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Supervised Machine-Learning Reveals That Old and Obese People Achieve Low Dapsone Concentrations
- Source :
- CPT: Pharmacometrics & Systems Pharmacology. 6:552-559
- Publication Year :
- 2017
- Publisher :
- Wiley, 2017.
-
Abstract
- The human species is becoming increasingly obese. Dapsone, which is extensively used across the globe for dermatological disorders, arachnid bites, and for treatment of several bacterial, fungal and parasitic diseases, could be affected by obesity. We performed a clinical experiment, using optimal design, in volunteers weighing 44-150 kilograms, to identify the effect of obesity on dapsone pharmacokinetic parameters based on maximum-likelihood solution via the expectation-maximization algorithm. Artificial intelligence-based multivariate adaptive regression splines were used for covariate selection, and identified weight and/or age as predictors of absorption, systemic clearance and volume of distribution. These relationships occurred only between certain patient weight and age ranges, delimited by multiple hinges and regions of discontinuity, not identified by standard pharmacometric approaches. Older and obese people have lower drug concentrations after standard dosing, but with complex patterns. Given that efficacy is concentration-dependent, optimal dapsone doses need to be personalized for obese patients. This article is protected by copyright. All rights reserved.
- Subjects :
- 0301 basic medicine
Volume of distribution
Pediatrics
medicine.medical_specialty
Multivariate adaptive regression splines
business.industry
030106 microbiology
Dapsone
medicine.disease
Obesity
3. Good health
03 medical and health sciences
030104 developmental biology
Pharmacokinetics
Modeling and Simulation
Immunology
Covariate
medicine
Pharmacology (medical)
Dosing
Young adult
business
medicine.drug
Subjects
Details
- ISSN :
- 21638306
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- CPT: Pharmacometrics & Systems Pharmacology
- Accession number :
- edsair.doi...........492670fc610480ef00726b5118f7391c
- Full Text :
- https://doi.org/10.1002/psp4.12208