Use of Artificial Intelligence to Identify New Mechanisms and Approaches to Therapy of Bone Disorders Associated With Chronic Kidney Disease

Adam E. Gaweda, Eleanor D. Lederer, Michael E. Brier

Research output: Contribution to journalReview articlepeer-review

Abstract

Chronic kidney disease (CKD) leads to clinically severe bone loss, resulting from the deranged mineral metabolism that accompanies CKD. Each individual patient presents a unique combination of risk factors, pathologies, and complications of bone disease. The complexity of the disorder coupled with our incomplete understanding of the pathophysiology has significantly hampered the ability of nephrologists to prevent fractures, a leading comorbidity of CKD. Much has been learned from animal models; however, we propose in this review that application of multiple techniques of mathematical modeling and artificial intelligence can accelerate our ability to develop relevant and impactful clinical trials and can lead to better understanding of the osteoporosis of CKD. We highlight the foundational work that informed our current model development and discuss the potential applications of our approach combining principles of quantitative systems pharmacology, model predictive control, and reinforcement learning to deliver individualized precision medical therapy of this highly complex disorder.

Original languageEnglish (US)
Article number807994
JournalFrontiers in Medicine
Volume9
DOIs
StatePublished - Mar 25 2022
Externally publishedYes

Keywords

  • artificial intelligence
  • chronic kidney disease
  • in silico clinical trials
  • mathematical modeling
  • osteoporosis

ASJC Scopus subject areas

  • Medicine(all)

Fingerprint

Dive into the research topics of 'Use of Artificial Intelligence to Identify New Mechanisms and Approaches to Therapy of Bone Disorders Associated With Chronic Kidney Disease'. Together they form a unique fingerprint.

Cite this