Dataset Information

Development of a population pharmacokinetic model of prucalopride in children with functional constipation.

ABSTRACT: A recent phase 3 trial of prucalopride in children with functional constipation (SPD555-303 ClinicalTrials.gov Identifier: NCT01330381) reported negative efficacy results. Here, we developed a population pharmacokinetic (PK) model of prucalopride in children to assess prucalopride exposure in SPD555-303. An initial population PK model in children was developed based on sampled single-dose data from a phase 1 study (PRU-USA-12). This model was subsequently updated with sampled data from SPD555-303 and used to simulate plasma concentration-time profiles for children aged 6 months to 18 years who were treated once daily with prucalopride 0.02, 0.04, or 0.06 mg kg-1 (maximum dose, 2 mg). Simulated PK profiles were compared with those of adults at the recommended dose of 2 mg once daily. Data were available from 38 patients (median age, 8.5 years) in PRU-USA-12 and 137 patients (median age, 7.9 years) in SPD555-303. Mean (range) area under the plasma concentration-time curve (AUC) at steady state was 62.3 (40.5-82.7) ng mL-1 h (dose, 0.03 mg kg-1) in PRU-USA-12 and 100.3 (22.7-286.0) ng mL-1 h (dose, 0.04 mg kg-1; maximum, 2 mg) in SPD555-303. Prucalopride 0.04 mg kg-1 once daily in children produced similar maximum plasma concentrations and approximately 10% lower AUC compared with adults receiving 2 mg once daily. This population PK analysis indicates that the PK profile of prucalopride in children in SPD555-303 was similar to that observed in adults. The negative efficacy results of SPD555-303 cannot be explained by differences in prucalopride exposure between children and adults.

SUBMITTER: van Schaick E

PROVIDER: S-EPMC5114692 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Development of a population pharmacokinetic model of prucalopride in children with functional constipation.

van Schaick Erno E Benninga Marc A MA Levine Amy A Magnusson Mats M Troy Steven S

Pharmacology research & perspectives 20160601 4

A recent phase 3 trial of prucalopride in children with functional constipation (SPD555-303 ClinicalTrials.gov Identifier: NCT01330381) reported negative efficacy results. Here, we developed a population pharmacokinetic (PK) model of prucalopride in children to assess prucalopride exposure in SPD555-303. An initial population PK model in children was developed based on sampled single-dose data from a phase 1 study (PRU-USA-12). This model was subsequently updated with sampled data from SPD555-30 ...[more]

PMID: 27891230

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Project description:BackgroundChildren with intractable functional constipation (IFC) who are refractory to traditional pharmacological intervention develop severe symptoms that can persist even in adulthood, resulting in a substantial deterioration in their quality of life. In order to better manage IFC patients, efficient subtyping of IFC into its three subtypes, normal transit constipation (NTC), outlet obstruction constipation (OOC), and slow transit constipation (STC), at early stages is crucial. With advancements in technology, machine learning can classify IFC early through the use of validated questionnaires and the different serum concentrations of gastrointestinal motility-related hormones.MethodA hundred and one children with IFC and 50 controls were enrolled in this study. Three supervised machine-learning methods, support vector machine, random forest, and light gradient boosting machine (LGBM), were used to classify children with IFC into the three subtypes based on their symptom severity, self-efficacy, and quality of life which were quantified using certified questionnaires and their serum concentrations of the gastrointestinal hormones evaluated with enzyme-linked immunosorbent assay. The accuracy of machine learning subtyping was evaluated with respect to radiopaque markers.ResultsOf 101 IFC patients, 37 had NTC, 49 had OOC, and 15 had STC. The variables significant for IFC subtype classification, according to SelectKBest, were stool frequency, the satisfaction domain of the Patient Assessment of Constipation Quality of Life questionnaire (PAC-QOL), the emotional self-efficacy for Functional Constipation questionnaire (SEFCQ), motilin serum concentration, and vasoactive intestinal peptide serum concentration. Among the three models, the LGBM model demonstrated an accuracy of 83.8%, a precision of 84.5%, a recall of 83.6%, a f1-score of 83.4%, and an area under the receiver operating characteristic curve (AUROC) of 0.89 in discriminating IFC subtypes.ConclusionUsing clinical characteristics measured by certified questionnaires and serum concentrations of the gastrointestinal hormones, machine learning can efficiently classify pediatric IFC into its three subtypes. Of the three models tested, the LGBM model is the most accurate model for the classification of IFC, with an accuracy of 83.8%, demonstrating that machine learning is an efficient tool for the management of IFC in children.

