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Lookup NU author(s): Micael Karlberg, Dr Moritz von Stosch, Professor Jarka Glassey
This is the authors' accepted manuscript of an article that has been published in its final definitive form by Taylor & Francis Inc., 2018.
For re-use rights please refer to the publisher's terms and conditions.
© 2018 Informa UK Limited, trading as Taylor & Francis Group In today’s biopharmaceutical industries, the lead time to develop and produce a new monoclonal antibody takes years before it can be launched commercially. The reasons lie in the complexity of the monoclonal antibodies and the need for high product quality to ensure clinical safety which has a significant impact on the process development time. Frameworks such as quality by design are becoming widely used by the pharmaceutical industries as they introduce a systematic approach for building quality into the product. However, full implementation of quality by design has still not been achieved due to attrition mainly from limited risk assessment of product properties as well as the large number of process factors affecting product quality that needs to be investigated during the process development. This has introduced a need for better methods and tools that can be used for early risk assessment and predictions of critical product properties and process factors to enhance process development and reduce costs. In this review, we investigate how the quantitative structure–activity relationships framework can be applied to an existing process development framework such as quality by design in order to increase product understanding based on the protein structure of monoclonal antibodies. Compared to quality by design, where the effect of process parameters on the drug product are explored, quantitative structure–activity relationships gives a reversed perspective which investigates how the protein structure can affect the performance in different unit operations. This provides valuable information that can be used during the early process development of new drug products where limited process understanding is available. Thus, quantitative structure–activity relationships methodology is explored and explained in detail and we investigate the means of directly linking the structural properties of monoclonal antibodies to process data. The resulting information as a decision tool can help to enhance the risk assessment to better aid process development and thereby overcome some of the limitations and challenges present in QbD implementation today.
Author(s): Karlberg M, von Stosch M, Glassey J
Publication type: Article
Publication status: Published
Journal: Critical Reviews in Biotechnology
Year: 2018
Volume: 38
Issue: 6
Pages: 957-970
Print publication date: 01/07/2018
Online publication date: 07/03/2018
Acceptance date: 15/12/2017
Date deposited: 15/01/2018
ISSN (print): 0738-8551
ISSN (electronic): 1549-7801
Publisher: Taylor & Francis Inc.
URL: https://doi.org/10.1080/07388551.2017.1421899
DOI: 10.1080/07388551.2017.1421899
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