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This article discusses the adoption of RBQM in academic settings and the lessons that were learned.
Garry Kasparov, one of the greatest chess players in human history, who lost to IBM Deep Blue in 1997, said, “don’t fear intelligent machines, work with them… weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.” 
As the biopharmaceutical industry explores Risk-Based Monitoring (RBM) as a part of Risk-Based Quality Management (RBQM), many clinical project managers are becoming more involved with cross-functional teams to implement RBM and are learning how to manage risks in clinical studies.
However, during the implementation of the RBM process, the inferior process becomes the largest risk. The team, usually not experienced with the methodology of risk assessment, makes mistakes. The most common pitfalls involve ignoring operational roles, or replacing a process with technology and vice versa. As a result, a team overreacts on minor hazards and ignores the most probable events that exhibit a major impact on study results.
As an example of best practice, presented by Bristol-Meyers-Squibb at Clinical Trials Innovations Summit, BMS consults with varying functions to comprehensively develop an RBM strategy (Figure 1). If one or several of those teams do not have the skillsets required to properly interpret and communicate risk, leverage RBM technology, and understand the RBM process, critical study risks may be missed, and studies would, subsequently, suffer.
Figure 1: Cross-Functional RBM Team at BMS
Apart from poor understanding of the core concepts of risk management and KRIs/KPIs, commonly chosen technologies that do not incorporate RBM process burden study teams, rather than facilitate the process. This means that quality risk management plans may lack solid foundation.
In such circumstances, it is very important to provide examples based on my experience training multi-functional biopharmaceutical professionals on Risk-Based Quality Management (RBQM) as a guest lecturer at the Rutgers School of Health Professions. The unique feature of this one module in the Project Management (PM) for the Life Science Professional course was to explore the RBQM theory with the application of professional RBM technology in practice. The main goal for students was to create a retrospective quality risk management plan for previously failed industry studies.
Explore Core Risk Management Concepts
With the collaboration of Lisa Palladino Kim, lead Professor of the PM course, the students learned the basics of risk management from a general industry standpoint, i.e., the broad concepts and definitions of risk, differentiating between qualitative and quantitative risk, risk types, how the risks interact, risk categorization, KRIs/KPIs, risk mitigation, and force field analyses.
Clinical trial-specific topics went into matrix diagrams, and how they apply to TransCelerate RACT, TransCelerate RACT categories, and an example of how TransCelerate RACT was used to identify risks in protocols.
Finally, and importantly, we discussed the topics covered in ICH E6 (R2) addendum on RBQM, EMA’s reflection paper on risk-based quality management in clinical trials, and vital components of a quality risk management plan.
Selection RBM Technology and Demonstration
As our educational goal was to prepare students for a real-world situation, we leveraged the Cyntegrity RBM technology, and its cloud-based RACT -@RACT, which offers a set of customizable components for educational purposes. The main driver for my decision to use Cyntegrity was that the system guided students through the RACT exercise in a simple way, without unnecessary complexities that typically come with other technologies. Specifically, the risk methodology upgrades TransCelerate RACT by essentially requiring risk-managers to document risks, which includes the “event, cause, and impact” approach (Figure 2).
Figure 2: Example of Cyntegrity Risk Statement
Moreover, the Cyntegrity platform was flexible to enable the administrator to turn sections of the RACT on/off, so the educational experience was customized for students, allowing them to focus on sections relevant to the lesson.
Select Exercise Protocols and Specify Sections
The Cyntegrity platform offers students protocols from succeeded and failed studies provided by Project DataSphere for educational purposes, which exposes students to real-world protocols. While those protocols added application experience to the lesson, many of the protocols were more than 100 pages in length, and to perform a RACT exercise containing all 13 TransCelerate RACT sections was not feasible; not all students had relevant experience in all RACT sections. The selective approach enforced the productive and collaborative effort between the multifunctional groups of students.
The purpose of the exercise was to expose students to real-world risk management applications and to enable them to understand how to categorize and manage risk. Correspondingly, the pre-selected protocol sections provided students with sufficient exposure, and equipped them with required skill sets to efficiently and holistically perform RACT in their functions.
Draft a Quality Risk Management Plan
With a thorough understanding of risk management concepts, the facilitation of risk identification via RBM technology, and guidance on writing quality risk management plans, students (in a team setting) were required to compare their RACT results from Cyntegrity, and draft their own quality risk management plans.
Results and Takeaways
On review of the students’ quality risk management plans; they far exceeded expectations, especially knowing that most students had minimal prior exposure to risk management. Firstly, there were not many questions on the RBM technology received, because the technology was self-intuitive and user-friendly, and it efficiently facilitated RBM-specific processes. Secondly, due to the multi-functional approach in team settings, students were able to identify risks that I had not thought of, and created their own customized key risk and performance indicators, proving the axiom that the involvement of many stakeholders improves the objectivity of RACTs. Moreover, the students went beyond by proposing impressive risk mitigation techniques. If these procedures and strategies were implemented to those failed studies in the past, perhaps some of those studies might have succeeded, or go/no go decisions were made earlier.
The main lesson learned from this experience was that biopharmaceutical professionals who have minimal experience in risk management, if educated sufficiently and empowered with the right process-driven technology, can contribute significant value to a risk identification and risk assessment exercise. They can be superior to other teams, who do not apply technology and process. With the described educational approach, biopharmaceutical professionals can better translate their experience and expertise into an actionable risk management plan and empower study teams to execute quality risk management correctly, and greatly reduce the probability of a study’s failure.