One group is working on deep brain stimulation methods to treat motor symptoms. Two groups are focusing on freezing of gait (FOG), a symptom of Parkinson’s – one using computer vision to measure FOG, another using spinal cord stimulation to treat it. And another team is trying to better understand the erratic, involuntary movements many 80-90 percent of Parkinson’s patients experience as a side effect of L-DOPA, the most common treatment for the disease.
Principal investigator Ellen Hess, professor of pharmacology and chemistry in Emory’s School of Medicine, is collaborating with BME Assistant Professor Chethan Pandarinath on idenfitying the neuron activity related to L-DOPA-induced-dyskinesias, or LID.
“After we identify the abnormal firing patterns, we hope to use that information to lead us to therapeutics that nudge the firing patterns back to normal to alleviate the LIDS while still allowing patients to experience the beneficial effects of L-DOPA,” said Hess, whose team will use a deep learning method developed by Pandrarinath’s lab. “It is a unique system and really the only way that we could accomplish our goals,” she added.
Other teams are developing algorithms to optimize electrical brain stimulation and medication dosages, biofeedback devices to help Parkinson’s patients better communicate through vocal therapy, and wearable technology to continuously monitor patients’ cardiac activity and blood pressure.
And sometimes the research involves reapplying an established technology to a slightly different task. For example, the project being led by Cassie Mitchell will build on her lab’s successful text mining platform for identifying repurposed drugs for Covid-19.
“We’ll use predictive medicine techniques with machine learning, network pathology dynamics, and large-scale text mining of millions of journal articles,” said Mitchell, whose team received a $40,000 award.
Her goal is to personalize and optimize diagnostic and treatment protocols. Mitchell and her co-investigators will build a data network and text mining foundation for making prioritized predictions for Parkinson’s and Parkinson’s-like disorders.
“Future projects based on this work will deliver clinically translational diagnostic algorithms, repurposed drugs or new therapeutic targets, and new personalized treatment recommendation systems,” said Mitchell, whose lab has specialized in predictive medicine for multi-factorial neurological disease in the past. “We’re excited and grateful to expand our work to Parkinson’s and Parkinsonian disorders.”