH Q8 (R2) provides us the guidance to the product design which tells us if the product is capable to meet patients' needs and requires data support from the clinical trials. Furthermore the product should remain effective for certain shelf life so the stability studies is other essential aspect of the product design. At product design stage the key focus revolves around the characterization of the drug product, interactions of drug & excipient, optimization of the formulation and establishing the CMA. It is impractical for a formulation scientist to look into every material feature found during formulation optimization studies because there are numerous characteristics of the drug substance and excipients that could potentially affect the CQAs of the intermediates and final therapeutic product. A risk assessment would therefore be helpful in determining which material features are most important to investigate further. Risk assessments leads to refining of the design space. Refining design space is one of the conclusions using QbD in pharmaceutical manufacturing landscapes. There are other factors too that drives the design space such as comparability exercises, process development, process analytical, technologies advancement, increased product knowledge from clinical and non-clinical research. Refining of design space requires huge investments. Therefore it is important using small-scale models and techniques like Design of experiment DOE, a risk assessment should be carried out to determine which process parameters need to be reevaluated in light of their possible impact on essential quality attributes. This need has led to the establishment of the process analytical technology (PAT)team for real time release testing, they follows the guidelines of regulatory bodies and are responsible to develops a system of controlling and manufacturing through timely measurement of the CQAs in the end to end process of manufacturing drug product. They also reviews the implication of QbD before the final submission for evaluation by the respective regulatory bodies.[2]

Understanding of the product design along with design space involves strategies & ways to establish relationship between inputs as CMAs and CCPs and output as CQAs. It is crucial to know the process parameters and use risk assessments backed with scientific knowledge to reach out the potentially high-risk parameter. It is important then to establish the levels of the high-risk parameters using the DOE and analyses the experimental data to confirm the parameter as critical, a step towards founding the first principle model with scalability of the quality product. This point is where the CMAs & CCPs links to the COAs. Process design or design space concept is also applied at this point for the cases where there are more parameters or material attributes are involved.

The set of controls utilized to maintain the CMAs and process parameters within the design space is known as the control strategy for the drug product. The design space and the risk assessment procedure serve as the foundation for the control approach. Equipment certification, environmental monitoring, and in-process testing are common controls for manufacture. Going deeper, there are levels of the control strategy whereby level 1 applies the automatic engineering to monitor the COAs like adoption of the real time testing by the PAT team for improvising the quality assurance is not the only way to the level of control. Level 2 has pharmaceutical controls with reduced end product testing and flexible material attributes. So by reducing the dependence on end-product testing and moving controls upstream are made possible by an understanding of the effects that variability has on inprocess materials, downstream processing, and drug product quality. The pharmaceutical sector has historically employed Level 3 of control. This control technique depends on closely controlled material qualities and process parameters as well as comprehensive end-product testing. Any meaningful change in these necessitates regulatory control because the sources of variability have not been well characterized and the effect of CMAs and CPPs on the CQAs of drug products has not been fully understood. Actually, a hybrid strategy that combines levels 1 and 2 may be applied. A control strategy is defined by ICH Q8 (R2) as a planned collection of controls that guarantee process performance and product quality. These controls are resulting from current product and process information. Why do we have the need for control strategy? Since variability is evident dues to the fact that in product development and in process manufacturing there exists various parameters or attributes related to the drug product. Regarding the specified acceptance criteria, the process capability that involves continuous verification, process changes and comparability helps in quantifying the intrinsic variability of a stable process in a statistically controlled state, ultimately establishes the comparability protocols (CPs) and expanded change controls. Understanding of the product and process acquired throughout pharmaceutical development should enable early detection and mitigation of potential sources of common cause variation in a QbD development process through the implementation of a control strategy as much as possible. When a root cause analysis is necessary, common cause variation is more likely to be found during commercial production in a non-QbD approach. This could disrupt commercial production and result in a scarcity of drugs. Lastly, Continuous improvement (CI) is applied where there is a need to enhance products abilities to meet the requirements. QbD is applied to CI in the following ways:

1. Process monitoring and evaluation

2. Root cause analysis

3. Change management CMAs Product Design Material attributes CQAs QbD (QTPP) Design Space & Control Strategy CPPs Process Design Process parameters Process Capabilities & Continuous improvement

Figure above is a flowchart representing as QbD is applied on establishing ideal QTPP having the CMAs, CPPs as input to customize the CQAs as output with a direct influence on the Design space and the control plan that ultimately give space to analyze the process capabilities and further need for the continuous improvement as crucial part in the lifecycle of a drug product.

