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Role of Knowledge Management in Development and Lifecycle Management of Biopharmaceuticals
AuthorRathore, Anurag S. ; Garcia-Apont, Oscar Fabián ; Golabgir, Aydin ; Vallejo-Diaz, Bibiana Margarita ; Herwig, Christoph In der Gemeinsamen Normdatei der DNB nachschlagen
Published in
Pharmaceutical Research, 2017, Vol. 34, Issue 2, page 243-256
PublishedSpringer US, 2017
The final publication is available at Springer via https://doi.org/10.1007/s11095-016-2043-9.
Document typeJournal Article
Keywords (EN)knowledge indicators / knowledge management / ontologies / process modeling / quality by design
Project-/ReportnumberIndustrial Methods for Process Analytical Chemistry - From Measurement Technologies to Information Systems (imPACts): 843546
URNurn:nbn:at:at-ubtuw:3-3900 Persistent Identifier (URN)
 The work is publicly available
Role of Knowledge Management in Development and Lifecycle Management of Biopharmaceuticals [1.87 mb]Supplementary material [0.16 mb]
Abstract (English)

Knowledge Management (KM) is a key enabler for achieving quality in a lifecycle approach for production of biopharmaceuticals. Due to the important role that it plays towards successful implementation of Quality by Design (QbD), an analysis of KM solutions is needed. This work provides a comprehensive review of the interface between KM and QbD-driven biopharmaceutical production systems as perceived by academic as well as industrial viewpoints. A comprehensive set of 356 publications addressing the applications of KM tools to QbD-related tasks were screened and a query to gather industrial inputs from 17 major biopharmaceutical organizations was performed. Three KM tool classes were identified as having high relevance for biopharmaceutical production systems and have been further explored: knowledge indicators, ontologies, and process modeling. A proposed categorization of 16 distinct KM tool classes allowed for the identification of holistic technologies supporting QbD. In addition, the classification allowed for addressing the disparity between industrial and academic expectations regarding the application of KM methodologies. This is a first of a kind attempt and thus we think that this paper would be of considerable interest to those in academia and industry that are engaged in accelerating development and commercialization of biopharmaceuticals.

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