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December 14, 2021 at 2:00 AM
by Advanced Research Institute
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No matter which condition or issue is being studied, it's vital that any clinical trial being carried out be properly organized and laid out to ensure efficiency and quality data capture. There are a few elements that may comprise these efforts, and one of the most important is known as clinical research study validation.

At Advanced Research Institute, we're proud to offer a wide range of clinical trials in both Nevada and Utah, including everything from GERD clinical trials to conditions like diabetes, IBS and many others. We take pride in the quality level of our studies, including a robust validation process that ensures data reliability and other basic benefits. What is this process, how was it done in the past, and how has modern technology changed things within this realm? Here's a primer on everything you need to know.

Clinical Trial Validation Basics

In the simplest possible terms, clinical trial validation refers to several different methods that might be taken to check clinical data for both accuracy and completeness. It's performed both in advance of the study and throughout the course of the trial itself. The goal, above all else, is to get a clear idea of what's going on within the trial and how it compares to other data sets involving similar clinical issues.

The actual process itself involves testing the behavior of various study data points, edit checks, workflow and many other factors. The goal is to make sure that the data being collected are both correct and complete, which may mean pulling up information from different sources or using various techniques. It's an important step in the trial process because if there are obvious flaws within the data capture method, they'll need to be corrected before any truly reliable results can be put together.

The Importance of Validation

In the distant past, this was a task that really didn't get too much emphasis. That's because most data capture was done manually and generally involved paper records. The goal wasn't necessarily to get completely accurate results so much as it was to get something close enough to what was needed for the study at hand.

In today's world, this couldn't be further from the truth. Clinical research studies almost always rely on electronic data capture, which means that getting accurate and complete information is more important than ever. Without the proper amount of validation efforts, clinical trials often receive an automatic failure label or face significant delays in final results.

Older Validation Methods - Value and Issues

As we just noted above, clinical trials carried out in the decades before major technological advances were generally validated using manual formats like paper spreadsheets and other basic methods. Research teams would use a mixture of different data validation techniques to ensure that the information was as accurate and complete as possible. They might check for basic errors like typos or check the completeness of certain clinical trial elements, such as patient records.

And while the process of manual input was no doubt much more cumbersome than today's methods, this traditional format still did set the baseline for modern validation. Anytime an edit check doesn't work how it's intended, for instance, it would be logged into the spreadsheet, modified and then re-tested -- this is the same process that's gone through today, only with greater speed and efficiency.

Advances in Validation Techniques

Over the last couple decades, though, technological advances have allowed for the streamlining of validation within the clinical trial field. The most important of these would probably be electronic data capture, which works to cut down on the amount of paper used during the process and make everything much more automated. As a result, validation efforts today can sometimes take mere seconds compared to hours or even days in earlier times.

This also makes it easier for researchers to implement efforts like statistical checks, which review the amount of data in a clinical trial and verify practically every individual element. They can also see if any particular factor or condition is more likely to cause errors than others.

A few of the specific tools often used within clinical trial validation today:

  • Auto validation tools: These are automated systems that emulate every action made by a user when completing a given form or data entry point. They then compare the outcome with that of what is expected, measuring it against certain criteria to determine if any potential problems exist. These systems also save enormous amounts of time on repeated data entry, which is no longer necessary with an automated system.
  • Data dictionary: This is a function that creates a blueprint with specific details and definitions for every element in the dataset, from variables like gender and weight to entries for data that's been collected. It's vital that every entry be properly defined and laid out in order to ensure accuracy and avoid any problems down the line; this is why a good data dictionary is so useful.
  • Sample size calculator: This tool helps researchers determine how much information should be captured within a given clinical trial. It takes into account things that may affect a specific study, such as group size and mean or median values that will be captured by the trial. With this tool in place, researchers will also know when they're at risk for reaching saturation levels, which is when no new information can be gathered through data collection.

Validation and Protocol Changes

In many cases, clinical trials will undergo what are known as protocol changes, which refer to changes in the objectives of a given study. These studies may have been designed to test one or more conditions in a specific area, for instance, but the researchers may decide that additional tests need to be carried out during their research.

The result is a change in the focus of the clinical trial, which means that it needs to be validated again from the beginning. As a result, clinical trial teams must be prepared to perform their validation efforts all over again whenever a significant change is made -- and this can be time-consuming, but remains necessary.

For more on the clinical trial validation process, or to learn about any of our current studies and how to enroll, speak to the staff at Advanced Research Institute today.