FEATURED SOLUTION: PROTOCOL DEVIATIONS TOOLKIT
“The TransCelerate Protocol Deviation Toolkit was leveraged to inform our strategy for a significant shift in our Protocol Deviation process. Although we did not participate in the workstream, it helped build a robust business case to secure internal commitment for the process improvement. Subsequently, the various components shaped the overall outcome.
The Protocol Deviation Toolkit inspired our business case, which resonated with leadership and enriched our Protocol Deviation process offering to the business. The primary objectives were to standardize how we managed our protocol deviations internally, align with industry best practices and provide a more consistent experience for our sites.
The Protocol Deviation Process Guide was invaluable. It provided information and examples to create our own guidance for managing Protocol Deviations during the COVID-19 pandemic. It was also instrumental in driving the development of our revised standard operating procedure (SOP) and we continue to reference it in providing support to study teams.
We incorporated the concepts of organization, intermediate and protocol-level Protocol Deviations, and aligned with the proposed TransCelerate definitions. The Protocol Decision Tree was tailored to our internal requirements and incorporated as an appendix. The Protocol Deviation Assessment Plan (PDAP) was also adapted and is now a mandatory element.
Study team feedback confirms the benefits of our revised Protocol Deviation process. Investigators are familiar with reporting requirements and study teams appreciate the simplified definitions and categorization approach. Study Teams are using the PDAP efficiently and it has triggered focused crossfunctional discussions. Our Global Process Owner reported, ‘I’m very grateful that you introduced me to the world of TransCelerate, and I believe we have a more optimal global process as a result.’ By simplifying the process for investigators and study teams, we improve the management of protocol deviations which, by default, should also improve patient safety and data quality in our clinical trials.”