
Increased regulatory requirements, complex protocols, and a global patient population make clinical trial recruitment increasingly difficult to manage and result in many trials failing to enroll enough patients and to finish on time.
The impact is significant; delays in enrollment completion affect regulatory approval submissions and, ultimately, product launch. Budget and cost overruns combined with launch delays can cost a company hundreds of millions of dollars.
A reliable enrollment plan is critical to finishing a trial on time. Because tools like spreadsheets, business intelligence software, and transactional CTMS systems require extensive customizations, study teams often rely on intuition, good fortune, and budget overruns to meet subject and timeline targets. In addition, enrollment management varies from study manager to study manager, making it difficult to share best practices or enforce consistent business rules across the organization.
Study Managers often miss valuable insights and fail to spot potential problems because they lack the tools to quickly identify clinical study enrollment trends. Home-grown spreadsheet models provide some assistance, but have limited ability to aggregate data and predict potential problems in an automated fashion. Instead of seeing problems before they occur, most study managers rely on contingency planning to address enrollment issues after the fact.
Slow site initiation, high screen failures, seasonal variability, and unproductive sites can all delay recruitment. Even good plans need to be adjusted from time to time.
Without the ability to predict, simulate, and model different scenarios, study managers can’t effectively adjust the plan to keep enrollment on track.
In addition, aggregating data from multiple sources takes up to 10% of a study manager’s time--time that can be better spent analyzing data to make the best decisions.
With spreadsheets, study managers can’t view and drill down into data to diagnose problems or to track progress. Without simulation and modeling tools, study managers may over-invest in activities that contribute to over-enrollment, such as advertising campaigns, new centers, and other costly initiatives.
Many global study teams have difficulty collaborating because they lack timely data across numerous countries and centers. This lack of transparency impedes communications across multiple time zones and delays decisions.
Not only does the absence of a transparent system reduce staff efficiency and increase enrollment and data clean-up problems, but it also allows companies to repeat costly mistakes. When companies can’t track each site’s historical performance, they can’t identify top performers or weed out underperformers for future trials.