Identifiability of PBPK models with applications to dimethylarsinic acid exposure
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| 024 | 7 | 0 | |a 10.1007/s10928-015-9424-2 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s10928-015-9424-2 | ||
| 245 | 0 | 0 | |a Identifiability of PBPK models with applications to dimethylarsinic acid exposure |h [Elektronische Daten] |c [Ramon Garcia, Joseph Ibrahim, John Wambaugh, Elaina Kenyon, R. Setzer] |
| 520 | 3 | |a Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss different types of identifiability that occur in PBPK models and give reasons why they occur. We particularly focus on how the mathematical structure of a PBPK model and lack of appropriate data can lead to statistical models in which it is impossible to estimate at least some parameters precisely. Methods are reviewed which can determine whether a purely linear PBPK model is globally identifiable. We propose a theorem which determines when identifiability at a set of finite and specific values of the mathematical PBPK model (global discete identifiability) implies identifiability of the statistical model. However, we are unable to establish conditions that imply global discrete identifiability, and conclude that the only safe approach to analysis of PBPK models involves Bayesian analysis with truncated priors. Finally, computational issues regarding posterior simulations of PBPK models are discussed. The methodology is very general and can be applied to numerous PBPK models which can be expressed as linear time-invariant systems. A real data set of a PBPK model for exposure to dimethyl arsinic acid (DMA(V)) is presented to illustrate the proposed methodology. | |
| 540 | |a Springer Science+Business Media New York (outside the USA), 2015 | ||
| 690 | 7 | |a PBPK Models |2 nationallicence | |
| 690 | 7 | |a Identifiability |2 nationallicence | |
| 690 | 7 | |a Gibbs sampling |2 nationallicence | |
| 690 | 7 | |a Metropolis-Hasting algorithm |2 nationallicence | |
| 690 | 7 | |a Dimethyl arsinic acid |2 nationallicence | |
| 700 | 1 | |a Garcia |D Ramon |u Department of Biostatistics, University of North Carolina, 27599, Chapel Hill, NC, USA |4 aut | |
| 700 | 1 | |a Ibrahim |D Joseph |u Department of Biostatistics, University of North Carolina, 27599, Chapel Hill, NC, USA |4 aut | |
| 700 | 1 | |a Wambaugh |D John |u United States Environmental Protection Agency, National Center for Computational Toxicology, 27711, Research Triangle Park, NC, USA |4 aut | |
| 700 | 1 | |a Kenyon |D Elaina |u United States Environmental Protection Agency, National Health and Environmental Effects Laboratory, 27711, Research Triangle Park, NC, USA |4 aut | |
| 700 | 1 | |a Setzer |D R. |u United States Environmental Protection Agency, National Center for Computational Toxicology, 27711, Research Triangle Park, NC, USA |4 aut | |
| 773 | 0 | |t Journal of Pharmacokinetics and Pharmacodynamics |d Springer US; http://www.springer-ny.com |g 42/6(2015-12-01), 591-609 |x 1567-567X |q 42:6<591 |1 2015 |2 42 |o 10928 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s10928-015-9424-2 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s10928-015-9424-2 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Garcia |D Ramon |u Department of Biostatistics, University of North Carolina, 27599, Chapel Hill, NC, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Ibrahim |D Joseph |u Department of Biostatistics, University of North Carolina, 27599, Chapel Hill, NC, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Wambaugh |D John |u United States Environmental Protection Agency, National Center for Computational Toxicology, 27711, Research Triangle Park, NC, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Kenyon |D Elaina |u United States Environmental Protection Agency, National Health and Environmental Effects Laboratory, 27711, Research Triangle Park, NC, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Setzer |D R. |u United States Environmental Protection Agency, National Center for Computational Toxicology, 27711, Research Triangle Park, NC, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Journal of Pharmacokinetics and Pharmacodynamics |d Springer US; http://www.springer-ny.com |g 42/6(2015-12-01), 591-609 |x 1567-567X |q 42:6<591 |1 2015 |2 42 |o 10928 | ||