Cassie Mitchell Wins Prestigious NSF CAREER Award

<p><a href="http://pwp.gatech.edu/denislab/"><strong>Cassie S. Mitchell</strong></a>, assistant professor in the Coulter Department, has won a Faculty Early Career Development (CAREER) Award from the National Science Foundation.</p>

Cassie S. Mitchell, assistant professor in the Coulter Department, has won a Faculty Early Career Development (CAREER) Award from the National Science Foundation.

Cassie S. Mitchell, assistant professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University, and researcher in the Petit Institute for Bioengineering and Bioscience, has won a Faculty Early Career Development (CAREER) Award from the National Science Foundation.

The CAREER Award is the NSF’s most prestigious award in support of junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education, and the integration of education and research within the context of the mission of their organizations.

Mitchell’s award centers around her proposal titled “A systems engineering approach to elucidate and treat multi-factorial pathology.” The award includes $533,682 over five years to develop innovative and integrative data mining technologies that enable the elucidation of the etiology and treatment of multi-factorial diseases.

Millions of patients worldwide suffer from currently intractable multi-factorial diseases, which are diseases with no single cause but rather numerous contributing factors. Effectively measuring multiple simultaneous contributing factors throughout the disease course is extremely challenging in a traditional lab or clinical setting. The goal of her faculty CAREER award is to develop new complex computer models that integrate and simultaneously analyze data from thousands of scientific studies that examine individual disease factors measured in the lab or clinic.

The developed integrative computer models prioritize the most promising factors and develop optimal combination treatment strategies. Computer prioritization increases the likelihood of clinical trial success and expedites the rate of new treatment availability to patients. While this project focuses on predicting treatments for Alzheimer’s disease, frontotemporal dementia, and amyotrophic lateral sclerosis (ALS), the developed new technology can be applied to numerous other multi-factorial diseases.

Additional benefits to society include project-related outreach, such as professional training and mentoring for students with disabilities as part of the Georgia Tech ABLE Alliance co-founded and co-directed by Mitchell; community scientific education symposia for patients with multi-factorial neurologic diseases; innovative systems neuropathology and translational engineering undergraduate and graduate curricula; and a large STEM research internship program to provide research opportunities for 100 undergraduate and high school students.

“Multi-factorial diseases have dynamics that change over time. The specific goal is to construct dynamic models of multi-factorial neurologic disease to predict which factors or combinations of factors need to be treated and at what point in the disease course treatment should commence,” said Mitchell.

Mitchell’s project will utilize text mining, machine learning, and computational neuroscience to integrate thousands to millions of scientific studies into cohesive, dynamic models that prioritize etiological and treatment factors based on their system dynamics. The developed technology, data pipeline, and model architectures will be broadly applicable to all of biomedical science.

 

 

Media Contact:
Walter Rich
Communications Manager
Wallace H. Coulter Department of Biomedical Engineering
Georgia Institute of Technology

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Walter Rich