In the news release, Research Grid's artificial intelligence automates a 3-year Queen Mary clinical trial in seconds, issued 04-Jun-2025 by Research Grid Ltd over PR Newswire, we are advised by the company that the word "patented" in the first and third paragraphs and photo caption field was incorrectly used as originally issued. The complete, corrected release follows:

Research Grid's artificial intelligence automates a 3-year Queen Mary clinical trial in seconds

A large heart imaging study previously undertaken at Queen Mary University of London (QMUL) and Barts Health NHS Trust tested Research Grid's AI.
The AI study demonstrated a savings of $1.5 million in data entry, cut a 5% human error rate, and automated over 24 thousand staff hours with automation

NEW YORK and LONDON, June 4, 2025 /PRNewswire/ -- A study at Queen Mary University of London (QMUL) has shown that Research Grid's AI engine can automate one of the most time-consuming parts of medical research -- data entry.

In a major cardiac imaging trial involving over 600 patients, the AI was able to digitize thousands of pages of patient records in seconds or minutes. This eliminated a 5% human error rate, saved over 24,000 staff hours, and cut data entry costs from $1.5 million to $6,000.

Over 80% of medical research data globally is still entered manually by highly qualified research staff, slowing progress and driving up costs. Research Grid's AI changes that by safely handling complex clinical trial admin of every kind. For example, handwritten text, numbers, images and anonymization while performing quality checks.

"Our AI safely meets today's research demands," said Research Grid Founder and CEO, Dr. Amber Hill. "For too long, the clinical research industry has accepted manual back-office processes as the cost of doing research. The success of this trial shows there's a better way. It's a critical next step in the company's goal of admin-free trials to make research faster and more successful for everyone."

While AI systems have already found a home in industries like finance and insurance, their use in clinical trials has been limited by the complex and sensitive nature of medical records. This QMUL study illustrates that purpose-built AI automation can be introduced safely and effectively in clinical trials, academic research, and a wider variety of use cases.

Professor Anthony Mathur, Study Lead and Centre Lead for the Centre for Cardiovascular Medicine and Devices at Queen Mary's William Harvey Research Institute, said:

"This technology has the potential to dramatically improve the efficiency and accuracy of how we perform clinical trials and clearly emphasizes the role of digital technologies in supporting research workflows. I look forward to the future of this technology."

Beyond clinical trials, the AI could help hospitals and healthcare providers digitize years of paper records in seconds, improving patient tracking and care. As healthcare systems face mounting pressure to modernize with limited resources, this successful trial marks a major step forward in making high-quality, scalable "admin-free" research and care a reality.

About Research Grid

Research Grid is the automation engine for admin-free clinical trials. Too many trials fail because of delays, errors, or weak patient engagement caused by legacy software and manual processes. Our mission is to enable faster, more successful clinical trials by engineering smart software that safely automates back-office admin across the full life cycle.

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