Work
Facial recognition feature, web-based platform development, app development, solution for more accurate clinical trials.
Summary
Langate created a web-based platform and mobile app for iOS and Android with a facial recognition feature; thus preventing duplicate subjects in remote clinical trials and contributing to more accurate trial results.
About 25% of research participants attempt to simultaneously enroll in multiple studies in the 1st phase of remote clinical trials. This percentage ranges from 2% to 12% in the 2nd to 4th phases of these clinical trials. So duplicate subjects (people who take part in more than one trial at a time) become a great risk for the end results and safety of the researched treatment. Facial recognition helps to avoid these risks through improved identification. This solution is useful for remote trials that are unable to perform fingerprint identification and, consequently, are more likely to face the problem of duplicate subjects.
Our client wanted to further develop their toolset for accurate subject identification through a facial recognition feature. As they were looking for a development company with deep expertise in healthcare technology, they discovered Langate and, based on our experience, chose to work with us.
Our client helps healthcare organizations conduct better clinical trials through the prevention of both duplicate subjects and key protocol violations. Their main aim is to facilitate accurate and safe clinical trials, while saving time and money for the researchers and stakeholders.
Langate knows how to ensure the quality of research and results to optimize routine processes!
Duplicate Subjects Elimination
Those who deceive researchers in order to be enrolled multiple times in trials also tend to lie about treatment results to stay in the trial, thus, causing the trial to be ineffective, inaccurate, and potentially dangerous. Sometimes researchers have to redo the entire trial as a result and spend twice as much money to receive approval for the treatment.
Subjects' Identify Verification
Remote clinical trials have become increasingly popular, especially after the pandemic when hospital visits were limited. Healthcare researchers could not identify subjects through fingertip recognition and needed an entirely new remote tool. Our client came up with the idea of a facial recognition feature that will identify subjects and their clinical trial background without the need to visit the research center. They turned to Langate for the development of a web-based platform that can break down this issue.
With our decade-long experience in the development of healthcare software, we were able to not only deliver the necessary solution, but we also went above and beyond our client’s expectations. For this project, we were able to create:
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