Quality by Design for Biopharmaceutical Drug Product Development

Jameel, Feroz; Hershenson, Susan; Khan, Mansoor A.; Martin-Moe, Sheryl

doi:10.1007/978-1-4939-2316-8

Cited by 9 publications

(3 citation statements)

References 220 publications

(292 reference statements)

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“…The exact representation of the design space and what the design space exactly describes seems to be left to the applicant, i.e., "Design space is proposed by the applicant and is subject to regulatory assessment and approval" [6]. However, a common understanding seems to be reached on how the design space should be developed, referred to as the QbD roadmap [1][2][3][4][5]7]. Based on the Quality Target Product Profile (QTPP), the Critical Quality Attributes (CQAs) of the product either at the output of the entire process or after each process unit are identified based on risk assessment approaches.…”

Section: The Current View On the Development And Representation Of Thmentioning

confidence: 99%

“…where w are the process model parameter estimates. The form of this equation seems to be used to describe the design space when filing the design space [2,6,7]. The equation can either describe each unit operation or the entire process [6].…”

Section: The Current View On the Development And Representation Of Thmentioning

confidence: 99%

“…Operation within the design space yields selected quality attributes of the drug to stay within acceptable ranges (the approach for the selection of process parameters and quality attributes is sketched below). Several publications describe the development of design spaces in the pharmaceutical QbD context [1][2][3][4][5] and a review of the design space development was performed by Debevec et al However, most of these design space developments use a rather static characterization of the design space, via Design of Experiments (DoEs) and statistical modeling approaches.…”

Section: Introductionmentioning

confidence: 99%

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Working within the Design Space: Do Our Static Process Characterization Methods Suffice?

et al. 2020

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The Process Analytical Technology initiative and Quality by Design paradigm have led to changes in the guidelines and views of how to develop drug manufacturing processes. On this occasion the concept of the design space, which describes the impact of process parameters and material attributes on the attributes of the product, was introduced in the ICH Q8 guideline. The way the design space is defined and can be presented for regulatory approval seems to be left to the applicants, among who at least a consensus on how to characterize the design space seems to have evolved. The large majority of design spaces described in publications seem to follow a “static” statistical experimentation and modeling approach. Given that temporal deviations in the process parameters (i.e., moving within the design space) are of a dynamic nature, static approaches might not suffice for the consideration of the implications of variations in the values of the process parameters. In this paper, different forms of design space representations are discussed and the current consensus is challenged, which in turn, establishes the need for a dynamic representation and characterization of the design space. Subsequently, selected approaches for a dynamic representation, characterization and validation which are proposed in the literature are discussed, also showcasing the opportunity to integrate the activities of process characterization, process monitoring and process control strategy development.

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