AppliedVR, a virtual reality startup, is adopting a novel approach to a new clinical study for its chronic pain therapy. Rather than recruiting individuals with chronic back pain to enroll in the study but not get treatment, they will utilize data from an existing database of chronic pain patients as a comparison group – an approach that has the potential to improve the efficiency of clinical studies.
In November, AppliedVR received FDA certification for their virtual reality system for treating chronic back pain. The business is gathering further data on how the therapy works in practice with various populations. They're doing the research in collaboration with healthcare data startup Komodo Health. Komodo provides its customers with access to a massive database of anonymized patient health information from individuals suffering from various health issues, including chronic pain.
The agreement enables AppliedVR to follow the experience of chronic lower back sufferers in general and compare it to the experience of trial participants. "As a result, they'll be able to communicate and illustrate the value of their technology and what it offers compared to standard chronic pain therapies much more clearly going ahead," says Web Sun, president and co-founder of Komodo Health.
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What Did The Study Entail?
Using real-world data as a patient group in a study, referred to as a synthetic control arm, may increase the efficiency of research studies by relieving corporations of the burden of recruiting as many individuals for clinical trials. Additionally, they can ensure that every patient who voluntarily chooses to enroll in a study receives the medicine being studied, rather than taking the risk of enrolling to get a placebo. Sun adds that synthetic control groups may also help enhance clinical research's equality. Due to ethnic minority groups' historical distrust of the medical system and limited healthcare access, minority groups are often underrepresented in clinical trials. Komodo's database includes data on patient race and ethnicity, allowing research teams to focus on particular subgroups.
"This enables us to examine all of those various subpopulations and underrepresented patient groups to see if they have significantly different outcomes," he explains.
This kind of trial design is still in its infancy – experts are enthusiastic about its potential, but it is not routinely used. Researchers are presently verifying that it can yield data as precisely as a specific control group and determining the sorts of studies for which it may be most effective. "The FDA continues to be skeptical of trial designs in which a synthetic control arm is intended to completely replace traditional data due to concerns that synthetic data is not a perfect match for traditional data," Arnaub Chatterjee, senior vice president of products at health data company Medidata Acorn AI, told PharmaVoice.
However, Chatterjee said that the agency is becoming more comfortable with this data, especially when combined with more conventional patient groups. Additionally, some organizations are beginning to utilize synthetic patient arms in studies included in FDA clearance applications: the FDA said in 2020 that a pharma manufacturer might consist of a partially artificial control arm in a study assessing a cancer therapy.
The Vision of The President
Sun is confident that this method of conducting clinical trials will become increasingly prevalent. "Regulatory authorities are more supportive of this strategy since they appreciate the inherent difficulties associated with trials," he adds. "It saves time and money, but most significantly, it enables us to accelerate the development of innovative medicines and bring them to market more quickly, more affordably, and with more representativeness."
Featured image: AppliedVR
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