Standardized performance metrics that are actionable drive transparency and process improvement
goBalto, announced today the June release of the ChromoReport, a quarterly analytical discussion on study startup, representing over 70 percent of clinical trial sites in phase II & III of the Top 25 pharma companies.
Study startup is a complex business, composed of country selection, pre-study visits, site selection and initiation, regulatory document submission, budget and contract negotiations, patient recruitment initiatives, and enrolling the first patient.
The focus on technology as a driver of performance improvement in clinical trials is intense, but despite years of valiant efforts, study execution remains far from optimal. For study startup, the data are dismal. Results of a 2017 survey conducted by the Tufts Center for the Study of Drug Development (Tufts CSDD), Start-up Time And Readiness Tracking (START) II, found that 80% of respondents who have invested moderately or heavily in study startup technology reported time savings. Moreover, respondents who stated that their startup technology is adequate have cycle times that are 30% shorter that those with inadequate technologies.
Similar to previous research, the study revealed that on average nearly 11% of sites selected are never activated. The primary reason cited was budgeting and contracting problems, which has been a challenge identified in much published work.
Workflow-based technology is critical in the clinical trial continuum enhancing operational performance and quality. This advanced technology also enables prediction models to be built. For example, if the pre-visit to contract executed task in Phase II and III studies typically takes 6.2 months, as suggested by Tufts CSDD research, it is critical to track the sub-steps involved in that task, and who is responsible for each. Without this information, only the overall time for the task is known, but it cannot be determined where bottlenecks may be occurring.
Contract execution, provides a good example of a process with many sub-steps (Figure 1), and why each must be tracked to avoid bottlenecks. For example, All Contracts Executed, normally available in an eTMF as a summary of artifacts does not provide any metrics on the sub-steps that precede it. Without those metrics, stakeholders would be unaware of any issues until the planned date for All Contracts Executed was reached. Analytics need to be actionable. To make this happen performance metrics must be data-driven, standardized across studies, indication, therapeutic areas, and timely.
Figure 1. Site level Contracts tasks and milestones
Recent research from the KMR Group on global site contract cycle times highlights why tracking these sub-steps is critical. Their study, evaluating 20,000 recently-executed contracts for Phase II and III trials from leading biopharmaceutical companies, found that overall contract cycle times have doubled from an industry median of 1.5 months in 2009-2011 to more than 3 months in 2014-2015. Even contracts conducted in North America, traditionally a top performer, increased from 1.3 months in 2010-2011 to 2.4 in 2014-2015. Cycle times in emerging markets were even longer.
Additionally, in a survey of more than 400 investigative sites, CenterWatch found that contract and budget negotiations with investigative sites are protracted and fraught with delays, contributing to slow study startup timelines.
What do the industry metrics have to say about contract timelines in study startup?
Patient's Can't Wait
"Turning big data into big insights requires analytics that are actionable. Performance metrics must be data-driven, standardized across studies, indication, and therapeutic areas, and timely. They must also, importantly, facilitate a forum for discussion."
Jeff was formerly VP Clinical Innovation and Implementation at Eli Lilly and Company
President and Founder
"Utilizing overarching cycle times within your own company or team is only the beginning of creating the best results for your company. To truly begin to move toward 'best in class' or 'industry leading' you need to consider your processes and cycle times from a bottleneck perspective, as well as industry standard. By thoroughly understanding the data you will support your teams to make the best decisions to improve study startup, ensuring that the goal of getting protocols to patients faster is achieved, which represents the first step in competing a study on or ahead of schedule."
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