Three Ways To Improve Quality In Clinical Trial Processes

By Ed Miseta, Chief Editor, Clinical Leader

Timeliness, cost, and quality are all critical factors that must come together to ensure an efficient and successful clinical trial. Unfortunately, the complexity of trials, combined with coordination challenges, force sponsors to have to identify the opportunities needed to improve trials. But how do you know what efforts will produce the best results? And what are the common challenges and shortfalls impacting most companies? To identify those issues, clinical solutions provider Shearwater Health reviewed recent research outlining the challenges and opportunities that exist in clinical trial processes. After the main issues were identified, the findings were grouped into three areas requiring improvement by sponsors.

1. Rampant Data Errors And Gaps

How extensive are data input errors in the life sciences industry? An audit of ongoing clinical trials conducted in 2013 found extensive errors and gaps in eTMF (electronic trial master file)-entered data. The study found the most egregious issues existed in three categories. 

• Site management records that were misclassified, had missing signatures, or were incomplete.
• Trial-supply documentation that was expired or had inaccurate, duplicate, or incomplete data.
• Data management, statistics, and trial management records that had expired or were inaccurate, incomplete, or were duplicates.

Quality data is essential to getting regulatory approval, yet this problem may be more far-reaching than you think. A study published in the Drug Information Journal found that 6.2 percent of records in EDC (electronic data capture) clinical trial databases needed changes. Of those records needing changes, 71.1 percent were due to data-entry errors. Not something most clinical data experts would want to hear.

But the news is not all bad. The Drug Information Journal study also noted the solution to this problem lies in improved data management and risk-based monitoring, which would achieve significant efficiencies in clinical trials. Those efficiencies include:

• An increase in the quality of clinical trial data.
• Reduced timeframes to database lock.
• An earlier stop to the clinical development of ineffective or unsafe drugs.
• A reduction in clinical trial costs.
• An accelerated time to market.

The study also found that accurate records helped organizations identify protocol variations and data outside the normal range at the time of entry, rather than days, weeks, or months later.

2. Absent Data Compilation Quality Control

Do you have a quality control standard operating procedure (SOP) in place? SOPs are essential to successful quality control systems within TMF groups. SOPs also ensure that quality control stakeholders have evaluated an appropriate number of documents in advance of regulatory audits or inspections. According to a study on clinical trial data management conducted in December 2016, 72 percent of TMF groups had a quality control SOP in place. Unfortunately, that also means 28 percent of teams do not have a quality control SOP in place for their TMF. Although most TMF teams recognize the importance of quality-control SOPs, the reasons for not having one varied from one company to the next.

Regardless of the reasons for not having one, implementing SOPs for data entry into TMFs can significantly improve the quality, accuracy, and completeness of trial information. This can save organizations time and money.

3. Deficient Process Optimization Through Limited or No Data Mining

The final piece of this puzzle examined by Shearwater Health has to do with data mining. Do you use data to improve study processes? If not, you probably should be. A 2017 survey of unified clinical operations found that 23 percent of sponsors do not, or rarely, use data for this purpose. The survey, which queried 300 clinical operations professionals, also found 46 percent only use data for process improvement in certain cases.

While the findings indicate an industrywide drive towards a unified clinical model defined by end-to-end processes and systems, seamless collaboration, and insights across the clinical lifecycle, the shortcomings are reason for concern. Respondents also cited challenges resulting from application and process silos, with almost half noting the challenge of integrating their eTMF or EDC application with their CTMS (clinical trial management system).

Another study, conducted in 2016, found that organizations using clinical trial data and metrics to improve trial processes have seen significant benefits. Those benefits include:

• Improved audit and inspection readiness
• Better visibility into performance metrics
• Cost savings
• Faster study start-up
• Shortened clinical time

So what does this all mean? Automation can make your life better, but care must be taken to avoid input errors, which will lead to needed changes in the future. Quality control is a necessity, and audits will help ensure improvements in quality, accuracy, and completeness of trial information. And finally, don’t miss out on the benefits that can be accrued through proper data mining. Shorter clinical timelines, lower cost, and faster start-up are all possible when using trial data and metrics to improve trial processes.