Maturation of the Glomerular Filtration Rate in Neonates, as Reflected by Amikacin Clearance

During the newborn period and early infancy, renal function matures, resulting in changes in the glomerular filtration rate (GFR). This study was performed to quantify developmental changes in the GFR in (pre)term neonates by use of amikacin clearance as proof of concept. The model was used to derive a rational dosing regimen in comparison with currently used dosing regimens for amikacin. Methods Population pharmacokinetic modelling was performed in nonlinear mixed-effect modelling software (NONMEM version 6.2) using data from 874 neonates obtained from two previously published datasets (gestational age 24–43 weeks; postnatal age 1–30 days; birthweight 385–4650 g). The influence of different age-related, weight-related and other covariates was investigated. The model was validated both internally and externally. Results Postmenstrual age was identified as the most significant covariate on clearance. However, the combination of birthweight and postnatal age proved to be superior to postmenstrual age alone. Birthweight was best described using an allometric function with an exponent of 1.34. Postnatal age was identified using a linear function with a slope of 0.2, while co-administration of ibuprofen proved to be a third covariate. Current bodyweight was the most important covariate for the volume of distribution, using an allometric function. The external evaluation supported the prediction of the final pharmacokinetic model. This analysis illustrated clearly that the currently used dosing regimens for amikacin in reference handbooks may possibly increase the risk of toxicities and should be revised. Consequently, a new model-based dosing regimen based on current bodyweight and postnatal age was derived. Conclusions Amikacin clearance, reflecting the GFR in neonates, can be predicted by birthweight representing the antenatal state of maturation of the kidney, postnatal age representing postnatal maturation, and co-administration of ibuprofen. Finally, the model reflects maturation of the GFR, allowing for adjustments of dosing regimens for other renally excreted drugs in preterm and term neonates

Maturation of the Glomerular Filtration Rate in Neonates, as Reflected by Amikacin Clearance

During the newborn period and early infancy, renal function matures, resulting in changes in the glomerular filtration rate (GFR). This study was performed to quantify developmental changes in the GFR in (pre)term neonates by use of amikacin clearance as proof of concept. The model was used to derive a rational dosing regimen in comparison with currently used dosing regimens for amikacin. Methods Population pharmacokinetic modelling was performed in nonlinear mixed-effect modelling software (NONMEM version 6.2) using data from 874 neonates obtained from two previously published datasets (gestational age 24–43 weeks; postnatal age 1–30 days; birthweight 385–4650 g). The influence of different age-related, weight-related and other covariates was investigated. The model was validated both internally and externally. Results Postmenstrual age was identified as the most significant covariate on clearance. However, the combination of birthweight and postnatal age proved to be superior to postmenstrual age alone. Birthweight was best described using an allometric function with an exponent of 1.34. Postnatal age was identified using a linear function with a slope of 0.2, while co-administration of ibuprofen proved to be a third covariate. Current bodyweight was the most important covariate for the volume of distribution, using an allometric function. The external evaluation supported the prediction of the final pharmacokinetic model. This analysis illustrated clearly that the currently used dosing regimens for amikacin in reference handbooks may possibly increase the risk of toxicities and should be revised. Consequently, a new model-based dosing regimen based on current bodyweight and postnatal age was derived. Conclusions Amikacin clearance, reflecting the GFR in neonates, can be predicted by birthweight representing the antenatal state of maturation of the kidney, postnatal age representing postnatal maturation, and co-administration of ibuprofen. Finally, the model reflects maturation of the GFR, allowing for adjustments of dosing regimens for other renally excreted drugs in preterm and term neonates

Low but inducible contribution of renal elimination to clearance of propylene glycol in preterm and term neonates

BACKGROUND: Despite limited information being available on the pharmacokinetics of excipients, propylene glycol (PG) is often used as an excipient in both adults and children. The aim of this study is to characterize the renal and hepatic elimination of PG in preterm and term neonates. METHODS: The pharmacokinetic analysis of PG was performed in NONMEM 6.2. on the basis of PG concentrations in plasma and/or urine samples for a total of 69 (pre)term neonates (birth weight 630-3980 g, gestational age 24-41 weeks, postnatal age 1-29 days) who received PG coadministered with intravenous paracetamol (5-10 mg/kg per 6 hours), phenobarbital (5 mg·kg·d), or both. To capture the time-dependent trend in the renal excretion of PG, different models based on time after the first dose, urine volume, and creatinine amount in urine were tested. RESULTS:A one-compartment model parameterized in terms of renal clearance, hepatic clearance, and volume of distribution was found to adequately describe the observations in both plasma and urine. After the first dose was administered, the renal elimination of PG was 15% of total clearance, which increased over time to 25% at 24 hours after the first dose of PG. This increase was best described using a hyperbolic function based on time after the first dose. CONCLUSIONS:Renal elimination of PG in (pre)term neonates is low, particularly compared with the reported percentage of 45% in adults, but it may increase with time after the first dose of PG. To study whether this increase is caused by an autoinduced increase in the renal secretion or a reduction of tubular reabsorption of PG, further research is needed.</p