Continuous improvement has five phase categories as first with defining of the project goal (sets the stage for improvement process), key aspects of the product related to current process and collect relevant data, investigate the RCA by determining the relationship to ensure that all factors has been considered, based on the RCA analysis create new process with improvised current process using DOE and finally establish the control for the new state of process.[3]

For example, a batch technique is being used by a biomanufacturer to produce a monoclonal antibody (mAb). Impurities in the finished product are causing a high percentage of product rejection for the producer. The manufacturer looks into the problem's underlying cause using QbD concepts. The following key process parameters (CPPs) are noted by the manufacturer: a) Meals A load density column b) Buffer for elution pH and c) flow rate. The firm runs tests to find out how these CPPs affect the amount of impurities in the finished product. The manufacturer discovers that when the pH of the elution buffer is low and the load density of the protein A column is high, the impurity levels are at their maximum. The following corrective measures are carried out by the manufacturer: a) Diminish the protein A load density column and b) Elevate the pH of the elution buffer. To make sure the CPPs stay inside the design space, the manufacturer additionally employs a control technique. The elution buffer pH and the protein A column load density are continuously monitored by the manufacturer, who makes any necessary modifications. These corrective measures have resulted in a significant decrease in the rate of product rejection owing to contaminants. The producer may now create mAbs with excellent yield and purity. This illustration demonstrates how QbD can be applied to bio manufacturing to achieve ongoing improvement. Bio manufacturers can find and fix the underlying causes of production issues by applying QbD concepts. Significant gains in product quality, yield, and efficiency may result from this.[4]

In conclusion, QbD is a systematic approach to product development and manufacturing that emphasizes understanding and controlling product quality throughout the product lifecycle. It promotes innovation, continuous improvement, and regulatory flexibility while ensuring consistent product quality and patient safety. QbD is particularly important for biologics, as they are complex products with a high degree of variability. QbD can help bio manufacturers to design and implement robust manufacturing processes that produce high-quality products. As well the chemistry, manufacturing, and controls (CMC) examination of abbreviated new drug applications (ANDAs) will be transformed into a science-based pharmaceutical quality assessment with the help of QbD implementation. It is held to be fruitful to keep encouraging regulators and industry to work together to clarify the concepts and implementation of QbD for drug products.[5]

References:

1. Rathore, A., Winkle, H. Quality by design for biopharmaceuticals. Nat Biotechnol 27, 26–34 (2009). https://doi.org/10.1038/nbt0109-26

2. Quality by design, European Medicine agency Sep 30 2023 URL: https://www.ema.europa.eu/en/human-regulatory/research-development/quality-design#section2

3. Yu LX et.al. Understanding pharmaceutical quality by design. AAPS J. 2014 Jul;16(4):771-83. doi: 10.1208/s12248-014-9598-3. Epub 2014 May 23. PMID: 24854893; PMCID: PMC4070262.

4. Red Rock BioProcess Consulting Co Sep 08 2023, Medium Sep 30 2023 URL: https://medium.com/@RR-BPC/quality-by-design-qbd-in-biomanufacturing-a-personal-journey86239c12601a

5. Sally Anliker et. al. Quality by Design for Biotechnology Products—Part 3 BioPharm International, BioPharm International-01-01-2010, Volume 23, Issue 1 Pages: 40–45

About the Author:

Shruti Talashi

Ms. Shruti  Talashi  boasts a dual mastery of lab research and writing. Her doctoral study outcome as M.Phil in biomedical science while studying breast cancer and an extraordinary masters degrees dissertation work on exploring role of Gal-lectin in cancer metastasis fuels her extensive research interests. She has gained few publication in journals. Bridging the science-public gap is her passion, aided by expertise in diverse techniques. From oncology to antibiotic/drugs production, she's led and managed complex projects, even clinical trials. Now, as a freelance Content Coordinator for Sinoexpo Pharmasource.com, her industry knowledge shines through valuable insights on cutting-edge topics like GMP, QbD, and biofoundry.