a mab case study

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Quality by design (QbD) encourages the pharmaceutical industry to use risk management and science-based manufacturing principles to gain process and product understanding and thus assures quality of the product. With the objective to curb the rising costs for development and regulatory barriers to innovation and creativity, QbD is being widely promoted by Food and Drug Administration (FDA) and International Conference on Harmonization (ICH). Areas covered: This review describes the elements, different design and tools of QbD as well as multidimensional applications of QbD ranging from dosage form and method development to meeting latest regulatory requirements. Expert opinion: The understanding of a process is facilitated by proper identification of sources of variation, management of variability by process design, and prediction of product quality attributes using design space. The pharmaceutical industry is rapidly adopting the QbD principles for fabrication of safe, effective and...

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DOI: 10.21276/sajp.2018.7.6.8 Abstract: This article describes the concept of pharmaceutical Quality by Design (QbD) and how it can be used to ensure pharmaceutical quality. QbD is a significant part of the present-day approach to improving pharmaceutical quality. It can be described as a novel approach to development of any product which may increase efficiencies, offer regulatory relief and pliability, and also provide business advantages throughout the product lifecycle. In the present review, basics of QbD along with its regulatory needs are discussed. For the detailed explanation of how QbD ensures the drug product quality, several documents from ICH such as ICH Q8, i.e. Pharmaceutical development; ICH Q9, i.e. Quality Risk Management; ICH Q10, i.e. Pharmaceutical Quality Systems and FDA’s Process Analytical Technology (PAT) were referred. By using QbD, formulation and manufacturing variables can be appropriately understood and controlled.

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The application of quality by design (QbD) in pharmaceutical product development is now a thrust area for the regulatory authorities and the pharmaceutical industry. International Conference on Harmonization and United States Food and Drug Administration (USFDA) emphasized the principles and applications of QbD in pharmaceutical development in their guidance for the industry. QbD attributes are addressed in question-based review, developed by USFDA for chemistry, manufacturing, and controls section of abbreviated new drug applications. QbD principles, when implemented, lead to a successful product development, subsequent prompt regulatory approval, reduce exhaustive validation burden, and significantly reduce post-approval changes. The key elements of QbD viz., target product quality profile, critical quality attributes, risk assessments, design space, control strategy, product lifecycle management, and continual improvement are discussed to understand the performance of dosage form...

The use of a Quality by Design (QbD) approach in the development of pharmaceutical products is known to bring many advantages to the table, such as increased product and process knowledge, robust manufacturing processes, and regulatory flexibility regarding changes during the commercial phase. However, many companies still adhere to a more traditional pharmaceutical process development—in some cases due to the difficulty of going from a theoretical view of QbD to its actual application. This article presents a real-world case study for the development of an industrial pharmaceutical drug product (oral solid dosage form) using the QbD methodology, demonstrating the activities involved and the gains in obtaining systematic process and product knowledge.

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This review further clarifies the concept of pharmaceutical quality by design (QbD) and describes its objectives. QbD elements include the following: (1) a quality target product profile (QTPP) that identifies the critical quality attributes (CQAs) of the drug product; (2) product design and understanding including identification of critical material attributes (CMAs); (3) process design and understanding including identification of critical process parameters (CPPs), linking CMAs and CPPs to CQAs; (4) a control strategy that includes specifications for the drug substance(s), excipient(s), and drug product as well as controls for each step of the manufacturing process; and (5) process capability and continual improvement. QbD tools and studies include prior knowledge, risk assessment, mechanistic models, design of experiments (DoE) and data analysis, and process analytical technology (PAT). As the pharmaceutical industry moves toward the implementation of pharmaceutical QbD, a commo...

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Quality by Design A-MAb Case Study Challenges Conventional Thinking

When the CMC Biotech Working Group began developing a case study on applying Quality by Design (QbD) to biotech products, the goal was to challenge conventional thinking on the subject.

