Document Detail


The design and analysis of parallel experiments to produce structurally identifiable models.
MedLine Citation:
PMID:  23300030     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Pharmacokinetic analysis in humans using compartmental models is restricted with respect to the estimation of parameter values. This is because the experimenter usually is only able to apply inputs and observations in a very small number of compartments in the system. This has implications for the structural identifiability of such systems and consequently limits the complexity and mechanistic relevance of the models that may be applied to such experiments. A number of strategies are presented whereby models are rendered globally identifiable by considering a series of experiments in parallel. Examples are taken from the pharmacokinetic literature and analysed using this parallel experiment methodology. It is concluded that considering a series of pharmacokinetic experiments where some, but not all, of the parameters may be shared across the experiments can improve the identifiability of some compartmental models.
Authors:
S Y Amy Cheung; James W T Yates; Leon Aarons
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-9
Journal Detail:
Title:  Journal of pharmacokinetics and pharmacodynamics     Volume:  -     ISSN:  1573-8744     ISO Abbreviation:  J Pharmacokinet Pharmacodyn     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-9     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101096520     Medline TA:  J Pharmacokinet Pharmacodyn     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Clinical Pharmacology and Pharmacometrics, AstraZeneca, Alderley Park, Macclesfield, UK, Amy.Cheung@astrazeneca.com.
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