Knowledge elicitation as a route to understanding the decision making landscape in monoclonal antibody manufacturing

Gary Montague, Olga Obrezanova, John Liddell, Alison Turner, Suzanne Aldington, Jamie Graham, Andy Racher, Susanne Joerg

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This paper considers a strategy for identifying the decisions and bottlenecks that arise in monoclonal antibody development in the progression from a multitude of potential candidate molecules to a prioritised sub-set that are taken through development and possess a good chance of succeeding in the clinic. While the steps involved are common across the industry, the need to ‘fail fast’ challenges existing decision making. In any development there are numerous technical and business focused staff involved with different skill sets and areas and scales of focus. As potential products could fail in any part of the development programme, failing ‘fast’ requires understanding of the requirements of those in latter stages by technical and business decision makers in as early development as possible. The focus of the paper is the use of the Knowledge Acquisition Technique to elicit the expertise of numerous specialists and to develop an interpretable decision-making landscape across development to facilitate decision making. The effectiveness of the elicitation is considered and the richness of information it delivers to challenge conventional wisdom addressed. The technique is shown to deliver a broader appreciation of the requirements throughout the development supply chain.
Original languageEnglish
Pages (from-to)87-96
Number of pages10
JournalFood and Bioproducts Processing
Early online date12 Jul 2022
Publication statusPublished - 1 Sept 2022

Bibliographical note

Funding Information:
The authors acknowledge the financial support of BioStreamline funded by the United Kingdom Government under the Advanced Manufacturing Supply Chain Initiative. In addition to the authors, the contribution of Colin Jacques, Jim Davies and Jean Aucamp from Lonza Biologics, Claude Peerboom and Mari Spitali from UCB in taking part in the knowledge elicitation tasks is also gratefully acknowledged.

Publisher Copyright:
© 2022 The Author(s)


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