Quality by Design: Industrial Case Studies on Defining and Implementing Design Space for Pharmaceutical Processes—Part 1 - How to use multivariate experiments to define acceptable ranges. - BioP

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Quality by Design: Industrial Case Studies on Defining and Implementing Design Space for Pharmaceutical Processes—Part 1
How to use multivariate experiments to define acceptable ranges.


BioPharm International
Volume 21, Issue 12

ABSTRACT
A key challenge in successfully implementing Quality by Design (QbD) is achieving a thorough understanding of the product and the process. This knowledge base must include understanding the variability in raw materials, the relationship between the process and the critical quality attributes (CQAs) of the product, and finally the relationship between the CQAs and the clinical safety and efficacy of the product.


AVECIA BIOLOGICS LIMITED
Quality by Design (QbD) is receiving significant attention in both the traditional pharmaceutical and biopharmaceutical industry subsequent to the FDA's publication of the International Conference on Harmonization (ICH) Q8 guidance, Pharmaceutical Development, in May 2006.1 Previously, in August 2002, the FDA had announced a major initiative aimed at improving the quality and management of pharmaceuticals. This "Risk Based Approach to Pharmaceutical cGMPs for the 21st Century" contained innovative concepts that FDA believed would modernize the regulation of pharmaceutical manufacturing and product quality. Several of the key concepts included in the initiative were encouraging the early adoption of new technological advances, facilitating industry application of modern quality-management techniques, and encouraging implementation of risk-based approaches. An outgrowth of using the newest technological advances was the process analytical technology (PAT) initiative. FDA outlined the expectations for PAT in its guidance PAT—A Framework for Innovative Pharmaceutical Manufacturing and Quality Assurance. 2


Anurag S. Rathore, PhD
Complementing the FDA's current good manufacturing practices (cGMP) initiative, two important guidance documents were also published by the FDA that were aligned with ICH documents: ICH Q8, Pharmaceutical Development, 1 mentioned above, and ICH Q9, Quality Risk Management. 3 ICH Q8 described the expectations for the Drug Product Pharmaceutical Development Section of the common technical document, and ICH Q9 outlined approaches to producing quality pharmaceutical products using scientific and risk-based approaches. Much work and progress has been made in defining the application of these expectations in the biotech and traditional small-molecule pharmaceutical industry. The industry also has been working actively on applying these concepts to the development and manufacture of drug products.

Nail and Searles recently reviewed various applications of QbD involving the development, scale-up, and technology transfer of freeze-dried parenteral drugs.4 Cook et al. published a case study involving design of experiments (DOE) to identify key and critical process parameters and their targets for a hydrophobic interaction chromatography step used in an antibody purification process.5 Harms et al. recently presented a case study illustrating an approach to establishing process design space for biotech products.6

This article is the fourteenth in the "Elements of Biopharmaceutical Production" series. In Part 1 of this article, we present a stepwise approach to defining a design space. Case studies from industry, including both biotech and traditional small-molecule pharmaceutical manufacturing, are used to illustrate the key aspects. Part 2, which will appear in the January issue, will present a stepwise approach to validating, filing, and monitoring the design space. It will also discuss how to implement QbD for legacy products and how to integrate QbD with process analytical technology (PAT).


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