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Modeling and simulation of the exposure–response and dropout pattern of guanfacine extended-release in pediatric patients with ADHD

Abstract

Guanfacine extended-release (GXR) is a selective α2A-adrenergic receptor agonist approved in the United States for once-daily administration for the treatment of attention-deficit hyperactivity disorder (ADHD) in children and adolescents ages 6–17 years old either as monotherapy or adjunctive to stimulant medications. This analysis integrates exposure–response, placebo, and dropout data from 10 clinical trials that used GXR in adolescents and children with ADHD. In these trials, the ADHD Rating Scale-IV (ADHD RS-IV) score was collected longitudinally within patients over the course of 6–13 weeks. Non-linear mixed effects models were developed and used to describe the exposure–response of the GXR and placebo time course. The OpenBUGS program was utilized to describe the dropout time course across the trials. Placebo time course was best described by an inverse Bateman function with a 3-group mixture model that allowed for the onset and offset of the placebo response. Dropout time modeling indicated a missing at random mechanism for dropouts which was best described by a Weibull distribution with an estimated percentage of non-dropout patients. A linear exposure–response model with an adolescent effect on maximum slope (SLPmax), and a time delay for reaching SLPmax, provided the best description of the GXR exposure–response time course. The GXR exposure–response model indicated that the typical (95 % confidence interval) decrease in ADHD RS-IV score from the placebo–response trajectory would be 37.1 % (32.2, 42.0 %) per 0.1 mg/kg of GXR exposure. There was little noticeable difference between the exposure–response in adolescents and children or across ADHD subtypes.

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Acknowledgments

With great sadness, the authors acknowledge the passing of Carla White and recognize her contributions to this article. Funding for this research was provided by Shire Development LLC to Metrum Research Group LLC. Wilson Joe, from MedErgy, provided editorial assistance in formatting, proofreading, and copy editing. This support was funded by Shire. Although the sponsor was involved in the design, collection, analysis, interpretation, and fact checking of information, the content of this manuscript, the ultimate interpretation, and the decision to submit it for publication in the Journal of Pharmacokinetics and Pharmacodynamics were made by all of the authors independently.

Ethical standards

The studies conducted comply with the current laws of the United States of America in which they were performed.

Conflict of interest

William Knebel, Jim Rogers, Dan Polhamus, and Marc R. Gastonguay are employees of Metrum Research Group LLC, which received funding from Shire Development LLC for this study. Carla White, deceased, had served as a consultant for Shire Pharmaceutical Development Ltd, Basingstoke, United Kingdom. James Ermer is an employee of Shire Development LLC and holds stock/stock options in Shire.

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Correspondence to William Knebel.

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10928_2014_9397_MOESM1_ESM.eps

Fig. S1. Diagnostic plots for placebo model. Population and individual predicted ADHD RS-IV score versus observed score for the placebo model are presented in the top and middle plots, respectively. The line of identity (white) is included as a reference. Conditional weighted residuals versus population predicted ADHD RS-IV scores are presented in the bottom plots. Values are indicated by open circles with a white line at y = 0 as a reference. Plots are subsetted by subject type with children on the left and adolescents on the right. (ADHD RS-IV, Attention-deficit Hyperactivity Disorder Rating Scale-IV.) (EPS 407 kb)

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Knebel, W., Rogers, J., Polhamus, D. et al. Modeling and simulation of the exposure–response and dropout pattern of guanfacine extended-release in pediatric patients with ADHD. J Pharmacokinet Pharmacodyn 42, 45–65 (2015). https://doi.org/10.1007/s10928-014-9397-6

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Keywords

  • ADHD
  • Guanfacine
  • Exposure–response
  • Pediatric
  • Modeling
  • Simulation