title: Population pharmacokinetics of fluconazole in young infants.
abstract: Fluconazole is being increasingly used to prevent and treat invasive candidiasis in neonates, yet dosing is largely empirical due to the lack of adequate pharmacokinetic (PK) data. We performed a multicenter population PK study of fluconazole in 23- to 40-week-gestation infants less than 120 days of age. We developed a population PK model using nonlinear mixed effect modeling (NONMEM) with the NONMEM algorithm. Covariate effects were predefined and evaluated based on estimation precision and clinical significance. We studied fluconazole PK in 55 infants who at enrollment had a median (range) weight of 1.02 (0.440 to 7.125) kg, a gestational age at birth (BGA) of 26 (23 to 40) weeks, and a postnatal age (PNA) of 2.3 (0.14 to 12.6) weeks. The final data set contained 357 samples; 217/357 (61%) were collected prospectively at prespecified time intervals, and 140/357 (39%) were scavenged from discarded clinical specimens. Fluconazole population PK was best described by a one-compartment model with covariates normalized to median values. The population mean clearance (CL) can be derived for this population by the equation CL (liter/h) equals 0.015 . (weight/1)(0.75) . (BGA/26)(1.739) . (PNA/2)(0.237) . serum creatinine (SCRT)(-4.896) (when SCRT is >1.0 mg/dl), and using a volume of distribution (V) (liter) of 1.024 . (weight/1). The relative standard error around the fixed effects point estimates ranged from 3 to 24%. CL doubles between birth and 28 days of age from 0.008 to 0.016 and from 0.010 to 0.022 liter/kg/h for typical 24- and 32-week-gestation infants, respectively. This population PK model of fluconazole discriminated the impact of BGA, PNA, and creatinine on drug CL. Our data suggest that dosing in young infants will require adjustment for BGA and PNA to achieve targeted systemic drug exposures.
authors.affiliation: Department of Pediatrics, Division of Neonatology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania 19104, USA. wade@email.chop.edu
authors.forename: K C
authors.initials: KC
authors.lastname: Wade
authors.forename: D
authors.initials: D
authors.lastname: Wu
authors.forename: D A
authors.initials: DA
authors.lastname: Kaufman
authors.forename: R M
authors.initials: RM
authors.lastname: Ward
authors.forename: D K
authors.initials: DK
authors.lastname: Benjamin
authors.forename: J E
authors.initials: JE
authors.lastname: Sullivan
authors.forename: N
authors.initials: N
authors.lastname: Ramey
authors.forename: B
authors.initials: B
authors.lastname: Jayaraman
authors.forename: K
authors.initials: K
authors.lastname: Hoppu
authors.forename: P C
authors.initials: PC
authors.lastname: Adamson
authors.forename: M R
authors.initials: MR
authors.lastname: Gastonguay
authors.forename: J S
authors.initials: JS
authors.lastname: Barrett
mesh_terms: D000367:Age Factors; D000465:Algorithms; D000935:Antifungal Agents / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D002177:Candidiasis / Q000097:blood / Q000188:drug therapy / Q000517:prevention & control; D003404:Creatinine / Q000097:blood; D004305:Dose-Response Relationship, Drug; D005260:Female; D015725:Fluconazole / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007234:Infant, Premature; D008297:Male; D008657:Metabolic Clearance Rate; D008954:Models, Biological; D009010:Monte Carlo Method; D017711:Nonlinear Dynamics; D011446:Prospective Studies
chemical_list: D000935:Antifungal Agents; D015725:Fluconazole; D003404:Creatinine