Morphine glucuronidation in preterm neonates, infants and children younger than 3 years
ABSTRACT A considerable amount of drug use in children is still unlicensed or off-label. In order to derive rational dosing schemes, the influence of aging on glucuronidation capacity in newborns, including preterms, infants and children under the age of 3 years was studied using morphine and its major metabolites as a model drug.
A population pharmacokinetic model was developed with the nonlinear mixed-effects modelling software NONMEM V, on the basis of 2159 concentrations of morphine and its glucuronides from 248 infants receiving intravenous morphine ranging in bodyweight from 500 g to 18 kg (median 2.8 kg). The model was internally validated using normalized prediction distribution errors.
Formation clearances of morphine to its glucuronides and elimination clearances of the glucuronides were found to be primarily influenced by bodyweight, which was parameterized using an allometric equation with an estimated exponential scaling factor of 1.44. Additionally, a postnatal age of less than 10 days was identified as a covariate for formation clearance to the glucuronides, independent of birthweight or postmenstrual age. Distribution volumes scaled linearly with bodyweight.
Model-based simulations show that in newborns, including preterms, infants and children under the age of 3 years, a loading dose in microg/kg and a maintenance dose expressed in microg/kg1.5/h, with a 50% reduction of the maintenance dose in newborns younger than 10 days, results in a narrow range of morphine and metabolite serum concentrations throughout the studied age range. Future pharmacodynamic investigations are needed to reveal target concentrations in this population, after which final dosing recommendations can be made.
- SourceAvailable from: Chuan-Yue Wang
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- "The upper left graph is a quantile-quantile plot (QQ plot) comparing the distribution of the NPDE to the theoretical N (0, 1) distribution, and the upper right graph is a histogram of the NPDE with the density of N (0, 1) overlaid. In the two lower graphs, the NPDE is plotted against time (the independent variable X) and the predicted concentration (predicted Y), respectively21,24,25. For clozapine and norclozapine, the mean of the distribution of the NPDE was close to 0, and the variance was small. "
ABSTRACT: Aim: To develop a combined population pharmacokinetic model (PPK) to assess the magnitude and variability of exposure to both clozapine and its primary metabolite norclozapine in Chinese patients with refractory schizophrenia via sparse sampling with a focus on the effects of covariates on the pharmacokinetic parameters. Methods: Relevant patient concentration data (eg, demographic data, medication history, dosage regimen, time of last dose, sampling time, concentrations of clozapine and norclozapine, etc) were collected using a standardized data collection form. The demographic characteristics of the patients, including sex, age, weight, body surface area, smoking status, and information on concomitant medications as well as biochemical and hematological test results were recorded. Persons who had smoked 5 or more cigarettes per day within the last week were defined as smokers. The concentrations of clozapine and norclozapine were measured using a HPLC system equipped with a UV detector. PPK analysis was performed using NONMEM. Age, weight, sex, and smoking status were evaluated as main covariates. The model was internally validated using normalized prediction distribution errors. Results: A total of 809 clozapine concentration data sets and 808 norclozapine concentration data sets from 162 inpatients (74 males, 88 females) at multiple mental health sites in China were included. The one-compartment pharmacokinetic model with mixture error could best describe the concentration-time profiles of clozapine and norclozapine. The population-predicted clearance of clozapine and norclozapine in female nonsmokers were 21.9 and 32.7 L/h, respectively. The population-predicted volumes of distribution for clozapine and norclozapine were 526 and 624 L, respectively. Smoking was significantly associated with increases in the clearance (clozapine by 45%; norclozapine by 54.3%). The clearance was significantly greater in males than in females (clozapine by 20.8%; norclozapine by 24.2%). The clearance of clozapine and norclozapine did not differ significantly between Chinese patients and American patients. Conclusion: Smoking and male were significantly associated with a lower exposure to clozapine and norclozapine due to higher clearance. This model can be used in individualized drug dosing and therapeutic drug monitoring.Acta Pharmacologica Sinica 07/2012; 33(11). DOI:10.1038/aps.2012.71 · 2.50 Impact Factor
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- "Pediatrics 114 (5): 1362-1364 54 Allegaert K, Anderson BJ, Cossey V, et al (2006) Limited predictability of amikacin clearance in extreme premature neonates at birth. Br J Clin Pharmacol 61 (1): 39-48 55 Knibbe CA, Krekels EH, van den Anker JN, et al (2009) Morphine glucuronidation in preterm neonates, infants and children younger than 3 years. Clin Pharmacokinet 48 (6): 371-385 56 Mahmood I (2007) Prediction of drug clearance in children: impact of allometric exponents, body weight, and age. "
ABSTRACT: Children differ from adults in their response to drugs. While this may be the result of changes in dose exposure (pharmacokinetics [PK]) and/or exposure response (pharmacodynamics [PD]) relationships, the magnitude of these changes may not be solely reflected by differences in body weight. As a consequence, dosing recommendations empirically derived from adults dosing regimens using linear extrapolations based on body weight, can result in therapeutic failure, occurrence of adverse effect or even fatalities. In order to define rational, patient-tailored dosing schemes, population PK-PD studies in children are needed. For the analysis of the data, population modelling using non-linear mixed effect modelling is the preferred tool since this approach allows for the analysis of sparse and unbalanced datasets. Additionally, it permits the exploration of the influence of different covariates such as body weight and age to explain the variability in drug response. Finally, using this approach, these PK-PD studies can be designed in the most efficient manner in order to obtain the maximum information on the PK-PD parameters with the highest precision. Once a population PK-PD model is developed, internal and external validations should be performed. If the model performs well in these validation procedures, model simulations can be used to define a dosing regimen, which in turn needs to be tested and challenged in a prospective clinical trial. This methodology will improve the efficacy/safety balance of dosing guidelines, which will be of benefit to the individual child.European Journal of Clinical Pharmacology 03/2010; 67 Suppl 1(Suppl 1):5-16. DOI:10.1007/s00228-009-0782-9 · 2.70 Impact Factor
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ABSTRACT: The primary focus of pain research in intellectually disabled individuals is still on pain assessment. Several observational pain assessment scales are available, each with its own characteristics, its own target group and its own validated use. Observational studies report differences in the treatment of intra- and postoperative pain of intellectually disabled children and almost all children with intellectual disability have comorbidities that need to be addressed. The scope of research has started to broaden. In this review we aim to answer the question: Can we integrate validated ways of pain assessment and postoperative pain treatment in intellectually disabled children to develop specific analgesic algorithms? Regrettably there is little knowledge on possible interaction effects and other relevant pharmacological issues. Possible genotype-phenotype associations related to pain in children with Down syndrome have several promises as six possible candidate genes are located on chromosome 21. In conclusion, the pain assessment tools for intellectually disabled children are there. We should now focus on tailoring the pain treatment. To this aim we need to perform pharmacokinetic and pharmacodynamic studies of analgesics and obtain information about the genotype-phenotype relationships for pain. This can lead to the development of specific analgesic algorithms.Developmental Disabilities Research Reviews 01/2010; 16(3):248-57. DOI:10.1002/ddrr.117 · 0.29 Impact Factor