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The precision medicine process for treating rare disease using the artificial intelligence tool mediKanren

Authors :
Aleksandra Foksinska
Camerron M. Crowder
Andrew B. Crouse
Jeff Henrikson
William E. Byrd
Gregory Rosenblatt
Michael J. Patton
Kaiwen He
Thi K. Tran-Nguyen
Marissa Zheng
Stephen A. Ramsey
Nada Amin
John Osborne
UAB Precision Medicine Institute
Matthew Might
Stephen Barnes
Mei-Jan Chen
Mary E. Crumbley
Madeline Eckenrode
Crayton A. Fargason
Nathaniel Fehrmann
Forest Huls
Matthew Jarrell
Lindsay Jenkins
Meg McCalley
Tamsyn Osborn
Elizabeth Pollard
Sienna Rucka
Nicholas T. Southern
Jillian Tinglin
Jordan H. Whitlock
Source :
Frontiers in Artificial Intelligence, Vol 5 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

There are over 6,000 different rare diseases estimated to impact 300 million people worldwide. As genetic testing becomes more common practice in the clinical setting, the number of rare disease diagnoses will continue to increase, resulting in the need for novel treatment options. Identifying treatments for these disorders is challenging due to a limited understanding of disease mechanisms, small cohort sizes, interindividual symptom variability, and little commercial incentive to develop new treatments. A promising avenue for treatment is drug repurposing, where FDA-approved drugs are repositioned as novel treatments. However, linking disease mechanisms to drug action can be extraordinarily difficult and requires a depth of knowledge across multiple fields, which is complicated by the rapid pace of biomedical knowledge discovery. To address these challenges, The Hugh Kaul Precision Medicine Institute developed an artificial intelligence tool, mediKanren, that leverages the mechanistic insight of genetic disorders to identify therapeutic options. Using knowledge graphs, mediKanren enables an efficient way to link all relevant literature and databases. This tool has allowed for a scalable process that has been used to help over 500 rare disease families. Here, we provide a description of our process, the advantages of mediKanren, and its impact on rare disease patients.

Details

Language :
English
ISSN :
26248212
Volume :
5
Database :
Directory of Open Access Journals
Journal :
Frontiers in Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
edsdoj.fb0ce485144f31abd3b657a1dff8e1
Document Type :
article
Full Text :
https://doi.org/10.3389/frai.2022.910216