Plans Afoot to Create Algorithm That Predicts Treatment Responses
Girihlet, Mayo Clinic join forces in using ImmuneScanner technology
The biotech company Girihlet will collaborate with Mayo Clinic to develop an algorithm that evaluates the effects of immune-suppressing treatments in patients with ankylosing spondylitis (AS), Girihlet announced.
Under the so-called “know-how agreement,” Girihlet will use its proprietary ImmuneScanner technology to monitor changes in immune T-cells after treatment and build an algorithm that classifies treatment responses. The company will work with John Davis III, MD, a rheumatologist at Mayo Clinic, and other experts in the field to test and validate its algorithm.
“ImmuneScanner generates a snapshot of the T cells of the immune system, empowering doctors to monitor individual response to therapies, to personalize treatments (modify dosage, drugs),” Anitha Jayaprakash, PhD, CEO of Girihlet, said in a company press release.
First-line therapies for AS, including non-steroidal anti-inflammatory medications, can ease pain and inflammation, but aren’t designed to specifically slow AS progression.
However, immune-modulating second-line therapies, including anti-TNF medications and interleukin inhibitors, can slow disease progression. But their immune-suppressing effects can come with significant and severe side effects.
Many patients may undergo a treatment odyssey, trying multiple therapies over the course of many months before finding the right fit.
As part of the collaboration, researchers will rely on a component of ImmuneScanner called Tseek, which uses a non-invasive blood sample to track the profile of a person’s T-cells. This class of immune cells are directly implicated in autoimmune diseases like AS, and can be influenced by immune-modulating treatments.
Ultimately, the company hopes its approach will help doctors identify early on if a patient is or isn’t likely to benefit from a treatment, and to help them select the best option.
“We want to address and prevent a painful journey of taking expensive drugs with heavy side effects,” Jayaprakash said.
The study will involve recently diagnosed AS patients who are starting their first treatment. Blood samples will be obtained at the start of treatment, and then at two, four, and 16 weeks after treatment begins.
Patients’ T-cell profiles, determined with Tseek, along with clinical data collected throughout the study, will be used to train the algorithm. After training, ImmuneScanner will predict the best treatment option for each patient.
Tseek also has been used to study the effects of vaccines and cancer immunotherapy, as well as transplant rejection and colitis in animal models, according to Girihlet.
While AS is the first autoimmune disease in the clinical pipeline for ImmuneScanner, the company hopes to expand the technology as a way of monitoring and tailoring treatment approaches for a range of complex autoimmune diseases.
“As an autoimmune patient who has undergone many different immunosuppressive therapies that were determined by trial and error, I believe ImmuneScanner can revolutionize the treatment of these conditions,” said Ian Weisberger, an investor and AS patient advisor to Girihlet.