COVID-19 Trial Finder, a simplified method for patients, clinicians and healthy volunteers to search for appropriate COVID-related clinical trials in their general location. This system also allows potential candidates to pre-screen their eligibility for such trials through a set of short medical questions.Researchers at Columbia University have developed
There are currently more than 1500 COVID-related trials ongoing, including more than 300 in the United States, according to ClinicalTrials.gov. The process of identifying applicable trials can be daunting, especially for patients dealing with COVID-related stress.
COVID-19 Trial Finder, a system detailed in JAMIA last November, eases the burden for trial seekers by generating user-specific questionnaires dynamically to filter out trials. The development team created an updated version of the system to focus solely on COVID-related trials, which can reduce a large set of potential trials to only a handful within 5-6 survey questions.
“Information overload is an unnecessary challenge for patients and clinicians seeking COVID-related trials,” says Chunhua Weng, PhD, Professor of Biomedical Informatics at Columbia University and a member of the Columbia Data Science Institute. “The process of finding the right trial, based on location, eligibility and any other factor, can be overwhelming and turn people off to the process. We believe this system, based on our DQueST research, can provide frontline workers, clinicians and patients a simplified portal to the right trial for them.”
This publicly facing site opens with questions related to a person’s location, age, gender and COVID status (diagnosed with, high risk for contracting, hospitalized, etc.) to come up with a first set of related trials, and then allows the user to answer a minimal number of questions tailored to a patient’s clinical characteristics to filter out even more trials.
“When the COVID-19 pandemic started, the entire Weng Lab banded together to contribute in any way they could,” said Alex Butler, a MD/MS candidate at Columbia. “As a medical student, I hope this tool can help patients, clinicians, and the general public stay safe and help to fight this global health crisis.”
A manageable set of trials will be generated after the search, whose titles and direct links to eligible trials through ClinicalTrials.gov are shared with the user, who can determine which, if any, are best for them.
“COVID-19 Trial Finder is accurate in eligible trial searching and easier to use,” said Yingcheng Sun, a postdoc research scientist majoring in computer science. “New data processing and verification techniques are used to ensure our data was accurate and users would be given the right information immediately. We also designed data visualization and analytics modules to improve user experience. Everybody, not only medical personnel, can do something to fight this pandemic.”
Clinicians see the potential benefit of COVID-19 Trial Finder as well.
“This will be a powerful tool for clinicians caring for patients who are critically ill with the coronavirus infection,” says Benjamin A. Miko, MD, Assistant Professor of Medicine at Columbia University. “As there are limited treatment options for COVID, it is critical that all patients have access to clinical trials. Participation in research gives patients access to the most cutting-edge therapies while providing valuable information to healthcare providers, thereby improving the care of future patients.
“While we’re lucky that there are a growing number of trials available for coronavirus therapies, it is often difficulty to determine which specific studies are appropriate for individual patients,” adds Dr. Miko, who specializes in infectious diseases. “This online tool will be an enormous help to busy clinicians, allowing them to efficiently link patients with the trials best suited to them. I’m confident that this will positively impact individual patients and the larger medical community, allowing us to share the benefits of discovery with the largest possible number of people.”
This research is supported by the Irving Institute for Clinical and Translations Research, the National Center for Advancing Translational Sciences through Grant Number UL1TR001873, and the National Library of Medicine Grant R01LM009886 (Bridging the semantic gap between research eligibility criteria and clinical data).