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Cited by 18Parathyroid Disorders and TreatmentsArtificial Intelligence in Healthcare and EducationDialysis and Renal Disease Management

Artificial intelligence–guided precision treatment of chronic kidney disease–mineral bone disorder

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Gaweda, Adam E., Lederer, Eleanor D., Brier, Michael E.·2022·CPT: Pharmacometrics & Systems Pharmacology
DOI 10.1002/psp4.12843PMC PMC9574726
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Abstract

Chronic kidney disease (CKD)–mineral bone disorder (MBD) is a complex clinical syndrome that begins early during CKD and evolves into one of the deadliest complications of CKD through its effects on the cardiovascular and skeletal systems. Achievement of treatment goals to decrease the risk of accelerated cardiovascular events and fractures has been challenging. We hypothesized that application of quantitative systems pharmacology (QSP) modeling combined with artificial intelligence techniques could improve the management of CKD–MBD with the goal of improving outcomes for patients with CKD. We present the implementation of a reinforcement learning (RL) approach to achieve the prescribed goals for serum calcium, phosphorus, and parathyroid hormone through concurrent dosing of phosphate binders, vitamin D analogs, and calcimimetics by simulation in 80 subjects in Matlab. In silico simulation results demonstrate that the application of a QSP model coupled with RL more effectively and quickly achieves treatment goals even in the setting of inferior simulated subject compliance with medical therapy and identifies key decision variables for therapeutic recommendations.

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Sorted by citations

Authors
Gaweda, A. E., Lederer, E. D., & Brier, M. E.
Affiliations
  • Division of Nephrology, Department of Medicine University of Louisville School of Medicine Louisville Kentucky USA
  • VA North Texas Health Care System (US)
  • University of Louisville (US)
Corresponding author
Lederer, Eleanor D.
ORCID
Venue
CPT: Pharmacometrics & Systems Pharmacology
Publisher
Wiley
Published
2022-08-03
Volume
11
Issue
10
Pages
1305-1315
ISSN
2163-8306 (ISSN-L)
DOI
10.1002/psp4.12843
PMC
PMC9574726
OpenAlex
W4289711169
Cited by
18
References
1
Citations by year
2026: 4 · 2025: 6 · 2024: 5 · 2023: 2 · 2022: 1
FWCI
2.22
Type
journal article
Language
en
Open access
Licence
Locations
  • CPT Pharmacometrics & Systems Pharmacology (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
U.S. Department of Veterans Affairs (CX001614)
Topics
  • Health Sciences › Medicine › Nephrology › Parathyroid Disorders and Treatments
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Medicine › Nephrology › Dialysis and Renal Disease Management
Keywords
chronic kidney disease-mineral bone disorder, artificial intelligence, reinforcement learning, quantitative systems pharmacology, phosphate binders, vitamin D analogs, calcimimetics, serum calcium, serum phosphorus, parathyroid hormone, treatment goal attainment, medication adherence, cardiovascular risk, fracture risk
MeSH terms
Artificial Intelligence, Calcium, Humans, Minerals, Parathyroid Hormone, Phosphates, Phosphorus, Vitamin D, Renal Insufficiency, Chronic

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