Streamlining Data Review in Clinical Trial Management

Introduction

For many therapeutics companies, the success of clinical trials on their path to FDA approval is twofold: adhering to projected trial timelines and ensuring the collection of high-quality data to substantiate your primary endpoints. While successful patient enrollment is a significant milestone, unresolved queries and incomplete eCRF (electronic case report form) pages can also undermine trial timelines and budget, which can be tens of millions of dollars in phase 2 and 3 trials.

Traditional data review approaches often rely on manual, time-intensive spreadsheet trackers built on top of various reports from your Electronic Data Capture (EDC) system. In addition, data reviews are often conducted at predetermined milestones during the trial, for example after a certain number of patients have been enrolled, or at a set time period, such as monthly reviews.

However, the intermittent nature of these data reviews means that a huge volume of open queries and incomplete eCRF pages can accumulate, requiring an extensive effort and coordination with sites long afterward. This process can be extremely time-consuming as you wait to resolve open queries and incomplete eCRF’s in order to conduct data analysis for readout, potentially putting your trial timeline at risk and consuming more operational runway.

In this article, we’ll provide an overview of the data review process at many biotech companies today, some of the common challenges, and most importantly, ways to enhance trial success with more efficient data review strategies.

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Overview of the Data Review Process

Data review stands as a cornerstone of effective clinical trial management. It’s a crucial process to ensure the accuracy, completeness, and integrity of trial data. This often involves a detailed examination of data captured in electronic Case Report Forms (eCRFs), with the ultimate goal of identifying and resolving any queries or discrepancies that arise. It acts as a critical defense mechanism, protecting against data inaccuracies that could compromise trial results or undermine the study's validity.

A comprehensive approach to data review extends beyond mere query resolution. It encompasses a thorough evaluation of eCRF page statuses—ranging from 'expected' to 'entered,' 'overdue,' and 'reviewed'—to gauge the completeness of data entry and adherence to trial timelines. Similarly, the assessment of query statuses, including 'answered,' 'cancelled,' 'closed,' and 'open,' provides insights into the responsiveness and issue-resolution capabilities of your trial sites.

Equally important is monitoring the speed at which sites address and resolve queries, comparing it against agreed upon benchmarks set forth in contractual agreements. This measure not only reflects the efficiency of site operations but also serves as an indicator of the trial's overall health and progress. By maintaining a vigilant eye on these components, trial managers can ensure a streamlined and rigorous data review process, facilitating a more accurate and reliable trial outcome.

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Common Challenges in Data Review

It’s essential to conduct meticulous data review in an ongoing fashion as part of your clinical trial management. However, for smaller biotech companies with limited resources, this can pose a challenge. Key obstacles encountered in the industry today include:

‍Manual Spreadsheet Trackers

Manual spreadsheet trackers for managing trial data is time-consuming, and therefore, may not be possible to compile on a daily basis. They are also prone to human error because they are often created from data review reports from their EDC system and involve the use of various Excel functions across multiple sheets. These manual spreadsheet trackers require a dedicated personnel to keep pace with the volume and complexity of data populated in their EDC system, but at smaller biotech companies, they have limited time and resources.

‍Intermittent Review Cycles

Scheduled data reviews are often tied to specific milestones, such as certain number of participants completed treatment or study, or on a set cadence, such as once a month. However, depending on the scale of the study, this can lead to significant delays in query resolution because the volume of the data can aggregate very quickly. The gap between data entry and review sessions allows errors to persist, complicating subsequent data analysis and decision-making processes. If there are pervasive errors across many sites, your team should identify and resolve those issues quickly to protect the integrity of your trial data and effectively communicate with sites on those issues.

‍Coordination with Research Sites

Addressing accumulated queries requires extensive back-and-forth communication with research sites. This can be highly inefficient and time-consuming because sites may be working on many other studies and have a huge number of patients they have seen in between the time they filled out the eCRF pages in question and when you are contacting them. This can strain relationships with site staff, further delaying the resolution process and also potentially risking future studies. Your team’s relationship with your sites is key to ensuring a successful clinical trial.

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Best Practices for Smaller Biotech Companies

‍Maximize Your EDC System

Modern Electronic Data Capture (EDC) systems like Medidata Rave EDC offer data management and data review reports that can help streamline the review process. They have reports that show you the breakdown of query status, ages of queries across sites, and page review status. Many biotech companies take advantage of these out-of-box reports, but because they aren’t flexible to produce custom reports necessary for each biotech’s needs, you often need to create separate spreadsheets to aggregate the data from all the reports into a single tracker.

If you have an in-house data management team or have the budget to work with an external data management vendor, you can also customize reports directly within your EDC system. Implementation may require additional time and investment, but it offers a tailored approach to data review that could enhance efficiency and data quality.

‍Embrace More Frequent Data Reviews

Implementing more frequent data reviews rather than monthly checks can significantly reduce the accumulation of unresolved queries and incomplete eCRF pages. This proactive strategy allows for quicker identification and resolution of data discrepancies and safeguarding the quality of your study data. While sorting through the relevant EDC reports and compiling data into spreadsheet trackers can be time-consuming, the effort could pay dividends in maintaining data quality and minimizing delays on the path to a database lock and readout.

The ultimate goal of more frequent data reviews is to uphold the highest quality of study data, thereby ensuring accurate data analysis. By maintaining a minimal number of open queries, you not only expedite the trial process but also lay the groundwork for accurate and reliable trial outcomes.

Real-Time Solutions for Data Review

Some biotech companies work with data companies like JReview, eClinical elluminate, and Spotfire, and depending on your budget and how much time you have for implementation, those could be great options to explore.

Miracle has also been helping biotech customers conduct continuous data review because we already integrated with their EDC system, such as Medidata Rave EDC, allowing them to get real-time updates on incomplete eCRF pages and open queries. Since it takes them less than a week to integrate their EDC and other systems into Miracle, it’s seamless to show the breakdown of pages and queries by site, drill into subject-level and even query-level details, and display this information in the context of your overall clinical trial management processes, including enrollment, safety, drug supply, etc.

Here is an example of conducting data review with Miracle:

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Final Thoughts

Efficient data review strategies are pivotal in adhering to planned trial timelines and minimizing delays towards data readout.

As we’ve highlighted in this article, traditional data review approaches are often time-consuming because of the queries and eCRF pages that quickly accumulate, and rely on manual spreadsheet trackers. By truly harnessing the data you have in your EDC system, you can adopt a continuous data review approach that can help you reduce the time you spend following up on unresolved queries and incomplete eCRF pages, thereby achieving data readout faster.

At Miracle, we work with smaller biotech companies in Phase 2 and 3 clinical trials to easily integrate with their EDC system and provide real-time data review dashboards. Because of our integration capabilities and connectors to popular EDC systems, we become your control room in less than a week. We make it easy to drill into metrics to get granular site-level and subject-level details, and combine data from your other sources, such as lab vendors, Randomization and Trial Supply Management (RTSM), and Interactive Response Technology (IRT). If you’d like to learn more about Miracle, please get in touch.