When the CMC Biotech Working Group began developing a case study on applying Quality by Design (QbD) to biotech products, the goal was to challenge conventional thinking on the subject. “If the regulatory authorities read our final document and said ‘yes, this is all fine,’ we will have failed,” said Ken Seamon, PhD, one of the project’s facilitators. Now that the project has been completed, John Berridge, PhD, another one of the working group’s three facilitators, thinks they achieved that goal. “When people read it, they will find areas that they agree with, and almost certainly find other areas where they don’t,” he said. “It’s an aspirational document.” The case study, which discusses a fictional monoclonal antibody product, referred to as “A-MAb,” was developed over the course of a year by participants of the working group representing Abbott, Amgen, Genentech, GlaxoSmithKline, Eli Lilly, MedImmune, and Pfizer. Two examples of where the case study challenged conventional thinking, Berridge said, related to scale and change management. Scale-Down Models The limits of the design space for the 15,000-L production bioreactor step were largely based on data derived using a 2-L scale-down model, built on extensive development and manufacturing data (at both the 2-L and 15,000-L scales) for a previous approved product, “X-MAb”. To demonstrate that the 2-L scale-down model was representative and predictive of large-scale manufacturing performance, the team developed a principal component analysis (PCA) model. PCA transforms a large number of possibly correlated variables into a smaller number of uncorrelated variables, called principal components, and analyzes the variability in the data. The analysis included 13 variables, such as peak viable cell density, final viability, pH, glucose, lactate, and peak lactate, and a high degree of correlation was seen in the data sets for the different scales. Also, a complete comparability analysis for the product was made at the 500, 1,000-, 5,000- and 15,000-L scales, and an “engineering design space” was developed for the bioreactor design. The result, the report says, supported the use of the scale-down model. Lifecycle Approach to Process Validation The report also recommends a validation strategy that “relies more on the continuous process verification rather than a minimum number of ‘validation batches’ typically practised.” For the bioreactor operation, the validation strategy involved just two batches at the 15,000-L scale to confirm that the process performance at the 15,000-L scale was within the model predictions. These two batches are seen as “the start of the continuous process verification process” and a lifecycle approach to validation. To provide continued assurance that the process would remain in a state of control throughout the life of commercial manufacturing, the team would create a multivariate statistical partial least squares (PLS) model, which would ensure that internal correlations among variables is also considered. “For example, if at any given time the titer is lower than expected for the measured variable cell concentration, the PCA model will be able to detect this as a potential out of normal signal, even if both parameters are within their respective univariate ranges,” the report says. In this way, the PCA model can detect a large number of potential shifts, trends, and excursions that would not be detected by univariate monitoring tools. Scale-up From 15K to 25K Considered Within the Design Space The report also anticipated that the A-MAb bioreactor process would be scaled up further, to the 25,000-L scale. For the case study, it was assumed that the 25,000-L plant had an extensive and proven commercial manufacturing record of cGMP compliance and MAb production. Based on bioreactor design and engineering parameter characterization, the 25,000-L bioreactors were considered to be within the engineering design space, thus providing a very high degree of assurance that operation at this scale will result in comparable process performance and product quality. “Thus, the scale-up to the 25,000-L bioreactor is considered a movement within the engineering design space,” the report says. If a change to a different bioreactor (e.g., one with a different impeller design or geometry) were considered, the report says that an assessment would be made to determine if the bioreactor characteristics fell within the engineering design space. If they did not, then equipment modifications or changes in operational parameters would be considered to bring the bioreactor operation within the approved engineering design space. Highlights and Workshops The best way to read the 278-page report, Berridge says, is to start with the introduction and chapter 2, then move to the highlighted information that appears in blue boxes throughout the report. “If the information in a particular blue box is of interest, you can read the surrounding details,” he says, “If not, you can go to the next chapter.” In addition, members of the working group will participate in various public workshops hosted by ISPE and CASSS, who have been designated as the primary facilitators of education related to the case study. Sessions will be held during three 2010 CASSS events, including the Well Characterized Biological Products (WCBP) conference in Washington, DC, in January, the CMC Strategy Forum Europe in Vienna, in April, and the CMC Strategy Forum in Bethesda, MD, in July. Workshops also will be incorporated into already scheduled ISPE 2010 meetings, in Milan in March, Tokyo in April, Washington, DC, in June, and Brussels in September. The entire case study can be found on the CASSS (www.casss.org) and ISPE (www.ispe.org) web sites. Previous coverage: QbD Case Study Will Push Limits http://biopharminternational.findpharma.com/biopharm/News/QbD-Case-Study-Will-Push-Limits/ArticleStandard/Article/detail/592288?ref=25

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Case Study CMC-Biotech Working Group 2009 A-Mab: A Case Study in Bioprocess Development Study Guide

Related Files

Micro scale self-interaction chromatography of proteins: A mAb case-study

Affiliations.

• 1 Surfaces and Particle Engineering Laboratory, Department of Chemical Engineering, Imperial College London, London, United Kingdom.
• 2 Surfaces and Particle Engineering Laboratory, Department of Chemical Engineering, Imperial College London, London, United Kingdom. Electronic address: [email protected].
• 3 R&D Group, FUJIFILM Diosynth Biotechnologies, Billingham, United Kingdom.
• PMID: 26810801
• DOI: 10.1016/j.chroma.2015.12.034

Self-interaction chromatography is known to be a fast, automated and promising experimental technique for determination of B22, but with the primary disadvantage of needing a significant amount of protein (>50 mg). This requirement compromises its usage as a technique for the early screening of new biotherapeutic candidates. A new scaled down SIC method has been evaluated here using a number of micro LC columns of different diameters and lengths, using typically 10 times less stationary phase than traditional SIC. Scale-down was successfully accomplished using these micro-columns, where the SIC results for a range of differing columns sizes were in agreement, as reflected by k', B22 and column volumes data. The results reported here demonstrate that a scaled down version of SIC can be easily implemented using conventional liquid chromatography system where the final amount of mAbs used was 10 times less than required by conventional SIC methodologies.

Keywords: Formulation; Monoclonal antibodies; Protein stability; Scale-down; Second virial coefficient; Self-interaction chromatography.

Copyright © 2016. Published by Elsevier B.V.

Publication types

• Research Support, Non-U.S. Gov't
• Antibodies, Monoclonal / chemistry*
• Chromatography, Liquid / instrumentation
• Chromatography, Liquid / methods*
• Muramidase / chemistry*
• Antibodies, Monoclonal

Grants and funding

• Biotechnology and Biological Sciences Research Council/United Kingdom