Examine the evolution of risk-based quality management toward a comprehensive, end-to-end system for identifying risk and managing quality organization-wide.

• Understand quality definitions and the importance of a common organization language
• Develop quality management systems that are fit for purpose - not every issue requires the same response (or sometimes a Corrective Action and document are enough)
• Build a quality culture - The changing role of QA with the changing regulations

There is a strong correlation between placing reasonable thresholds and setting effective key risk indicators. Learn how these tools allow potential issues to be identified, investigated, and rectified before impacting the quality of the data.

• Understand the impact of KRIs on QTLs
• Review top key risk indicators and their outputs to consider
• Evaluate exceeded thresholds and how to focus on errors that matter

It is critical to ensure that risk assessments feed into monitoring programs. Examine ways to focus monitoring on evolving areas of greatest need.

• Determine which risks have the biggest impact on patient safety and data quality
• Assess how monitoring changes with alternative data sources
• Target monitoring programs to areas of greatest risk

There is a tremendous opportunity to leverage the relationship between clinical and manufacturing process improvement methodologies to advance quality and risk management systematically. Biopharma manufacturing has leveraged process evaluation (define, measure, analyze, improve, control) to ensure continuous quality improvement and quality by design for many years. This presentation will focus on

• How can we transition from looking only at outputs of clinical trial execution processes toward where the processes could go wrong
• Discuss ways to contain, control and reduce the frequency or impact of deviations, from what is expected before we get there
• Identify how we might put in place better controls around complex processes

Tracking process performance is the best way to identify opportunities for improvement. Gain insight on ways to create and maintain a quality metrics program that enhances decision making.

• Identify best practices for tracking performance of clinical research processes
• Examine criteria for evaluation including audits, inspection, SOP deviation, root cause investigation
• Evaluate process measurement data and make changes to improve quality in clinical research

The pandemic has had tremendous impact on clinical trial sites and consequently, site-sponsor relationships and quality processes. Get the inside track on what sites need to ensure continued quality partnerships with sponsors.

• Examine changes in the research landscape from the site perspective
• What opportunities has the COVID-19 pandemic created for the site-sponsor partnership?
• Identify best practices to create quality partnerships with sites

Over the last 10 years, designs of clinical trials and methods of data collection have become more sophisticated which calls for effective risk management and data surveillance tools to ensure adequate sponsor oversight. The use of various service providers that collect and process the primary and secondary endpoint data has also significantly increased. It is the responsibility of the sponsor to ensure ICH E6 R2 “Good Clinical Practice” requirements are implemented. In addition, ICH E8 R1 (e.g., Designing quality into clinical studies) and ICH Q9 (e.g., Risk Management Methodology) help the industry focus on risk-proportionate operational oversight and prospective identification of what matters for patient safety, feasible conduct of the study and data quality.

In this presentation, we will explore the following concepts for how we might consider utilizing an existing system and tools that could help further evaluate risk management insights at the clinical program level.

• Leveraging existing risk management tools and experiences
• Creating a “top-down” approach to risk management
• Considering Quality by Design challenges
• Improving visibility and consistency for study level risk assessments
• Linking critical data and processes to a vendor(s) utilized in studies within a clinical program