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Parameter identifiability of fundamental pharmacodynamic models

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Janzén, David, Bergenholm, Linnéa, Jirstrand, Mats, Parkinson, Joanna, Yates, James, Evans, Neil D. and Chappell, Michael J. (2016) Parameter identifiability of fundamental pharmacodynamic models. Frontiers in Physiology, 7 . 590. doi:10.3389/fphys.2016.00590

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Official URL: http://dx.doi.org/10.3389/fphys.2016.00590

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Abstract

Issues of parameter identifiability of routinely used pharmacodynamics models are considered in this paper. The structural identifiability of 16 commonly applied pharmacodynamic model structures was analyzed analytically, using the input-output approach. Both fixed-effects versions (non-population, no between-subject variability) and mixed-effects versions (population, including between-subject variability) of each model structure were analyzed. All models were found to be structurally globally identifiable under conditions of fixing either one of two particular parameters. Furthermore, an example was constructed to illustrate the importance of sufficient data quality and show that structural identifiability is a prerequisite, but not a guarantee, for successful parameter estimation and practical parameter identifiability. This analysis was performed by generating artificial data of varying quality to a structurally identifiable model with known true parameter values, followed by re-estimation of the parameter values. In addition, to show the benefit of including structural identifiability as part of model development, a case study was performed applying an unidentifiable model to real experimental data. This case study shows how performing such an analysis prior to parameter estimation can improve the parameter estimation process and model performance. Finally, an unidentifiable model was fitted to simulated data using multiple initial parameter values, resulting in highly different estimated uncertainties. This example shows that although the standard errors of the parameter estimates often indicate a structural identifiability issue, reasonably “good” standard errors may sometimes mask unidentifiability issues.

Item Type: Journal Article
Subjects: R Medicine > RM Therapeutics. Pharmacology
Divisions: Faculty of Science > Life Sciences (2010- )
Library of Congress Subject Headings (LCSH): Drugs -- Physiological effect -- Mathematical models
Journal or Publication Title: Frontiers in Physiology
Publisher: Frontiers Research Foundation
ISSN: 1664-042X
Official Date: 5 December 2016
Dates:
DateEvent
5 December 2016Available
14 November 2016Accepted
Volume: 7
Article Number: 590
DOI: 10.3389/fphys.2016.00590
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
Funder: Seventh Framework Programme (European Commission) (FP7)
Grant number: People ITN European Industrial Doctorate (EID) project No.316736
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