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PharmTech.com Regulating Innovation, Quality, and Risk eBook January 2024 Pharmaceutical Technology ® 21 Qualit y invokes concepts of systems thinking in connecting QRM and KM as well as the opportunity to consider the role of knowledge and KM more holistically across the pharmaceutical business through application of a pro- cess classification framework. Background There has been a bolus of activity associated with ICH Q9(R1) (1) finalized in January 2023, as the long- awaited update to the 2005 guidance, ICH Q9 Quality Risk Management (2). This activity included scrutiny of the concept paper (3), comments on the draft revi- sion, and revision of the guideline itself. In addition, there has been a focus on the development of sup- porting training material by the ICH Expert Working Group (EWG) and to interpreting what it all means to industry and to organizations on an individual level as the deployment and adoption process begins. Concurrent to this activity surrounding ICH Q9(R1), the Pharmaceutical Regulatory Science Team (PRST) at Technological University Dublin have continued their ongoing research into related topics, including QRM, KM, and RBDM. In particular, the PRST are exploring the relationships and interconnectivity between these practices, applying through "systems thinking" mind- set and aspects of complexity theory where appropriate, which provide a more holistic approach to analysis and how the parts of a system interact over time (4). One of the key areas of focus for the PRST is regard- ing the practice of KM, including: • The role of KM as a pharmaceutical quality sys- tem (PQS) enabler as defined by ICH Q10, Phar- maceutical Quality System (5) • The relationship between QRM and KM as dual enablers of the PQS • The role of KM in informing risk-based decision making. The purpose of this paper is to compile and synthesize this KM-related research describing how it supports the intent of the ICH Q9(R1) revision and, ultimately, the ob- jectives of the PQS itself as outlined by ICH Q10 Pharma- ceutical Quality System (5), which are to achieve product realization, establish and maintain a state of control, and facilitate continual improvement. To start with, however, it is important to demystify the relationship between the terms "knowledge" and KM. Authoritative definitions are presented in the next sec- tion of this paper, and the authors have discussed these concepts in more detail in a 2022 paper (6). Consider the following pragmatic descriptions by the authors. In a pharmaceutical context, "knowledge" is an asset that includes what is collectively known (e.g., scientific understanding and insight) about products, processes, and platforms (e.g., technology transfer documents, regulatory filings, process experience, etc.) inclusive of both documented (explicit) knowl- edge a nd k now-how, exper ience, a nd ot her tacit knowledge. To further break it down: • "Explicit knowledge" is "knowledge" that can be ex- pressed in words, numbers, and symbols and can be stored (e.g., in books, computers, etc.). Explicit knowledge can be articulated and easily commu- nicated between individuals and organizations (7). • "Tacit knowledge" refers to "knowledge" that re- sides in the minds of individuals and is surfaced in response to a situation or action (8). Tacit knowl- edge is often referred to as "know-how." Whereas, KM is a set of practices and associated mindsets and behaviors that determine how knowl- edge is managed (e.g., captured and made available in the future) in an intentional, repeatable, and systematic manner. Common KM practices include content man- agement processes, lessons learned, knowledge trans- fer activities, among others. KM as a discipline is most successful when certain enabling practices are in place, such as standard processes, dedicated roles (e.g., com- munity stewards, lessons learned facilitators), commu- nications, and training (9) as well as foundational prac- tices of effective data management (e.g., data strategy, standards, and stewardship). Essentially, if "knowledge" is considered a noun, then "KM" can be considered a verb. This is perhaps a seemingly obvious but important distinction—as in the authors' experience—these terms of "knowledge" and "KM" are often used loosely, almost interchangeably. It is crucial that the reader is mindful of the difference and—as the authors will make the case—knowledge is the currency of managing risk, and the smart investment is to ensure that the best possible knowledge is available when and where it is needed—via KM—to inform QRM and risk- based decision making, and to support the PQS objectives. The foundational role of knowledge and KM for risk management, risk-based decision-making, and pharmaceutical quality When one looks holistically across the ICH quality guidelines (10), the expectations for managing knowl- edge are implied through the repeated references to the availability and application of knowledge in support of risk management, science and risk-based decision-mak- ing, product and process understanding, and, ultimately, ensuring availability of a safe and efficacious product to the patient. While these references are not each overtly stated as "knowledge" or "knowledge management," they do repeatedly invoke the availability and applica- tion of "knowledge" under the guise of many synonyms, including prior knowledge, platform knowledge, scien- tific knowledge, science, evidence, product knowledge, process knowledge, experience, product development history, expertise, know-how, product understanding, process understanding, and lessons learned (6).