Arjun P. Athreya, Ph.D., M.S., develops novel methodologies and tools that embody innovations in artificial intelligence and machine learning that aid in translational research and clinical decision-making. His research combines patient data relating to genomics, metabolomics, imaging and electronic health records to identify biomarkers of disease biology (discovery science), drug response (clinical science) or both.
Particularly, the technologies developed by Dr. Athreya are to be used as means of augmenting physicians' decision-making abilities. These technologies aid in optimizing treatment selection and treatment management to ensure that patients get the treatment with the highest likelihood of delivering the therapeutic benefit with minimized chances of side effects.
- Artificial intelligence
- Data science
Significance to patient care
In many fields of medicine, such as psychiatry and rheumatology, treatment selection is still on a trial-and-error basis, thus relying heavily on clinicians' expertise. Thus, treatment failures bring added disease burden for patients and increase the cost of care.
Using artificial intelligence and high volumes of patient data, Dr. Athreya is able to prioritize treatment selection based on therapeutic efficacy specific to the patient, and individualize treatment management based on specific symptom improvement after treatment initiation. Thus, the guessing involved in the trial-and-error practice of treating patients is dramatically minimized by starting patients on more optimized therapy and knowing when to switch treatment should early changes in symptom severity prognosticate a poor outcome in the long term.
- Recipient, Presidential Trainee Award, American Society of Clinical Pharmacology and Therapeutics, 2017-2019
- Fellow, Mayo Clinic, Illinois Healthcare Alliance, 2016-2018
- Recipient, Best Paper Award, IEEE CIBCB, 2017
- Recipient, Jason Morrow Memorial Award, American Society of Clinical Pharmacology and Therapeutics, 2017
- Recipient, Rambus Computer Engineering Fellowship, Department of Electrical and Computer Engineering, University of Illinois, 2017
- Recipient, Travel Award, IEEE Computational Intelligence Society, 2017
- Named, Mayo Clinic Early Career Scholar in Precision Medicine, 2016
- Recipient, Best Paper Award, IEEE/ACM BDCAT, 2016
- Recipient, Best Student Presentation Award, Coordinated Science Lab Student Conference, 2016
- Fellow, National Center for Supercomputing Applications and CompGen, 2015-2016
- Recipient, Best Student Paper Award, IEEE CCNC, 2014
- Fellow, Carnegie Institute of Technology Dean's Fellowship, Carnegie Mellon University, 2011-2013