Physical Sciences and Mathematics Commons^™

Emerging Technologies: Empowering People To Capture, Share And Transfer Tacit Knowledge, Donncadh J. Nagle, Melanie J. Adams

Level 3

ICH Q10 was published in 2008, and presented a model for an effective Pharmaceutical Quality System (PQS). However, the industry still has some way to go in embracing and implementing its principles in order to achieve greater product realisation, to establish and maintain a state of control, and to facilitate continual improvement.

ICH Q10 introduced us to two key enablers: Knowledge Management (KM) and Quality Risk Management (QRM).^[1] While the pharmaceutical industry has made progress in implementing the principles of QRM since 2008, there has been significantly slower progress in implementing knowledge management practices. However, there may be solutions …

Steps Towards Digital Transformation In The Pharmaceutical Manufacturing Landscape Knowledge-Enabled Technology Transfer, Anne Greene Professor, Martin Lipa Dr

Level 3

No abstract provided.

Managing Risk And Knowledge: Frameworks To Guide Knowledge-Enabled Technology Transfer, Martin Lipa Dr, Anne Greene

Level 3

Technology transfer is not only about the transfer of technology, but also about the transfer of knowledge, as evidenced by definitions of KM within the biopharma industry and beyond. However, knowledge transfer is often not well structured and its effectiveness – in particular for tacit knowledge (i.e., know how) – is an opportunity for improvement which can lead to many benefits. This article profiles recent research into the topic of improving knowledge transfer during technology transfer and presents several recently developed frameworks for improving such. The article furthermore explains how the frameworks can be co-deployed in support of robust knowledge …

Exploring Pathways From Data To Knowledge To Insights In The Pharmaceutical Industry: ‘Introducing The Pharmaceutical Knowledge Ecosystem’, Melanie J. Adams, Paige E. Kane, Anne Greene (Editor), Martin Lipa

Level 3

The ecosystem of how the pharmaceutical industry acquires data, transforms these data into tangible knowledge, and derives valuable insights throughout the process, is highly complex. Data, information, knowledge, and the resulting insights, are necessary to support decision- making, manage risk, problem solve, ensure product realisation, enable continual improvement, and enhance operational effectiveness. Building on the fundamental concepts established in the well-known Data Information Knowledge Wisdom (DIKW) hierarchy, this paper reviews the basic concepts involved in the DIKW pathway and begins to relate these concepts to both established capabilities (e.g., PAT), existing requirements (e.g., data integrity), and emerging trends in the …

Improving Risk-Based Decision Making (Rbdm) Effectiveness Through A Framework Which Integrates Knowledge And Risk, Martin Lipa, Valerie Mulholland, Anne Greene (Editor)

Level 3

This paper explores the emergence of the importance of knowledge in Risk-Based Decision Making (RBDM) and Quality Risk Management (QRM) through a detailed review of ICH Q9(R1) (Step 2) and presents a framework(the RKI cycle) to integrate knowledge and risk and associated six principles to operationalise it.