2024 - Rome - Italy

PAGE 2024: Drug/Disease Modelling - Paediatrics
Anne van Rongen

The impact of being born Small for Gestational Age (SGA) on the clearance of vancomycin versus morphine and midazolam

Anne van Rongen (1), Madelein E. Nuis (1), Runyi Ma (1), Karel Allegaert (2,3,4), Swantje Völler (1), Anne Smits (3,6), Robert B. Flint (4,7), Saskia N. de Wildt (7,8), Dick Tibboel (9), Sinno H.P. Simons (7), Elke H.J. Krekels (1,5), Catherijne A.J. Knibbe (1,7,10)

(1) Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands; (2) Department of Development and Regeneration, KU Leuven, Leuven, Belgium; (3) Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium; (4) Department of Hospital Pharmacy, Erasmus MC, Rotterdam, The Netherlands; (5) Certara Inc, Princeton, NJ, USA; (6) Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium; (7) Department of Pediatrics, Division of Neonatology, Erasmus MC-Sophia Children’s Hospital, Rotterdam, The Netherlands; (8) Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands; (9) Department of Pediatric Surgery, Erasmus University MC-Sophia Children's Hospital, Rotterdam, The Netherlands; (10) Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands

Objectives: The pharmacokinetics (PK) of drugs in neonates vary widely due to differences in gestational age (GA), birth bodyweight (bBW), and/or postnatal age (PNA). The combination of bBW or GA together with PNA is often the best predictor for drug clearance (CL) in neonates, where bBW or GA is reflecting the antenatal maturation and PNA the postnatal maturation [1,2]. A specific group of newborns, those that are born small for gestational age (SGA), i.e., neonates with a bBW less than the 10th percentile of the bBW for their GA, have been largely ignored in these PK studies. The aim of this study is to determine the influence of being born SGA on the CL of the renally cleared drug vancomycin and the hepatically cleared drugs morphine (UGT2B7) and midazolam (CYP3A) in neonates. 

Methods: We used the raw data of published population PK studies, including data of 437 preterm and term neonates treated with vancomycin, 154 preterm and term neonates and infants up to 98 days of age treated with morphine, and 57 preterm neonates and infants up to 108 days of age treated with midazolam [3–9]. Using Fenton growth charts, 100 (22.9%), 32 (20.8%), and 9 (15.8%) neonates were identified as SGA for the vancomycin, morphine and midazolam dataset, respectively [10]. For all three drugs, published PK models were taken from literature [11–14], i.e., for vancomycin and midazolam a two and one compartment model were used, respectively [11,12] and for morphine and morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G), a two- and one compartment model was used, respectively [13,14]. Volume of distribution increased with current bodyweight (cBW) in a power function with estimated exponent for vancomycin and midazolam and a linear function with cBW for morphine and metabolites [11–14]. A covariate analysis was performed in NONMEM 7.5, in which various functions (linear and power) were tested to describe antenatal and postnatal maturation based on bBW, cBW, GA, and PNA. The remaining influence of SGA was tested in the developed covariate models. For forward inclusion of covariates, a ΔOFV of -6.6 (p < 0.01) was taken and for backward exclusion ΔOFV of 10.8 (p < 0.001). In addition, GOF plots split for the different covariates and ETA and CWRES plots versus covariates were constructed to examine any remaining trends after inclusion of the covariates. 

Results: 

For the three drugs, inter-individual variability in all CL values was best described by a combination of bBW and PNA compared to GA and PNA. For vancomycin, bBW in a power function and PNA in a linear function was identified. For midazolam, a power function was found for both bBW and PNA. For morphine, different typical values were estimated for the formation and elimination CL of M3G and M6G, while the same covariate relationships were found for both M3G and M6G (i.e., power function for bBW and linear for PNA). SGA was a significant covariate for vancomycin CL with its influence depending on the combination of other covariates in the model. In the covariate model with bBW and PNA, CL was 30% higher in SGA neonates compared to appropriate for gestational age (AGA) neonates. Within the context of a model with GA and PNA, vancomycin CL was 28% lower in SGA compared to AGA neonates. Contrary to vancomycin, SGA was not identified as a covariate for midazolam CL neither in the covariate model with bBW and PNA nor in the model with GA and PNA. For the formation and elimination CL of M3G and M6G, SGA was not a covariate in the bBW and PNA model. Within the context of a model with GA and PNA for the formation and elimination of M3G and M6G, the formation clearance of M3G was 28% lower in SGA compared to AGA neonates, however the performance of this covariate model was significantly worse than the model with bBW and PNA.  

Conclusions: 

Being born SGA has an impact on the CL of the renally cleared drug vancomycin in neonates, with an increase of 30% in comparison to AGA neonates of the same bBW. When GA is used as covariate for antenatal maturation instead of bBW, CL is 28% decreased in SGA neonates compared to AGA neonates. For the hepatically cleared drugs morphine and midazolam, being born SGA has no influence on CL for neonates of the same bBW. Contrary to vancomycin CL, the renal excretion of M3G and M6G is not influenced by SGA, which can potentially be explained by the influence of renal transporters on morphine glucuronides.



References:

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  2. Salem F et al. J Clin Pharmacol. 2021;61(2):159–71.
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  10. Fenton TR et al. BMC Pediatr. 2013 Apr;13:59.
  11. De Cock RFW et al. Pharm Res. 2014;31(3):754–67.
  12. Völler S et al. J Clin Pharmacol. 2019 Oct;59(10):1300–8.
  13. Knibbe CAJ et al. Clin Pharmacokinet. 2009;48(6):371–85.
  14. Krekels EHJ et al. Clin Pharmacokinet. 2011 Jan;50(1):51–63.


Reference: PAGE 32 (2024) Abstr 11244 [www.page-meeting.org/?abstract=11244]
Poster: Drug/Disease Modelling - Paediatrics
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