Quality by design in pharmaceutical manufacturing: A systematic review of current status, challenges and future perspectives

[Display omitted] Quality by Design (QbD) was originated in the broad domain of Quality Management and was recently adapted and formalized in specific terms for assisting pharmaceutical companies efforts towards market and operational excellence. However, despite some impressive success stories, the...

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Bibliographic Details
Published in:	European journal of pharmaceutics and biopharmaceutics Vol. 147; pp. 19 - 37
Main Authors:	Grangeia, Helena Bigares, Silva, Cláudia, Simões, Sérgio Paulo, Reis, Marco S.
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01-02-2020
Subjects:	Attributes variability Design of experiments Legacy products Multivariate data analysis Pharmaceutical industry Quality by design Raw materials Retrospective quality by design Risk assessment Routine commercial manufacturing Quality by design Risk assessment Legacy products Raw materials Pharmaceutical industry Design of experiments Retrospective quality by design Attributes variability Multivariate data analysis Routine commercial manufacturing
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Summary:	[Display omitted] Quality by Design (QbD) was originated in the broad domain of Quality Management and was recently adapted and formalized in specific terms for assisting pharmaceutical companies efforts towards market and operational excellence. However, despite some impressive success stories, the pharmaceutical industry have not yet fully embraced QbD, particularly in routine commercial manufacturing (Rantanen and Khinast, 2015; Puñal Peces et al., 2016). In this review, we aim to analyse the current state of implementation of QbD methodologies and tools in the pharmaceutical industry, extracting patterns and trends and identifying gaps and opportunities that may be considered to improve QbD adoption. For this purpose, a critical analysis of 60 research papers was performed, whose contents were classified, compared and summarized at different abstraction levels. Our analysis reveals the following tools as the frequently adopted for conducting each activity: Risk Assessment (RA) - Ishikawa Diagram, Failure Mode and Effects Analysis (FMEA) and Risk Estimation Matrix (REM); Screening Design of Experiments (DoE) – 2-level Full and Fractional Factorial Designs; Optimisation DoE – Central Composite Design (CCD). Emerging trends include the growing interest in quantifying and managing the impact of raw materials’ attributes variability on process and product, as well as the development of Retrospective QbD approaches (rQbD) in complement to standard QbD.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Undefined-1 ObjectType-Feature-3 content type line 23
ISSN:	0939-6411 1873-3441
DOI:	10.1016/j.ejpb.2019.12.007