Evaluation of a System-Specific Function To Describe the Pharmacokinetics of Benzylpenicillin in Term Neonates Undergoing Moderate Hypothermia

评估系统特异性功能以描述接受中度低温治疗的足月新生儿体内苄青霉素的药代动力学

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Abstract

The pharmacokinetic (PK) properties of intravenous (i.v.) benzylpenicillin in term neonates undergoing moderate hypothermia after perinatal asphyxia were evaluated, as they have been unknown until now. A system-specific modeling approach was applied, in which our recently developed covariate model describing developmental and temperature-induced changes in amoxicillin clearance (CL) in the same patient study population was incorporated into a population PK model of benzylpenicillin with a priori birthweight (BW)-based allometric scaling. Pediatric population covariate models describing the developmental changes in drug elimination may constitute system-specific information and may therefore be incorporated into PK models of drugs cleared through the same pathway. The performance of this system-specific model was compared to that of a reference model. Furthermore, Monte-Carlo simulations were performed to evaluate the optimal dose. The system-specific model performed as well as the reference model. Significant correlations were found between CL and postnatal age (PNA), gestational age (GA), body temperature (TEMP), urine output (UO; system-specific model), and multiorgan failure (reference model). For a typical patient with a GA of 40 weeks, BW of 3,000 g, PNA of 2 days (TEMP, 33.5°C), and normal UO (2 ml/kg/h), benzylpenicillin CL was 0.48 liter/h (interindividual variability [IIV] of 49%) and the volume of distribution of the central compartment was 0.62 liter/kg (IIV of 53%) in the system-specific model. Based on simulations, we advise a benzylpenicillin i.v. dose regimen of 75,000 IU/kg/day every 8 h (q8h), 150,000 IU/kg/day q8h, and 200,000 IU/kg/day q6h for patients with GAs of 36 to 37 weeks, 38 to 41 weeks, and ≥42 weeks, respectively. The system-specific model may be used for other drugs cleared through the same pathway accelerating model development.

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