Full covariate modelling approach in population pharmacokinetics: understanding the underlying hypothesis tests and implications of multiplicity-Reference-Cited by-同舟云学术

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Full covariate modelling approach in population pharmacokinetics: understanding the underlying hypothesis tests and implications of multiplicity

Published:2018-05-03 Issue:7 Volume:84 Page:1525-1534
ISSN:0306-5251
Container-title:British Journal of Clinical Pharmacology
language:en
Short-container-title:Br J Clin Pharmacol

Author:

Xu Xu Steven¹^ORCID,Yuan Min²,Zhu Hao³,Yang Yaning⁴,Wang Hui⁵,Zhou Honghui¹,Xu Jinfeng⁶,Zhang Liping¹,Pinheiro Jose¹

Affiliation:

1. Janssen Research & Development; 920 Route 202 Raritan NJ 08869 USA

2. School of Public Health Administration; Anhui Medical University; Hefei China

3. Division of Clinical Pharmacology, Office of Clinical Pharmacology; US Food and Drug Administration; Silver Spring MD USA

4. Department of Statistics and Finance; University of Science and Technology of China; Hefei China

5. Athenex Inc.; Conventus 1001 Main St Buffalo NY 14203 USA

6. Department of Statistics & Actuarial Science; University of Hong Kong; Hong Kong

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Pharmacology (medical),Pharmacology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/bcp.13577/fullpdf

Reference16 articles.

1. Applications of population pharmacokinetics in current drug labelling;Duan;J Clin Pharm Ther,2007

2. Covariate pharmacokinetic model building in oncology and its potential clinical relevance;Joerger;AAPS J,2012

3. Essential pharmacokinetic information for drug dosage decisions: a concise visual presentation in the drug label;Menon-Andersen;Clin Pharmacol Ther,2011

4. Automated covariate model building within NONMEM;Jonsson;Pharm Res,1998

5. Model-based clinical pharmacology profiling of ipilimumab in patients with advanced melanoma;Feng;Br J Clin Pharmacol,2014

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