The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
EnForeSys is Cytel’s tool for patient recruitment planning. We have discussed on the blog recently with Tufts University's Center for the Study of Drug Development, Ken Getz, the problem the industry continues to face with patient recruitment, and the fact that most trials significantly exceed their original planned duration. In the face of this problem there's a pressing need to create more realistic plans and scenarios. To achieve this, EnForeSys models the enrollment process and then assigns probabilities for various scenarios.
We return to our discussion with Ken Getz of the Tufts CSDD for part 2 of our blog post on key challenges in clinical trial operations. You can find Part 1 of the interview here, or read on to gain his insights on the fundamental problem at the heart of clinical trial operations challenges, and his views on the initiatives and programs that he believes show the most promise for the future.
Photo by J. Kelly Brito on Unsplash
Research on clinical trial enrollment makes for sobering reading, characterized by the oft-cited statistic that 11% of active sites fail to enroll a single patient. In this first part of a two part interview, we sit down for a discussion with Ken Getz of the Tufts CSDD. Here, Mr. Getz expands on some of the Center’s more recent research on challenges in clinical trial operations. In the second part, to be published next week, Mr. Getz will reveal his insights on the key opportunities for the future.
Charles Liu, Statistician and Product Manager at Cytel will be part of the expert speaker panel at the 7th Annual SCOPE Summit on 23-26th February. This year’s meeting is taking place in Miami, and offers a packed program with tracks covering such varied topics as risk based monitoring, clinical data technology and integration, and managing outsourced clinical trials. SCOPE has become one of the leading events on the conference calendar for clinical operations executives, with 1100 delegates from over 300 companies expected to attend this February.
Clyde Haberman, a columnist for the New York Times, once commented on the remarkable consistency of train arrival times on the Tokyo subway: "Every station lists the scheduled arrival times: 9:01, 9:04, 9:08 and so on. I lived in that city for five years...I never saw a train arrive so much as a minute late, not once. A posting of 9:01 meant 9:01." . Such predictability is rarely observed in the messy world of clinical operations, yet many study plans are formulated like a Tokyo subway timetable. In a previous blog entry , we cited an example trial that targeted 1,800 patients across 50 sites over a 10-month period. Let us examine three underlying assumptions in this plan, with the help of a modeling and simulation tool.
Two insightful papers from Applied Clinical Trials should be of interest to many clinical trial planners. The first by Kenneth Getz describes the problem of enrollment performance, while the second by Matthew Kibby proposes a potential solution.
Getz reports a study providing recent estimates of industry-wide rates of enrollment delays . In 2012, the Tufts Center for the Study of Drug Development (CSDD) requested data from 10 pharmaceutical companies and two CROs. The combined database covered nearly 16,000 investigative sites involved in 151 clinical trials from years 2008-2010. A few significant findings are worth highlighting:
Midway through a trial is a terrible time to realize that you need a new strategy to complete the study. Sadly, it is typically midway through a trial when drug supply, patient recruitment and budget all tend to deviate from the planned development path. Sometimes this is because the initial plan utilized idealized assumptions, (i.e. non-random patient enrollment), which failed to give the desired ballpark estimate of timelines and resource constraints. Other times, responding to unexpected operational or statistical challenges might have proven difficult due to inflexible trial designs .
We have spoken in some depth about how thorough planning and room for flexible decision-making can avoid some of these potential difficulties   . However, sometimes the specter of trial discontinuity arises anyway. Here is a scenario which recently confronted the Cytel Consulting Team.