Building a Business Case for Biopharmaceutical QbD Implementation (Peer Reviewed) - The author describes a methodology for developing a per product qualitative and semi-qualitative business case for a


Building a Business Case for Biopharmaceutical QbD Implementation (Peer Reviewed)
The author describes a methodology for developing a per product qualitative and semi-qualitative business case for applying QbD to a biopharmaceutical product.

BioPharm International
Volume 25, Issue 8, pp. 40-47


Nature of QbD-related change

Engaging large organizations in QbD-related change implementation can be a challenging change-management exercise. There are several key areas of impact:

1. Structure: The disciplined and structured QbD approach uses paper analysis to drive experimental work. Additional staff member time spent on this analysis delays initiation of wet-lab work, but eventually it translates into less time spent on lower value-added work on less critical areas. Such risk assessments drive work towards what is really important to product quality and process performance (27). The design space established influences post-licensure regulatory strategies, tempered by the degree of regulatory comfort in a company's quality systems to control changes within ranges of demonstrated acceptable performance.

2.Technology: Although there is little change in the required science, there is a change in technology that challenges QbD implementation (3). High-throughput process and analytical technologies are linked to experimental planning and design to minimize resources and speed up the time required to address identified high-risk areas.

3. Knowledge: There is a prescribed knowledge build associated with QbD implementation. An information management strategy must maintain ongoing and current links to documentation and access to justifications for decisions. Increased understanding includes a primary focus on design space definition, specifically the extent of multivariate study linking multiple input parameters and raw material attributes (often from multiple steps) to CQAs. Data obtained are subsequently assembled into mathematical models that can readily predict outcomes for varied input ranges.

Understanding QbD implementation challenges

Many companies currently are struggling with QbD implementation (5). These challenges directly affect estimation of both costs and benefits, which in turn assist in fully creating and understanding the business case (21).

One main challenge is insufficient understanding of QbD itself. Training, mentoring, and overall integration into process development deliverables serves to improve this understanding. There are differences in levels of understanding among regulators within FDA and internationally (3, 5). Insufficient understanding among company scientists and regulators is potentially exacerbated by the lack of a significant number of actual success stories demonstrating the "value add" for large molecules. A bit of "flying the plane while building it" exists because many of the QbD implementation specifics are still being worked out and acceptance by FDA is not guaranteed. Interestingly, despite a similar assessment given by FDA's Woodcock about FDA's situation with the biosimilar pathway, several companies worldwide have managed to develop compelling business cases to undertake work in this area (30).

A second challenge relates to the cultural change required to adopt this new way of thinking (2), especially the increased requirements for cross-functional alignment (21). Several competing business factors limit the time, effort, and commitment required at all levels (ie, senior management, middle management, and staff). Upper management needs to consistently ask about risks to quality and timeline, and how can QbD mitigate these risks (1, 24, 31). The most mature QbD implementations have strong active and consistent senior management support, standardized and rigorous development tools/processes, and cooperation between development and manufacturing (25, 26). Generally, both regulatory and corporate scientists are more comfortable adding resources to address a high risk rather than subtracting resources when they do not add value to address a low risk. It thus has become difficult to redistribute resources while maintaining a "zero sum" outcome.

A third challenge is the unclear nature about whether QbD is a regulatory expectation, along with the "lack of tangible guidance for industry" (3). For example, some parts of ICH Q8 have been recommended to be part of inspections (32). Other parts of ICH Q8 have been incorporated in the newly approved revised process validation (PV) guidance, although without overtly using the term "quality-by-design" (33). Even so, some have observed that the new PV guidance requires "a wholesale shift towards a QbD approach to achieve compliance" and "greater characterization early in the product development cycle" (14). The co-existence of traditional and enhanced (i.e., QbD) approaches in these guidances suggests that a minimum level of QbD investment is expected by regulators. Potentially these incorporations eventually help develop a clear and unified picture of the information content and depth expected by regulators (5).

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