Founder and Scientific Director, Cleveland Clinic Consortium for Pain
Location: Cleveland Clinic Main Campus
Chronic (long-term) pain is one of the most widespread, costly and disabling health conditions in the United States. Musculoskeletal pain, the most common type of chronic pain, is especially devastating; healthcare costs for chronic low back pain are estimated at $100 billion a year.
Our research is based on new scientific findings showing that pain is controlled by the brain. Therefore, our main goal is to define the brain networks that govern pain, through non-invasive brain imaging and analysis of patient data. This will allow for better diagnosis of patients with pain, and will enable healthcare professionals to treat patients earlier to prevent long-term pain, disability and opioid use.
I am the director of the Pain Science Technology and Research (STAR) Lab, whose mission is to foster collaboration between clinicians and researchers to develop, test and validate novel technologies and methods to diagnose and treat chronic pain.
We seek to define traffic patterns between brain networks underlying sensory experiences.
Our research transcends the textbook drawings of static, Cartesian neuroanatomical wiring.
Our research team at Cleveland Clinic and Brown University uses electrophysiological, optogenetic and computational techniques to identify objective biosignatures of pain across species.
As part of a multi-PI collaboration with Brown University, we're building new technologies and platforms that will lead to new insights into network dynamics giving rise to sensory perception in health and disease, as well as more effective treatment and diagnosis of debilitating pain.
Our research program is guided by the scientific premise that sensory and emotional states are governed by neural circuits. Our main goal is to elucidate and map these circuits with unprecedented cellular specificity and temporal resolution, using multidisciplinary research tools such as optogenetics, self-report behavioral paradigms, and high-density (>200 units) neural recordings in vivo across the spine-brain continuum. Basic science discoveries are then translated to biomedical applications in collaboration with healthcare partners, using non-invasive brain imaging and machine learning.
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Dr. Saab and his team are exploring a new, more objective way to diagnose pain that is rapid, less expensive and provides more accurate results.