Maturation of GFR in Preterm and Term Neonates Reflected by Clearance of Different Antibiotics

Objectives: Throughout infancy, renal function matures resulting in differences in glomerular filtration rate (GFR) at different stages of development. These developmental changes in GFR were previously quantified in (pre)term neonates aged up to 1 month on the basis of the clearance of amikacin. In this developmental renal excretion model (1), the maturation of GFR was predicted by birth weight (BWb) and postnatal age (PNA). The aim of this study is to assess model performance when this developmental renal excretion model (1) is used to describe maturation in clearance of other renally excreted antibiotics in (pre)term neonates. Using this approach a distinction is being made between system specific and drug specific information in paediatric pharmacokinetic models. Methods: For the netilmicin dataset, 386 netilmicin concentrations were available from 97 (pre)term neonates (BWb 470-3000 g, PNA 1-30 days)(2). The vancomycin dataset contained 752 vancomycin concentrations from 273 preterm neonates (BWb 385-2550 g, PNA 1-30 days)(3). A pharmacokinetic model was developed for both netilmicin or vancomycin using the developmental renal excretion model for amikacin clearance in neonates (1): CLi=CLp*{((BWb/BWBmedian)^1.34)*(1+0.213*(PNA/PNAmedian))} Using this approach, CLp is considered a drug specific property and was therefore estimated for each of the drugs separately. The remaining information in this equation is considered system specific information which can be applied for all renally excreted drugs. The descriptive and predictive performance of models developed using the developmental renal excretion model (1) were compared with comprehensive covariate models (4) for netilmicin or vancomycin respectively, by evaluation of the objective function (OFV), basic goodness-of-fit plots, NPDE and the individual and population parameter estimates versus most predictive covariate (4). Results: The descriptive and predictive properties of the models developed using the developmental renal excretion model, were similar compared to the comprehensive covariate models for basic goodness-of-fit plots and NPDE. In agreement the models that were developed using the developmental renal excretion model, in the comprehensive covariate models BWb and PNA were identified as most predictive covariates for clearance. The comprehensive covariate models had only a slightly lower objective function (netilmicin p\u3c0.05, vancomycin p\u3c0.001) compared to the models using the developmental renal excretion model. Conclusions: Use of the developmental renal excretion model quantifying maturation in GFR mediated amikacin clearance for the analysis of netilmicin and vancomycin clearance in neonates, results in adequate descriptive and predictive performance. We conclude that the application of system specific information may lead to optimization of sparse data analysis in children

Maturation in GFR in Preterm Neonates Reflected by Clearance of Different Antibiotics

