Title |
Pharmacokinetic and pharmacodynamic optimisation of intravenous tobramycin dosing among children with cystic fibrosis
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Published in |
Journal of Pharmacokinetics and Pharmacodynamics, January 2014
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DOI | 10.1007/s10928-013-9348-7 |
Pubmed ID | |
Authors |
Catherine M. T. Sherwin, Jeffery T. Zobell, Chris Stockmann, Bradley E. McCrory, Millie Wisdom, David C. Young, Jared Olson, Krow Ampofo, Michael G. Spigarelli |
Abstract |
This study aimed to characterize the pharmacokinetics of tobramycin administered one, two, or three times daily and to develop an optimal dosing scheme for children with cystic fibrosis. Therapeutic drug monitoring data were obtained from children hospitalized at three academic medical centres from 2006 to 2012. Population pharmacokinetic models were constructed using NONMEM 7.2. Model-based simulations were performed in Matlab R2012b to identify optimal dosing regimens using pharmacodynamic targets. The pharmacokinetic analysis involved 257 patients with a median age of 8.1 years (range 0.1-18.8). Clearance was estimated as 5.59 L/h and the volume of distribution was 18.90 L. Mean (±SD) maximum serum concentrations were highest among patients dosed once per day (24.1 ± 8.9 μg/mL) and were lower among patients dosed two and three times per day (11.2 ± 1.4 and 8.1 ± 2.4 μg/mL, respectively). Simulations revealed that once daily dosing was the only effective regimen for a Pseudomonas aeruginosa MIC of 1.5 μg/mL and none of the tested regimens reliably achieved the pharmacodynamic target for MICs ≥2 μg/mL. Once daily dosing resulted in higher maximum serum concentrations when compared to multiple-daily dosing. In simulations, once daily dosing was the only regimen to achieve the pharmacodynamic target for all subjects with MICs <2 μg/mL. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 1 | 3% |
Unknown | 38 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 7 | 18% |
Student > Master | 6 | 15% |
Student > Ph. D. Student | 5 | 13% |
Student > Doctoral Student | 3 | 8% |
Professor | 3 | 8% |
Other | 10 | 26% |
Unknown | 5 | 13% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 13 | 33% |
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 10% |
Biochemistry, Genetics and Molecular Biology | 3 | 8% |
Agricultural and Biological Sciences | 3 | 8% |
Immunology and Microbiology | 2 | 5% |
Other | 7 | 18% |
Unknown | 7 | 18% |