Project description:Dexmedetomidine is a selective alpha-2 adrenergic agonist with concurrent sedative and analgesic effects, and it is being increasingly used in pediatric anesthesia and intensive care. This study aimed to investigate the pharmacokinetics of intravenous dexmedetomidine in mechanically ventilated children in the intensive care unit (ICU) after neurosurgery. Pediatric patients aged 2-12 years, who were mechanically ventilated in ICU after neurosurgery, were allocated into a low-dose (n = 15) or high-dose (n = 14) group. The low-dose group received dexmedetomidine at a loading dose of 0.25 µg/kg for 10 min, followed by a maintenance dose of 0.25 µg/kg/h for 50 min, whereas the high-dose group received dexmedetomidine at a loading dose of 0.5 µg/kg for 10 min, followed by a maintenance dose of 0.5 µg/kg/h for 50 min. Serial blood samples were collected for a pharmacokinetic analysis up to 480 min after the end of the infusion. The sedative effect of dexmedetomidine was assessed using the Bispectral Index and University of Michigan Sedation Scale. Adverse reactions, electrocardiography findings, and vital signs were monitored for a safety assessment. A population pharmacokinetic analysis was performed using non-linear mixed effects modeling. Dexmedetomidine induced a moderate-to-deep degree of sedation during infusion in both groups. The pharmacokinetics of dexmedetomidine were best described by a two-compartment disposition model with first-order elimination kinetics. The parameters were standardized for a body weight of 70 kg using an allometric power model. The population estimates (95% confidence interval) per 70 kg body weight were as follows: clearance of 81.0 (72.9-90.9) L/h, central volume of distribution of 64.2 (50.6-81.0) L, intercompartment clearance of 116.4 (90.6-156.0) L/h, and peripheral volume of distribution of 167 (132-217) L. No serious adverse reactions or hemodynamic changes requiring the discontinuation of dexmedetomidine were observed. Dexmedetomidine had increased clearance and volume of distribution in mechanically ventilated children in ICU after neurosurgery, thereby indicating the need to adjust the dosage to obtain a target plasma concentration.

Project description:BACKGROUND AND AIMS:Pharmacokinetic data for proton pump inhibitors (PPIs), acid-suppression drugs commonly prescribed to children, are lacking for obese children who are at greatest risk for acid-related disease. In a recent multi-center investigation, we demonstrated decreased, total body weight adjusted, apparent clearance (CL/F) of the PPI pantoprazole for obese children compared with their non-obese peers. Subsequently, we developed a population-based pharmacokinetic (PopPK) model to characterize pantoprazole disposition and evaluated appropriate pantoprazole dosing strategies for obese pediatric patients, using simulation. METHODS:Pharmacokinetic data from the only prospective study of PPIs in obese children (aged 6-17 years; n?=?40) included 273 pantoprazole and 256 pantoprazole-sulfone plasma concentrations, after single oral-dose administration, and were used for pantoprazole model development and covariate analysis (NONMEM®). Model evaluation was performed via bootstrapping and predictive checks, and the final model was applied to simulate systemic pantoprazole exposures for common dosing scenarios. RESULTS:A two-compartment PopPK model, which included CYP2C19 genotype and total body weight, provided the best fit. Resultant, typical, weight-normalized pantoprazole parameter estimates were different than previously reported for children or adults, with significantly reduced pantoprazole CL/F for obese children. Of the dosing scenarios evaluated, the weight-tiered approach, approved by the US Food and Drug Administration, achieved pantoprazole exposures [area under the curve (AUC0-?)] within ranges previously reported as therapeutic, without over- or under-prediction for obese children. CONCLUSIONS:Our data argue against empiric dose escalation of PPIs for obese children and support current FDA-approved pediatric weight-tiered dosing for pantoprazole; however, 3- to 5-fold inter-individual variability in pantoprazole AUC0-? remained using this dosing approach.

Dataset Information

Development of a population pharmacokinetic model of prucalopride in children with functional constipation.

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Development of a population pharmacokinetic model of prucalopride in children with functional constipation.

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