How Using AI in Clinical Trials Can Increase Participant Diversity

Table of Contents:

1. How AI in Clinical Trials Helps Identify Eligible Participants

2. How AI in Clinical Trials Can Create Virtual Control Groups

3. How AI in Clinical Trials Helps Provide New Insight From Study Data

4. Increase Diversity in Clinical Trials With StudyPages

Clinical trials are critical to developing new treatments for health conditions. Studies involving real people are often the last phase of research before new drugs or therapies are approved for use. The people who volunteer for these studies are important participants in medical research.

Over the past several years, researchers and government agencies have put a high priority on making sure that clinical trial participants are representative of the people who will be using the treatment when it is approved. Recruiting diverse groups of people for research studies can be challenging. Potential participants may not know about studies, or they may be unsure that a study will benefit them. In addition, researchers may be inadvertently making it harder to find participants by writing eligibility guidelines that are too strict.

AI and machine learning tools can potentially change how researchers recruit and enroll clinical trial participants. By using AI to guide study design and identify potential participants, scientists can ensure that they work with diverse participants to develop cutting-edge treatments.

How AI in Clinical Trials Helps Identify Eligible Participants

One of the biggest challenges in clinical trial enrollment is ensuring potential participants know about trials. In the past, researchers relied on publicizing studies to doctors, hospitals, and other facilities that interact with potential participants. Staff at these facilities could then guide individuals through the enrollment process if they were interested.

The increase in electronic health records (EHRs) has created an opportunity for researchers to deploy AI to find participants more directly. EHRs are essentially vast databases of health information. AI tools could be used to identify key data points, such as diagnostic information, that point to eligibility in a particular trial. Researchers could then reach out to people who might otherwise not have known about the trial. AI could also be a pre-screening tool that allows researchers to simplify study enrollment and make the process easier for participants.

Another benefit of using AI to locate potential participants is that researchers can use that data to decide where to run clinical trials. Many people aren’t able to participate in clinical trials if the research site is too far from where they live. AI clinical trial planning can pinpoint locations that work for a diverse group of participants, allowing researchers to set the trial in those areas.

How AI in Clinical Trials Can Create Virtual Control Groups

One barrier to participating in clinical trials is trust that the study will be of some benefit to participants. The use of double-study design is one reason some people don’t join clinical trials — they don’t think they would receive treatment.

In many clinical trials, participants are divided into treatment and control groups. The people in the control group do not receive the treatment. This allows researchers to compare outcomes for people who do and do not receive treatment, but it also means not all trial participants receive the benefits of new treatments. The possibility of being assigned to a non-treatment group can discourage people from enrolling in trials.

One emerging use of AI in clinical trials is technology that creates virtual control groups. Developers are perfecting AI technology that can create a “virtual twin” of each trial participant. The virtual twin is based on the medical information of the participant and can predict what would happen without treatment. Researchers could use the virtual twins as control groups, thus allowing all enrolled participants to benefit from the new treatment.

How AI in Clinical Trials Helps Provide New Insight From Study Data

One of AI's strengths is the ability to analyze large sets of data in multiple ways. Researchers can get new insights about the science and study design by asking AI to review data from existing studies.

When researchers design studies, they often write very strict guidelines on who can participate. This allows them to control for unexpected outcomes in the study. It also has the downside of making it hard for potential participants to qualify.

New AI tools allow researchers to take a deeper look at eligibility requirements, actual study enrollment, and results of past trials. AI can then offer models of how the participation and outcomes would have been different if certain factors were changed. This type of AI analysis of past trials can guide researchers in writing more inclusive eligibility guidelines for future studies.

A study published in the journal Nature demonstrated how AI analysis showed researchers that certain eligibility requirements had limited the number of participants during the trial. The AI modeling suggested that the treatment could be safely used on patients who had not been admitted to the first trial. This told researchers that the treatment could be helpful to more people than they initially thought. It also offered important insight into what to consider when writing future eligibility guidelines for similar studies.

As applications of AI in clinical trials increase, researchers and developers will need to be thoughtful about the ethics of machine learning. It is essential to program AI tools without biases. It is also critical that any data analysis tool can protect the privacy of the participants and potential participants. Agencies like the FDA are working out how to use AI for diversity in clinical trials while still guaranteeing safety and privacy for all study participants.

Increase Diversity in Clinical Trials With Studypages

All clinical trials rely on the help of people who volunteer to participate in the research. If you want to learn more about clinical trials and how you can participate in medical research, connect with Studypages and sign up for our free Pulse Newsletter. Studypages helps diverse individuals join real clinical studies and take part in the advancement of healthcare research.