Virtual reality company AppliedVR is taking an innovative approach to a new trial for treating chronic pain. Instead of trying to find a group of people with chronic back pain to sign up for the trial and not receive the treatment, they will pull data from an existing database of chronic pain patients to use as a comparison group — a strategy that has the potential to make clinical trials more efficient.
AppliedVR received approval from the Food and Drug Administration in November for its virtual reality system that treats chronic back pain. Now the company is gathering more information about how the treatment works in different groups in the real world. They are working with data company Komodo Health for the trial. Komodo provides its customers with access to a comprehensive database of anonymized patient records of people with a variety of health conditions, including chronic pain, that follow people over time.
The collaboration will allow AppliedVR to track the experience of chronic low back patients in general and compare their experience with the experience of people who actively participated in the study. “So as they move forward, they will be able to understand and demonstrate much better the value of their technology and what it delivers compared to traditional chronic pain treatments,” said Web Sun, president and co-founder of Komodo Health.
Using real world data as a patient group in a study, also known as a synthetic wishbone, can make research trials more efficient — companies don’t have to do the work of enrolling as many people as possible in clinical trials. They may also allow any patient who actively decides to enroll in a trial to receive the treatment being tested, rather than risk signing up just to get a placebo. Synthetic control groups may also improve fairness in clinical research, Sun says. Historical distrust of racial minority groups in the medical system and lower access to health care often means minority groups are underrepresented in clinical trials. Komodo’s database contains information about patients’ race and ethnicity so that research teams can target specific groups, he says.
“That allows us to look at all those different subpopulations and underrepresented patient populations to see if they have different outcomes,” he says.
This approach to pilot design is still new – experts are excited about its potential, but it’s not used regularly. Researchers are still checking to see if it can provide results as accurate as a standard control group and identifying what types of studies it might work for. “The FDA is still wary of trial designs in which a synthetic control arm is intended to completely replace traditional data because of concerns that synthetic data may not be a one-to-one match with traditional data,” Arnaub Chatterjee, senior VP of product at health data company Medidata Acorn AI, told Pharma Voice.
But the agency is getting more comfortable with this kind of data, especially when used in conjunction with more traditional patient groups, Chatterjee said. And some groups are starting to use synthetic patient arms for studies that will be part of applications for FDA approval: the FDA said in 2020 that a pharmaceutical company could use a partially synthetic control arm in a trial testing a cancer treatment.
Sun says he is optimistic that this approach to clinical trials will become more common. “Regulators are increasingly joining this approach as they recognize all the challenges of trials,” he says. “It saves time and money, but most importantly, it gives us the opportunity to accelerate the development of new therapies and bring them to market faster, cheaper and in a more representative way.”
SOURCE – www.theverge.com