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Global Sensitivity ...
Global Sensitivity Analysis of the Rodgers and Rowland Model for Prediction of Tissue: Plasma Partitioning Coefficients: Assessment of the Key Physiological and Physicochemical Factors That Determine Small-Molecule Tissue Distribution
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Yau, Estelle (author)
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Olivares-Morales, Andrés (author)
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Gertz, Michael (author)
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Parrott, Neil (author)
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- Darwich, Adam S. (author)
- KTH,Hälsoinformatik och logistik
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Aarons, Leon (author)
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Ogungbenro, Kayode (author)
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(creator_code:org_t)
- 2020-02-03
- 2020
- English.
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In: AAPS Journal. - : Springer Nature. - 1550-7416. ; 22:2, s. 1-13
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https://kth.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
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- In physiologically based pharmacokinetic (PBPK) modelling, the large number of input parameters, limited amount of available data and the structural model complexity generally hinder simultaneous estimation of uncertain and/or unknown parameters. These parameters are generally subject to estimation. However, the approaches taken for parameter estimation vary widely. Global sensitivity analyses are proposed as a method to systematically determine the most influential parameters that can be subject to estimation. Herein, a global sensitivity analysis was conducted to identify the key drug and physiological parameters influencing drug disposition in PBPK models and to potentially reduce the PBPK model dimensionality. The impact of these parameters was evaluated on the tissue-to-unbound plasma partition coefficients (Kpus) predicted by the Rodgers and Rowland model using Latin hypercube sampling combined to partial rank correlation coefficients (PRCC). For most drug classes, PRCC showed that LogP and fraction unbound in plasma (fup) were generally the most influential parameters for Kpu predictions. For strong bases, blood:plasma partitioning was one of the most influential parameter. Uncertainty in tissue composition parameters had a large impact on Kpu and Vss predictions for all classes. Among tissue composition parameters, changes in Kpu outputs were especially attributed to changes in tissue acidic phospholipid concentrations and extracellular protein tissue:plasma ratio values. In conclusion, this work demonstrates that for parameter estimation involving PBPK models and dimensionality reduction purposes, less influential parameters might be assigned fixed values depending on the parameter space, while influential parameters could be subject to parameters estimation.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Farmaceutiska vetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Pharmaceutical Sciences (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Farmakologi och toxikologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Pharmacology and Toxicology (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Fysiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Physiology (hsv//eng)
- NATURVETENSKAP -- Matematik -- Beräkningsmatematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Computational Mathematics (hsv//eng)
- NATURVETENSKAP -- Matematik -- Matematisk analys (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Mathematical Analysis (hsv//eng)
Keyword
- drug distribution
- global sensitivity analysis
- partition coefficients
- PBPK
- uncertainty
- Tillämpad matematik och beräkningsmatematik
- Applied and Computational Mathematics
- Teknik och hälsa
- Technology and Health
- Mathematical Statistics
- Matematisk statistik
- Applied Medical Technology
- Tillämpad medicinsk teknik
- Kemi
- Chemistry
Publication and Content Type
- ref (subject category)
- art (subject category)
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