1. Limited Sampling Strategies Using Linear Regression and the Bayesian Approach for Therapeutic Drug Monitoring of Moxifloxacin in Tuberculosis Patients
- Author
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Charles A. Peloquin, John L. Johnson, Daan J Touw, Tjip S. van der Werf, Marieke G G Sturkenboom, Katerina Manika, Onno W. Akkerman, Jan-Willem C. Alffenaar, Simone H J van den Elsen, Ioannis Kioumis, Microbes in Health and Disease (MHD), Biopharmaceuticals, Discovery, Design and Delivery (BDDD), Groningen Research Institute for Asthma and COPD (GRIAC), Critical care, Anesthesiology, Peri-operative and Emergency medicine (CAPE), Pharmaceutical Analysis, and Medicinal Chemistry and Bioanalysis (MCB)
- Subjects
Male ,Moxifloxacin ,Antitubercular Agents ,030226 pharmacology & pharmacy ,0302 clinical medicine ,Levofloxacin ,Pharmacology (medical) ,LEVOFLOXACIN ,0303 health sciences ,education.field_of_study ,RESISTANT TUBERCULOSIS ,medicine.diagnostic_test ,RIFAMPICIN ,Regression analysis ,Middle Aged ,POPULATION PHARMACOKINETICS ,Infectious Diseases ,SAFETY ,Area Under Curve ,Drug Therapy, Combination ,Female ,MYCOBACTERIUM-TUBERCULOSIS ,Drug Monitoring ,Rifampin ,medicine.drug ,Adult ,medicine.medical_specialty ,therapeutic drug monitoring ,Population ,Clinical Therapeutics ,03 medical and health sciences ,Pharmacokinetics ,Internal medicine ,Linear regression ,medicine ,Humans ,Tuberculosis ,education ,Pharmacology ,030306 microbiology ,business.industry ,Reproducibility of Results ,Bayes Theorem ,drug interactions ,sampling strategy ,IN-VITRO ,AMIKACIN ,MODEL ,Standard error ,QTC ,Therapeutic drug monitoring ,Linear Models ,business - Abstract
Therapeutic drug monitoring (TDM) of moxifloxacin is recommended to improve the response to tuberculosis treatment and reduce acquired drug resistance. Limited sampling strategies (LSSs) are able to reduce the burden of TDM by using a small number of appropriately timed samples to estimate the parameter of interest, the area under the concentration-time curve. This study aimed to develop LSSs for moxifloxacin alone (MFX) and together with rifampin (MFX+RIF) in tuberculosis (TB) patients. Population pharmacokinetic (popPK) models were developed for MFX (n = 77) and MFX+RIF (n = 24). In addition, LSSs using Bayesian approach and multiple linear regression were developed. Jackknife analysis was used for internal validation of the popPK models and multiple linear regression LSSs. Clinically feasible LSSs (one to three samples, 6-h timespan postdose, and 1-h interval) were tested. Moxifloxacin exposure was slightly underestimated in the one-compartment models of MFX (mean -5.1%, standard error [SE] 0.8%) and MFX+RIF (mean -10%, SE 2.5%). The Bayesian LSSs for MFX and MFX+RIF (both 0 and 6 h) slightly underestimated drug exposure (MFX mean -4.8%, SE 1.3%; MFX+RIF mean -5.5%, SE 3.1%). The multiple linear regression LSS for MFX (0 and 4 h) and MFX+RIF (1 and 6 h), showed mean overestimations of 0.2% (SE 1.3%) and 0.9% (SE 2.1%), respectively. LSSs were successfully developed using the Bayesian approach (MFX and MFX+RIF; 0 and 6 h) and multiple linear regression (MFX, 0 and 4h; MFX+RIF, 1 and 6h). These LSSs can be implemented in clinical practice to facilitate TDM of moxifloxacin in TB patients.
- Published
- 2019
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