(1) Division of Pharmacology, LACDR, Leiden University, Leiden, the Netherlands (2) Neonatal Intensive Care Unit, University Hospital Leuven, Leuven, Belgium (3) Division of Clinical Pharmacology & Clinical Trials Office Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT,USA (4) Department of Pediatric Intensive Care, Erasmus MC - Sophia Children’s Hospital, Rotterdam, The Netherlands (5) Division of Pediatric Clinical Pharmacology, Children’s National Medical Center, Washington, DC, USA (6) Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands Objectives: Throughout infancy, renal function matures resulting in differences in glomerular filtration rate (GFR) at different stages of development. These developmental changes in GFR were previously quantified in (pre)term neonates aged up to 1 month on the basis of the clearance of amikacin. In this developmental renal excretion model (1), the maturation of GFR was predicted by birth weight (BWb) and postnatal age (PNA). The aim of this study is to assess model performance when this developmental renal excretion model (1) is used to describe maturation in clearance of other renally excreted antibiotics in (pre)term neonates. Using this approach a distinction is being made between system specific and drug specific information in paediatric pharmacokinetic models. Methods: For the netilmicin dataset, 386 netilmicin concentrations were available from 97 (pre)term neonates (BWb 470-3000 g, PNA 1-30 days)(2). The vancomycin dataset contained 752 vancomycin concentrations from 273 preterm neonates (BWb 385-2550 g, PNA 1-30 days)(3). A pharmacokinetic model was developed for both netilmicin or vancomycin using the developmental renal excretion model for amikacin clearance in neonates (1): CLi=CLp*{((BWb/BWBmedian)^1.34)*(1+0.213*(PNA/PNAmedian))} Using this approach, CLp is considered a drug specific property and was therefore estimated for each of the drugs separately. The remaining information in this equation is considered system specific information which can be applied for all renally excreted drugs. The descriptive and predictive performance of models developed using the developmental renal excretion model (1) were compared with comprehensive covariate models (4) for netilmicin or vancomycin respectively, by evaluation of the objective function (OFV), basic goodness-of-fit plots, NPDE and the individual and population parameter estimates versus most predictive covariate (4). Results: The descriptive and predictive properties of the models developed using the developmental renal excretion model, were similar compared to the comprehensive covariate models for basic goodness-of-fit plots and NPDE. In agreement the models that were developed using the developmental renal excretion model, in the comprehensive covariate models BWb and PNA were identified as most predictive covariates for clearance. The comprehensive covariate models had only a slightly lower objective function (netilmicin p\u3c0.05, vancomycin p\u3c0.001) compared to the models using the developmental renal excretion model. Conclusions: Use of the developmental renal excretion model quantifying maturation in GFR mediated amikacin clearance for the analysis of netilmicin and vancomycin clearance in neonates, results in adequate descriptive and predictive performance. We conclude that the application of system specific information may lead to optimization of sparse data analysis in children. References: [1] De Cock et al PAGE 19 (2010); abstract 1900, available from [www.page-meeting.org/?abstract=1900] [2] Sherwin, C.M., Broadbent, R.S., Medlicott, N.J. & Reith, D.M. Individualising netilmicin dosing in neonates. Eur J Clin Pharmacol 64, 1201-8 (2008). [3] Allegaert, K., Anderson, B.J., van den Anker, J.N., Vanhaesebrouck, S. & de Zegher, F. Renal drug clearance in preterm neonates: relation to prenatal growth. Ther Drug Monit 29, 284-91 (2007). [4] Krekels, E.H., van Hasselt, J.G., Tibboel, D., Danhof, M. & Knibbe, C.A. Systematic Evaluation of the Descriptive and Predictive Performance of Paediatric Morphine Population Models. Pharm Res

Maturation in GFR in Preterm Neonates Reflected by Clearance of Different Antibiotics

