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Bridging the gap: a review of dose investigations in paediatric investigation plans
Author(s) -
Hampson Lisa V.,
Herold Ralf,
Posch Martin,
Saperia Julia,
Whitehead Anne
Publication year - 2014
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1111/bcp.12402
Subject(s) - dosing , medicine , bridging (networking) , sample size determination , medical physics , computer science , pharmacology , statistics , mathematics , computer network
Aims In the EU , development of new medicines for children should follow a prospectively agreed paediatric investigation plan ( PIP ). Finding the right dose for children is crucial but challenging due to the variability of pharmacokinetics across age groups and the limited sample sizes available. We examined strategies adopted in PIP s to support paediatric dosing recommendations to identify common assumptions underlying dose investigations and the attempts planned to verify them in children. Methods We extracted data from 73 PIP opinions recently adopted by the Paediatric Committee of the E uropean Medicines Agency. These opinions represented 79 medicinal development programmes and comprised a total of 97 dose investigation studies. We identified the design of these dose investigation studies, recorded the analyses planned and determined the criteria used to define target doses. Results Most dose investigation studies are clinical trials (83 of 97) that evaluate a single dosing rule. Sample sizes used to investigate dose are highly variable across programmes, with smaller numbers used in younger children (< 2 years). Many studies (40 of 97) do not pre‐specify a target dose criterion. Of those that do, most (33 of 57 studies) guide decisions using pharmacokinetic data alone. Conclusions Common assumptions underlying dose investigation strategies include dose proportionality and similar exposure−response relationships in adults and children. Few development programmes pre‐specify steps to verify assumptions in children. There is scope for the use of Bayesian methods as a framework for synthesizing existing information to quantify prior uncertainty about assumptions. This process can inform the design of optimal drug development strategies.