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Lynn Hassman, MD, talks about a promising new technology that can optimize precision medicine in patients with uveitis.
Biologic agents like adalimumab (HUMIRA) have proven to be efficacious and well-tolerated in patients with non-infectious uveitis — and yet, a subset of patients fail to respond to these targeted immune therapies.
According to a late-breaking presentation given at the American Academy of Ophthalmology (AAO) 2020 Virtual Conference, single-cell RNA sequencing has the potential to ultimately elucidate this treatment gap and provide insight into the driving factors behind the disease and immune response.
In an interview with HCPLive®, Lynn Hassman, MD, PhD, Assistant Professor, Ophthalmology and Visual Sciences, Washington University School of Medicine in St. Louis, discussed the need for this new technology as well as its clinical implications.
“As an immunologist, what that [treatment] gap tells me is that there are some patients whose immune response—and potentially some types of uveitis—may not be driven by TNF-α, the molecule targeted by Humira,” she said. “Therefore, Humira is probably never going to work for those patients.”
She explained how these responses (or non-responses) are determined through clinical trials. However, she stressed the necessity to predict response prior to treatment.
Her presentation focused on the ability of single-cell RNA sequencing to characterize differences between uveitis types and patients.
“This technology is revolutionizing our ability to study immune cells in the eye,” she said.
For example, she cited its power in producing a vast and deep amount of information from small amount of eye fluid, among other promising features.
So far, Hassman and her team have only studied a small number of patients. However, she has been encouraged by observed specifics of the disease made possible by the technology.
“The data that I present is not ready for [physicians] to change the way that they treat the vast majority of patients that they see,” she noted. “But, as we accumulate more data, and do more studies using this technology, we will start to find trends and patterns in the types of molecules that are expressed in different types of uveitis that are going to suggest treatments to try.”