A quarterly analytical discussion on study startup
The clinical trials sector is awash in metrics, and while early ones generally made broad determinations, such as which sites are top enrollers, the trend is toward more precise metrics that are actionable and help predict where bottlenecks may occur. This is a radical change for stakeholders looking to resolve one of study startup's most enduring challenges – improving budget and contract cycle times.
For years, this laborious step has ranked as the lengthiest of study startup activities, and recent data suggest it remains the primary cause of site activation failure. Some 50.5% of sponsors and 54.3% of contract research organizations (CROs) cite it as the main culprit. Further evidence of contracting problems stems from earlier research, which found that the time period from pre-site visit to contract and budget execution represents the majority of study startup cycle time, 76%, and can average eight months. In addition, a study in which 20,000 contracts were analyzed suggested that site contract cycle times have doubled in recent years. The industry median jumped from 1.5 months in 2010-2011 to more than three months in 2014-2015. With the pharmaceutical industry's intense focus on better performance, stakeholders are ready to embrace strategies that identify and help shorten long contract cycle times.
Addressing the budget and contract cycle involves moving away from the single data point approach, such as "time from pre-site visit to execute all site level contracts". This is not a useful metric unless it is based on its sub-steps. Measuring these sub-steps is critical to building prediction models that identify processes causing bottlenecks. With a predictive capability, grounded in workflow-based metrics, it becomes possible to condense contract cycle times, presenting a significant opportunity for optimizing clinical trial operations.
What do industry metrics say about the review durations of the investigative sites vs. sponsors/CROs?
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