Study Aims for Better Way of Marking Myelination in MS Patients
Rune Labs' AI platform to capture myelin status during neurostimulation
Rune Labs has partnered with Coastal Research Institute (CRI) to identify new and noninvasive biomarkers of the loss of myelin, the fatty sheath surrounding nerve fibers that is progressively damaged by multiple sclerosis (MS).
The collaboration involves a patient study that will take advantage of Rune Labs’ first-in-class precision neurology artificial intelligence (AI)-based platform to analyze nerve cells’ electrical activity and possibly uncover new disease markers.
Investigators hope the approach will offer a new way to monitor progression and better evaluate the effectiveness of potential MS treatments in clinical trials.
“Currently, clinicians have no easy way to measure myelination in patients with multiple sclerosis,” Krishnan Chakravarthy, MD, PhD, co-founder and executive director of CRI, and an adjunct professor of nanoengineering at the University of California San Diego, said in a Rune Labs’ press release.
“If we’re going to develop effective disease-modifying therapies, and design and run more efficient clinical trials that capture efficacy signals, we’ll need precise, non-invasive biomarkers that measure the degree of myelination and reflect disease [mechanisms],” Chakravarthy added.
MS is characterized by damaging and destructive autoimmune attacks on myelin, in a process called demyelination. Myelin loss slows the electrical impulses that nerve cells use to communicate, giving rise to a range of disease symptoms that can worsen as demyelination progresses.
Persistent myelin loss also kills nerve cells, leading to the development of brain and spinal cord lesions, which are areas of tissue damage and scarring.
Biomarkers of myelination needed
Some investigative MS therapies aim at restoring myelin, in the hopes of stopping or reversing disease progression. But a lack of tools measuring the degree of myelination limits researchers’ ability to monitor how well these treatments might be working.
Current strategies to monitor disease severity in clinical trials often rely on clinical scores, such as the Expanded Disability Status Scale (EDSS). While helpful, such clinical assessments can be imprecise, and may not accurately reflect the volume and activity of lesions in the brain or spinal cord, Rune Labs noted.
In the collaborative study, MS patients will receive a closed loop spinal cord stimulator. Spinal cord stimulators, commonly used to treat pain associated with nerve damage or injury, are devices placed under the skin that deliver light electrical stimulation to nerves in the spinal cord.
Those with closed loop technology are able to not only provide electrical stimulation, but also collect information of nerves’ electrical activity in response to the stimulation.
Rune Labs will record electric signals from study patients’ nerves in the spinal cord and a brain region called the cortex. Since myelin is involved in the speed at which nerve signals are sent, these data will contain information relating to the myelination status of nerve cell fibers.
“By taking advantage of access to the spinal cord provided during routine clinical procedures, this study will capture precise neurophysiological data and measure myelination using a variety of evoked potentials,” said Ro’ee Gilron, PhD, Rune Labs’ lead neuroscientist.
Evoked potentials refer to the electrical response of a nerve cell in response to stimulation.
To find meaning in the data, Rune will use its AI-based neurology software platform to uncover activity patterns that can serve as biomarkers of a person’s degree of myelination. The software uses machine learning, a type of AI that learns how to accurately predict an outcome — in this case myelination — from a large collection of data.
“Rune’s AI platform enables us to take raw brain data and convert it into actionable biomarkers of myelination,” Gilron said.
The ultimate goal is to find biomarkers that will complement clinical scores like the EDSS in patient trials, providing more sensitive evaluations of a person’s disease status and the effectiveness of potential treatments.
If the approach is successful, it could help to accelerate therapy development for MS, Rune stated in the release.