Frontiers in Artificial Intelligence (Sep 2022)

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

  • Aleksandra Foksinska,
  • Camerron M. Crowder,
  • 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,
  • William E. Byrd,
  • Mei-Jan Chen,
  • Andrew B. Crouse,
  • Camerron M. Crowder,
  • Mary E. Crumbley,
  • Madeline Eckenrode,
  • Crayton A. Fargason,
  • Nathaniel Fehrmann,
  • Aleksandra Foksinska,
  • Kaiwen He,
  • Forest Huls,
  • Matthew Jarrell,
  • Lindsay Jenkins,
  • Meg McCalley,
  • Matthew Might,
  • Tamsyn Osborn,
  • Michael J. Patton,
  • Elizabeth Pollard,
  • Gregory Rosenblatt,
  • Sienna Rucka,
  • Nicholas T. Southern,
  • Thi K. Tran-Nguyen,
  • Jillian Tinglin,
  • Jordan H. Whitlock

DOI
https://doi.org/10.3389/frai.2022.910216
Journal volume & issue
Vol. 5

Abstract

Read online

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.

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