(1) Division of Pharmacology, LACDR, Leiden University, Leiden, the Netherlands (2) Neonatal Intensive Care Unit, University Hospital Leuven, Leuven, Belgium (3) Division of Clinical Pharmacology & Clinical Trials Office Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT,USA (4) Department of Pediatric Intensive Care, Erasmus MC - Sophia Children’s Hospital, Rotterdam, The Netherlands (5) Division of Pediatric Clinical Pharmacology, Children’s National Medical Center, Washington, DC, USA (6) Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands Objectives: Throughout infancy, renal function matures resulting in differences in glomerular filtration rate (GFR) at different stages of development. These developmental changes in GFR were previously quantified in (pre)term neonates aged up to 1 month on the basis of the clearance of amikacin. In this developmental renal excretion model (1), the maturation of GFR was predicted by birth weight (BWb) and postnatal age (PNA). The aim of this study is to assess model performance when this developmental renal excretion model (1) is used to describe maturation in clearance of other renally excreted antibiotics in (pre)term neonates. Using this approach a distinction is being made between system specific and drug specific information in paediatric pharmacokinetic models. Methods: For the netilmicin dataset, 386 netilmicin concentrations were available from 97 (pre)term neonates (BWb 470-3000 g, PNA 1-30 days)(2). The vancomycin dataset contained 752 vancomycin concentrations from 273 preterm neonates (BWb 385-2550 g, PNA 1-30 days)(3). A pharmacokinetic model was developed for both netilmicin or vancomycin using the developmental renal excretion model for amikacin clearance in neonates (1): CLi=CLp*{((BWb/BWBmedian)^1.34)*(1+0.213*(PNA/PNAmedian))} Using this approach, CLp is considered a drug specific property and was therefore estimated for each of the drugs separately. The remaining information in this equation is considered system specific information which can be applied for all renally excreted drugs. The descriptive and predictive performance of models developed using the developmental renal excretion model (1) were compared with comprehensive covariate models (4) for netilmicin or vancomycin respectively, by evaluation of the objective function (OFV), basic goodness-of-fit plots, NPDE and the individual and population parameter estimates versus most predictive covariate (4). Results: The descriptive and predictive properties of the models developed using the developmental renal excretion model, were similar compared to the comprehensive covariate models for basic goodness-of-fit plots and NPDE. In agreement the models that were developed using the developmental renal excretion model, in the comprehensive covariate models BWb and PNA were identified as most predictive covariates for clearance. The comprehensive covariate models had only a slightly lower objective function (netilmicin p\u3c0.05, vancomycin p\u3c0.001) compared to the models using the developmental renal excretion model. Conclusions: Use of the developmental renal excretion model quantifying maturation in GFR mediated amikacin clearance for the analysis of netilmicin and vancomycin clearance in neonates, results in adequate descriptive and predictive performance. We conclude that the application of system specific information may lead to optimization of sparse data analysis in children. References: [1] De Cock et al PAGE 19 (2010); abstract 1900, available from [www.page-meeting.org/?abstract=1900] [2] Sherwin, C.M., Broadbent, R.S., Medlicott, N.J. & Reith, D.M. Individualising netilmicin dosing in neonates. Eur J Clin Pharmacol 64, 1201-8 (2008). [3] Allegaert, K., Anderson, B.J., van den Anker, J.N., Vanhaesebrouck, S. & de Zegher, F. Renal drug clearance in preterm neonates: relation to prenatal growth. Ther Drug Monit 29, 284-91 (2007). [4] Krekels, E.H., van Hasselt, J.G., Tibboel, D., Danhof, M. & Knibbe, C.A. Systematic Evaluation of the Descriptive and Predictive Performance of Paediatric Morphine Population Models. Pharm Res

Maturation of GFR in Preterm and Term Neonates Reflected by Clearance of Different Antibiotics

Objectives: Throughout infancy, renal function matures resulting in differences in glomerular filtration rate (GFR) at different stages of development. These developmental changes in GFR were previously quantified in (pre)term neonates aged up to 1 month on the basis of the clearance of amikacin. In this developmental renal excretion model (1), the maturation of GFR was predicted by birth weight (BWb) and postnatal age (PNA). The aim of this study is to assess model performance when this developmental renal excretion model (1) is used to describe maturation in clearance of other renally excreted antibiotics in (pre)term neonates. Using this approach a distinction is being made between system specific and drug specific information in paediatric pharmacokinetic models. Methods: For the netilmicin dataset, 386 netilmicin concentrations were available from 97 (pre)term neonates (BWb 470-3000 g, PNA 1-30 days)(2). The vancomycin dataset contained 752 vancomycin concentrations from 273 preterm neonates (BWb 385-2550 g, PNA 1-30 days)(3). A pharmacokinetic model was developed for both netilmicin or vancomycin using the developmental renal excretion model for amikacin clearance in neonates (1): CLi=CLp*{((BWb/BWBmedian)^1.34)*(1+0.213*(PNA/PNAmedian))} Using this approach, CLp is considered a drug specific property and was therefore estimated for each of the drugs separately. The remaining information in this equation is considered system specific information which can be applied for all renally excreted drugs. The descriptive and predictive performance of models developed using the developmental renal excretion model (1) were compared with comprehensive covariate models (4) for netilmicin or vancomycin respectively, by evaluation of the objective function (OFV), basic goodness-of-fit plots, NPDE and the individual and population parameter estimates versus most predictive covariate (4). Results: The descriptive and predictive properties of the models developed using the developmental renal excretion model, were similar compared to the comprehensive covariate models for basic goodness-of-fit plots and NPDE. In agreement the models that were developed using the developmental renal excretion model, in the comprehensive covariate models BWb and PNA were identified as most predictive covariates for clearance. The comprehensive covariate models had only a slightly lower objective function (netilmicin p\u3c0.05, vancomycin p\u3c0.001) compared to the models using the developmental renal excretion model. Conclusions: Use of the developmental renal excretion model quantifying maturation in GFR mediated amikacin clearance for the analysis of netilmicin and vancomycin clearance in neonates, results in adequate descriptive and predictive performance. We conclude that the application of system specific information may lead to optimization of sparse data analysis in children