Better data means better understanding of costs. With nearly half of clinical trial costs unaccounted for, including known administrative costs, and much of those linked to study startup, a renewed focus on purpose-build tools is paramount.
The clinical trials sector has done a good job tracking costs associated with study execution, but costs linked to study startup are conspicuously absent. A quick look at industry research confirms this gaping hole in cost accountability. For Phase III clinical trials, for example, it is widely recognized that total costs are substantial, ranging from an estimated $11.5 million to $52.9 million, depending on therapeutic indication. Upon closer examination, it is apparent that identified costs are almost exclusively tied to study execution, and rarely include details on the hefty costs incurred early on, namely those tied to study startup and site overhead. In fact, data from an often-quoted 2014 study published by the Department of Health and Human Services (DHHS) indicate that unaccounted for costs may represent upwards of 43% of the total cost of conducting a clinical trial.
This statistic is calculated from the DHHS study, which focused on numerous cost drivers in each phase of clinical trials and the percentage they represent of total costs. For Phase III studies, among the many known costs, the top three were:
- Administrative staff (11.7% of total costs)
- Clinical procedure costs, such as electronic data capture (11.3%)
- Site monitoring costs, such as risk-based monitoring (8.2%)
Collectively, these top known costs, plus all of the other known factors, rang in at $11.38 million, yet the average of all Phase III costs totaled $19.89 million. It is concerning that the large $8.51 million difference between these two figures lacks detail and remains unaccounted for.
How is this possible?
Download our white paper Analytics and Metrics Help Pinpoint Costs of Study Startup to see how by embracing a systematic data-driven approach, it is possible for metrics to identify more accurately the best sites, steps causing delays, the associated costs, and why this is happening.
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