Curious About your Clinical Trial Data Analytics? Overcoming the Top 3 Sponsor Obstacles

Brion Regan | |

Among many other things, clinical trial sponsors are responsible for patient safety, trial integrity, study and vendor oversight. Each of these key accountabilities hinges on high quality data and optimal data analytics, but it’s often difficult to know how your data-related processes measure up to other sponsors’. Here we address the three most common challenges trial leaders have expressed to us about optimizing data quality: accessing real-time analytics, navigating sponsor pitfalls and mitigating risks and delays.

 1. Accessing Real-time Analytics

 Having access to real-time analytics is a shared challenge between sponsors and CROs. Due to the large number of required trial endpoints, and the variability of data capture systems and devices currently used in clinical trials, most reports and dashboards must be manually compiled in order to get a complete picture of trial progress.

For CROs, this can mean that by the time their reports make it back to their sponsor customers, the data are often outdated. When thinking about data analytics, the quality and timeliness of the data is key. Take patient safety, for example. If a sponsor has to wait several months to analyze data that uncover patient safety trends, this poses risks that now must be resolved retroactively ― and hopefully haven’t mushroomed into significant issues.

Clinical trial data analytics solutions provide more current and actionable insight

Some larger sponsor organizations are taking control and bringing clinical trial data analytics and integration responsibilities in-house. It’s becoming more common for sponsors to create a data warehouse that collects and stores information from CROs and handles data analytics internally. Yet these programs can be quite costly and require significant time and resource commitments.

Other sponsors are turning to commercial business intelligence systems that can generate basic data analyses such as a pie chart or scatterplot, but these systems don’t provide a means of integrating and aggregating the necessary data points to produce important visualizations.

Savvy sponsors are turning to data analytics solutions that are specifically designed for clinical research and include data integration capabilities. By integrating data directly from the sponsor’s clinical systems, these solutions eliminate manual back-end processes, and do the heavy lifting for them. For a comparatively modest expense, sponsors can benefit from more current and actionable data, while freeing up valuable time to focus on other activities.

2. Navigating Sponsor Pitfalls

Sponsors and CROs move ahead quickly and efficiently with improved trial management

When identifying trial risks and compliance, it’s crucial to use a set of standard metrics across your trial programs. Otherwise, you’ll be forced to figure out how one metric compares to another. This is easier said than done because sponsors tend to partner with multiple CROs, or even split studies across multiple internal departments.

The need for standardization ties back to the recent ICH Addendum, which states that sponsors and CROs need to collaborate more effectively. This can be accomplished by setting up agreements and data review processes with your CRO partners to ensure you’re in lock step, deciding which data points will be used in analytics, how they will be prioritized and what they are measuring.

Another helpful step toward standardization is to look at existing industry standards. The industry’s most forward-thinking minds get together through the Metrics Champion Consortium (MCC) to create a list of quality and risk-based monitoring metrics. You don’t have to start from scratch.

3. Mitigating Risks and Delays

Data analytics allow for more rapid decision-making. With better access to your data, you can look for signals and trends that may indicate there’s a problem that needs to be stopped in its tracks – whether at a particular site or at the study level. From a process perspective, it’s important to view CROs as partners and integrate them into your team so you can collaborate more effectively.

If one team is looking at one set of analytics, and another is looking at different reports, you’ve just re-created the problem: “We have a lot of data, and we don’t know what it means.” It’s especially important to collaborate with your CRO early on in the planning stages of the trial to discuss what metrics will be used and how often you’ll meet to review the data. This will enable you to work together as partners in problem solving, instead of spending that time getting up to speed.

Have a challenge we didn’t address? Contact a Sales Specialist to schedule a 30-minute consultation to take a closer look at your data.

 For more information about how ERT can improve your reporting and analytics, visit our Trial Oversight page.

Brion Regan is a Director of Product Management at ERT.