The failure to enroll patients and keep them enrolled, the cost of taking a drug to market, the breakdown of relationships between sponsors and trial sites or sponsors and CROs are just some of the threats clinical trials face.
It’s important to watch out for these common threats and ensure the trial stays within its scope and timeframe. Failure to do so will result in significant financial burdens and even an aborted trial.
This post looks at some of the issues that beset trials, pushing them beyond their scope and threatening their efficacy. It also looks at ways to safeguard against these dangers, including the use of clinical trial management software.
So Just How Bad is the Problem?
More than a third of active clinical trials miss their deadlines and exceed their time limits. This is not because of “bad science” but “bad project management,” Alexandre Mouravskiy at contract research organization Biorasi writes.
When it happens, trials need rescuing — but there are few signposts along the way to look out for.
Missing minor deadlines. There is a significant threat to a trial when big deadlines such as regulatory approvals, patient recruitment deadlines and database lockings are missed. But small deadlines matter too, such as commitment failures from the CRO, emails sent late or not at all, study documents arriving late, trainings delayed, among others.
Delayed site activation. Enrollment is enough of a challenge on its own, so sites need to be activated on schedule. Failure to do so will mean not even a single patient can be screened. Site activations must be planned and their progress tracked accordingly, as this will notify trial managers when they’re off schedule.
Enrollment is low. Failure to enroll is a death knell for a trial’s success. When it is far behind projections, the trial is in danger, including budgetary burdens of opening more sites in an attempt to recruit new patients.
Slow response to queries. Gathered data needs to be queried for accuracy. But these queries need to be responded to very quickly as the longer time periods that pass, the harder it is to verify the data.
A Real-World Example
A case study published in The Pharmaceutical Journal reveals that one randomised double-blind, parallel-group placebo-controlled trial of propranolol and pizotifen for prevention of migraine became three years overdue and £230,000 over budget.
Due to various problems from drug formulations to releasing of funds, they found themselves facing severe delays — the project was set back by 26 months — and additional money troubles.
They offer a simple yet compelling maxim by which to plan a trial: “Saving time also saves money.”
Find the Root Cause
In addition to the warning signs Mouravskiy provides, Beth Harper, president of Clinical Performance Partners tells Clinical Leader’s Ed Miseta that trials often need rescuing from an underperforming CRO. This could be due to problems with “site activation, data quality, or other performance shortfalls,” but it can also be due to enrollment issues.
Invariably there needs to be a root cause analysis, Harper says, reliant on a “structured and systematic process” that yields as much information as possible to understand the study. To compute and analyze a sufficient amount of data to determine the root cause of a trial’s many issues, a robust CTMS is essential.
When a Study Needs Rescuing
If a CRO has missed submissions or not monitored visit reports or accurately gathered and packaged data, the trial is likely in danger.
This means it will overshoot its scope and timeframe and a rescue team CRO will be required, Jacquie Mardell, senior director of clinical operations at Ascendis Pharma, says.
The team at Atlant Clinical adds to Mardell’s list, noting a trial will need rescuing when it has been overly optimistic an inadequately planned, timelines have been rushed, team members’ have not had responsibilities allocated and vendors are not coordinated.
Plan for the Unplanned
Trials invariably won’t go according to plan, as we’ve noted. The best option is to factor in the inevitable aspects that could go wrong, Rebekah Puls, Ph.D., at the University of New South Wales Medicine says.
“If you have spent time considering the potential risks, building extra time into your planning, approval and start-up phase, to allow for ethics, contractual and regulatory approvals, you will save yourself stress later on,” she explains.
Better Communication Saves Time
Organization is essential for trials to succeed, Hope Cullen, associate director of operations at Imperial CRS, argues. Time lost scouring emails, transferring paper documents and locating information is a serious concern to trial managers.
Having a functioning and effective “conduit of communication” between project managers and their team members means all communication is recorded and runs through a devoted channel.
How CTMS Helps With Time Management
While not all of the above can be remedied using CTMS, the threats certainly can be mitigated. And it can help trial staff better manage their time, Lidiya Todorova, at Clinicubes, says. A CTMS ensures data is not duplicated and is captured in real-time. Reports are also easy to access, which means time is saved — and, of course, money.
CTMS Yields Accurate Data
Data helps trial managers improve processes so investment in the most suitable trial software is essential, according to the team at Shearwater Health. Citing a 2017 Veeva study, the team notes that improvements from data analysis sped up the patient recruitment cycle by 48 percent.
Schedule Thinking Time
It’s important to schedule time into the study that allows trial staff to stop and analyze the study’s scope, objectives, required course of action and other planning of metrics, Dalfoni Banerjee, principal consultant and CEO at 3Sixty Pharma Solutions LLC, advises.
Using software can keep track of “the project goals… [and] activities — especially meetings and communications.” This should act as “road map,” which is a “high-level timeline,” noting dates, resources and budget.
Machine Learning To Speed Up Processes
Proper data analysis is going to ensure the time of all trial stakeholders is suitably managed. Machine learning, more than regular CTMS, has the potential to enhance data analysis, Basheer Hawwash, Ph.D., principal data scientist at Remarque Systems says.
Machine learning draws together and analyzes “millions of points of data in minutes” to “flag anomalies, focus inquiries, inform decisions” and reduce risk. It also results in faster trial audits so “time-consuming data cleaning” is no longer required.
The Simple To-Do List Rebooted
In an age when talk of AI, machine learning and other data analyses abound, a to-do list may sound old-fashioned or simplistic. But without one, trial managers will likely suffer from time management issues.
Consider Forte’s director of analytics Wendy Tate who swears by a to-do list, albeit rebooted as an app-based tool. However, it’s best to choose the right kind of list — more visual or text-based — to meet the users’ needs.
Part of a successful to-do list requires tracking time spent on regular tasks and rating the fires (emergencies) that arise and determine the time needed to resolve them.
Clinical trials, difficult as they are to manage, run the risk of overshooting both the scope of the study and the timeframe by which to complete it. When this happens, it may well be too late to save, however, there are warning signs to watch out for.
Those trial managers that keep their sight on the clock and manage their time efficiently will likely be in charge of successful trials. The software sponsors and trial managers choose to use will impact how time is monitored, managed and maximized.