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Anurag S. Rathore is a professor in the Department of Chemical Engineering at the Indian Institute of Technology Delhi, Tel. +91.9650770650, firstname.lastname@example.org.
The author provides an overview of QbD implmentation for biopharmaceuticals.
Quality by design (QbD) began to gain momentum in the biotechnology industry after FDA published its process analytical technology (PAT) guidance, PAT—A Framework for Innovative Pharmaceutical Manufacturing and Quality Assurance in 2004 (1). Global acceptance of QbD and PAT principles are reflected in the contents of the International Conference on Harmonization (ICH) quality guidelines: ICH Q8 Pharmaceutical Development, ICH Q9 Quality Risk Management, and ICH Q10 Pharmaceutical Quality System (2–4). During the past seven years, industry and regulators have devoted significant resources to elucidate a path forward for implementing QbD in the drug-manufacturing environment and toward resolving the various challenges tied to successful implementation (5–8). To date, the first biotech drug application using a QbD approach has yet to be approved by FDA. Still, QbD principles are already being adopted widely throughout the biotechnology industry. This article provides an overview of QbD implementation for the development and commercialization of biologics and follow-on biologics.
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QbD's beginnings and cost of implementation
In the traditional approach to biotechnology production, manufacturers define a process and aim to perform the process consistently in a manner that the critical parameters are controlled within a narrow range so as to reduce variability in product quality. This approach has been successfully used to make safe and efficacious biotechnology products for the past few decades. However, because the process controls are fixed in this approach, any variability in raw materials, environmental controls, and/or process operations manifests as variability in product quality and results in lot failures (6–7).
ICH Q8 defines QbD as "a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management" (2). Figure 1 illustrates a roadmap for QbD implementation and outlines the key steps that need to be taken to successfully implement QbD for a biologic drug (5-8).
Figure 1: Illustration of key steps in implementation of QbD for a biotech product. Risk assessment and management, raw-material management, and statistical approaches are some of the elements that provide foundational support to the implementation (Ref. 5).
The current environment, where the cost of healthcare has been recognized to be spiraling out of control, has forced biotechnology companies to become sensitive to the cost of manufacturing their products. It is not surprising then, that when the discussions around QbD first started, cost of implementation was highlighted as a major concern. Today, industry has realized that the benefits of QbD implementation outweigh the startup costs. The biotechnology industry does hope, however, that the approaches taken today to generate the required product and process information, will become more efficient and cost effective.
As demonstrated in Figure 2, the market for these products is expected to pick up in 2012 as a significant number of innovator product patents expire through the year 2017. Expected expiries include Enbrel, Neulasta, Herceptin, Lantus, and Rituxan/Mab Thera. In Europe, a regulatory pathway already exists for follow-on biologics, and 14 such products have been approved (Abseamed, Binocrit, Biograstim, Epoetin-a hexal, Filgrastim hexal, Filgrastim ratiopharm, Nivestim, Omnitrope, Ratiograstim, Retacrit, Silapo, Tevagrastim, Valtropin and Zarzio) (9). A pathway, although approved, is still pending implementation in the United States. Established generic-drug companies, such as Teva Pharmceuticals and Sandoz, are expected to continue to play significant role in development and commercialization of follow-on biologics. At the same time, ewer players based in India and China are expected to emerge as potential follow-on manufacturers. It remains to be seen how companies in less-developed parts of the world will manage the high-cost dynamics of manufacturing these products.
Figure 2: Upcoming patent expirations of 10 top-selling biopharmaceutical products (Data based on Ref. 9).
QbD's future in biologics
Looking ahead, certain technologies and processes will need to be refined for QbD implementation in the biopharmaceutical industry (10).
High-throughput approaches. As noted, QbD implementation requires extensive process and product knowledge (6, 7). Acquiring this level of understanding requires extensive experimentation. In the current environment, where cost needs to be controlled, use of high-throughput tools and approaches has emerged as a means of saving considerable costs on needed chemicals, feed material, product, equipment, and most importantly, staff (11). There is a strong likelihood that widespread use of high-throughput tools and approaches will dramatically change how the biotech industry performs the various activities required for product and process development and commercialization in the next decade.
Nonclinical studies as predictors of safety and/or efficacy. Industry at present relies heavily on clinical studies to assess drug safety and efficacy. Although advances have been made in the past decade with regard to industry's ability to model safety and/or efficacy through nonclinical studies, more is needed to reduce reliance on human clinical trials (10). Developments in the way drugs are discovered and in molecular design are expected.
Use of statistical approaches and risk management. QbD implementation requires extensive information about the product and its manufacturing process. However, in view of the large number of variables and attributes that interplay to impact safety and efficacy of a biotechnology product, it is not possible to evaluate the effect of every variable. Statistical approaches, such as design of experiments (DOE) and multivariate data analysis (MVDA), along with risk management tools such as the Failure Modes and Effects and Analysis (FMEA), can help to ensure that resources are spent on the most important tasks.
Global adoption. Thus far, QbD implementation has been limited to large and mid-size biotechnology companies in the US and the Europe. As manufactures based in India and China start producing follow-on biologics for the European and the US markets, they too will start imbibing QbD principles. Some of these companies have already started this alignment. In the near future, the biotechnology industry is likely to see a major overhaul of scientific and quality-based manufacturing approaches as well as a more global adoption of QbD principles.
The economics of developing and commercializing follow-on biologics, in particular in Asia, necessitate that manufacturers cannot merely replicate process and product development practices that have been established at US and European manufacturers. The raised expectations of the regulatory agencies, as represented by the PAT and ICH guidelines, will need to be met. For QbD implementation, the next decade is likely to witness an evolution into a more cost-efficient approach, driven by innovation in the areas mentioned herein and beyond.
Anurag S. Rathore is a faculty member in the Department of Chemical Engineering at the Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India, +91 96 5077 0650, email@example.com.
1. FDA, Guidance for Industry: PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance (Rockville, MD, September, 2004.
2. ICH, Q8 Pharmaceutical Development (Geneva, November, 2007).
3. ICH, Q9 Quality Risk Management (Geneva, June 2006).
4. ICH, Q10 Pharmaceutical Quality Systems (Geneva, September, 2006).
5. A.S. Rathore, Pharm. Technol. Eur. 22 (2) 2010.
6. A.S. Rathore and H. Winkle, Nature Biotechnol. 27, 26-34 (2009).
7. S. Kozlowski and P. Swann, "Considerations for Biotechnology Product Quality by Design," in Quality by Design for Biopharmaceuticals: Perspectives and Case Studies, Eds. A.S. Rathore and R. Mhatre (Wiley Interscience 2009), pp. 9-30.
8. A.S. Rathore, Trends in Biotechnol. 27 (2009), 546–553.
9. G. Walsh, Nature Biotechnol. 28 (2010), 917–924.
10. A.S. Rathore, Trends in Biotechnol. 27 (2009), 698–705.
11. R. Bhambure, K. Kumar, and A. S. Rathore, Trends in Biotechnol. 27 (2010), doi:10.1016/j.tibtech.2010.12.001.