Traditionally, dosage for pediatric patients has been optimized using simple weight-scaled methods, but these methods do not always meet the requirements of children. To overcome this discrepancy, population pharmacokinetic (PK) modeling of size and maturation functions has been proposed. The main objective of the present study was to evaluate a new modeling method for pediatric patients using clinical data from three different clinical studies. To develop the PK models, a nonlinear mixed effect modeling method was employed, and to explore PK differences in pediatric patients, size with allometric and maturation with Michaelis–Menten type functions were evaluated. Goodness of fit plots, visual predictive check and bootstrap were used for model evaluation. Single application of size scaling to PK parameters was statistically significant for the over one year old group. On the other hand, simultaneous use of size and maturation functions was statistically significant for infants younger than one year old. In conclusion, population PK modeling for pediatric patients was successfully performed using clinical data. Size and maturation functions were applied according to established criteria, and single use of size function was applicable for over one year ages, while size and maturation functions were more effective for PK analysis of neonates and infants.
BackgroundOral administration of drugs is convenient and shows good compliance but it can be affected by many factors in the gastrointestinal (GI) system. Consumption of food is one of the major factors affecting the GI system and consequently the absorption of drugs. The aim of this study was to develop a mechanistic GI absorption model for explaining the effect of food on fenofibrate pharmacokinetics (PK), focusing on the food type and calorie content.MethodsClinical data from a fenofibrate PK study involving three different conditions (fasting, standard meals and high-fat meals) were used. The model was developed by nonlinear mixed effect modeling method. Both linear and nonlinear effects were evaluated to explain the impact of food intake on drug absorption. Similarly, to explain changes in gastric emptying time for the drug due to food effects was evaluated.ResultsThe gastric emptying rate increased by 61.7% during the first 6.94 h after food consumption. Increased calories in the duodenum increased the absorption rate constant of the drug in fed conditions (standard meal = 16.5%, high-fat meal = 21.8%) compared with fasted condition. The final model displayed good prediction power and precision.ConclusionsA mechanistic GI absorption model for quantitatively evaluating the effects of food on fenofibrate absorption was successfully developed, and acceptable parameters were obtained. The mechanism-based PK model of fenofibrate can quantify the effects of food on drug absorption by food type and calorie content.Electronic supplementary materialThe online version of this article (10.1186/s40360-018-0194-5) contains supplementary material, which is available to authorized users.
Background: The potential for hepatotoxicity during isoniazid-based tuberculosis (TB) treatment presents a major challenge for TB control programs worldwide. We sought to determine whether pharmacokinetic exposures of isoniazid and its metabolites were related to cellular oxidation/reduction status and downstream markers of oxidative DNA damage.
Methods: We performed intensive pharmacokinetic sampling among isoniazid-treated patients to determine the relative plasma exposures of isoniazid, acetylisoniazid, hydrazine, and acetylhydrazine. Physiologically-based pharmacokinetic modeling was used to estimate liver tissue exposures during a 24-hour dosing interval for each compound. We experimentally treated HepG2 cells with isoniazid and metabolites at equimolar concentrations corresponding to these exposures for 7, 14, and 28 day periods, and performed assays related to redox imbalance and oxidative DNA damage at each timepoint. We related a urine marker of oxidative DNA damage to serum isoniazid pharmacokinetic exposures and pharmacogenetics in a clinical study.
Results: Among isoniazid-treated patients, serum concentrations of hydrazine and isoniazid concentrations were highly correlated. At equimolar concentrations that approximated hepatic tissue exposures during a 24-hour dosing interval, hydrazine demonstrated the highest levels of redox imbalance, mitochondrial injury, and oxidative DNA damage over a 28-day treatment period. In a clinical validation study of isoniazid-treated TB patients, peak isoniazid serum concentrations were positively associated with a urine biomarker of oxidative DNA damage.
Conclusions: Isoniazid and its metabolites share the potential for oxidative cellular damage, with the greatest effects observed for hydrazine. Future studies should investigate the clinical consequences of oxidative stress with regards to clinical episodes of drug induced liver injury during isoniazid treatment.
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