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Pharmacokinetics of meropenem in children receiving continuous renal replacement therapy: Validation of clinical trial simulations
Author(s) -
Nehus Edward J.,
Mizuno Tomoyuki,
Cox Shareen,
Goldstein Stuart L.,
Vinks Alexander A.
Publication year - 2016
Publication title -
the journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 116
eISSN - 1552-4604
pISSN - 0091-2700
DOI - 10.1002/jcph.601
Subject(s) - meropenem , renal replacement therapy , medicine , dosing , pharmacokinetics , volume of distribution , regimen , renal function , critically ill , anesthesia , loading dose , population , pharmacodynamics , pharmacology , antibiotics , chemistry , biochemistry , environmental health , antibiotic resistance
Meropenem is frequently prescribed in critically ill children receiving continuous renal replacement therapy (CRRT). We previously used clinical trial simulations to evaluate dosing regimens of meropenem in this population and reported that a dose of 20 mg/kg every 12 hours optimizes target attainment. Meropenem pharmacokinetics were investigated in this prospective, open‐label study to validate our previous in silico predictions. Seven patients received meropenem (13.8–22 mg/kg) administered intravenously every 12 hours as part of standard care. A mean dose of 18.6 mg/kg of meropenem was administered, resulting in a mean peak concentration of 80.1 μg/mL. Meropenem volume of distribution was 0.35 ± 0.085 L/kg. CRRT clearance was 40.2 ± 6.6 mL/(min · 1.73 m 2 ) and accounted for 63.4% of the total clearance of 74.8 ± 36.9 mL/(min · 1.73 m 2 ). Simulations demonstrated that a dose of 20 mg/kg every 12 hours resulted in a time above the minimum inhibitory concentration (% f T > MIC) of 100% in 5 out of 7 subjects, with a % f T > MIC of 93% and 43% in the remaining 2 subjects. We conclude that CRRT contributed significantly to the total clearance of meropenem. A dosing regimen of 20 mg/kg achieved good target attainment in critically ill children receiving CRRT, which is consistent with our previously published in silico predictions.