Considerations and Caveats when Applying Global Sensitivity Analysis Methods to Physiologically Based Pharmacokinetic Mo
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Research Article Considerations and Caveats when Applying Global Sensitivity Analysis Methods to Physiologically Based Pharmacokinetic Models Dan Liu,1,2 Linzhong Li,1 Amin Rostami-Hodjegan,1 Frederic Y. Bois,1 and Masoud Jamei1
Received 21 March 2020; accepted 7 July 2020 Abstract. Three global sensitivity analysis (GSA) methods (Morris, Sobol and extended
Sobol) are applied to a minimal physiologically based PK (mPBPK) model using three model drugs given orally, namely quinidine, alprazolam, and midazolam. We investigated how correlations among input parameters affect the determination of the key parameters influencing pharmacokinetic (PK) properties of general interest, i.e., the maximal plasma concentration (Cmax) time at which Cmax is reached (Tmax), and area under plasma concentration (AUC). The influential parameters determined by the Morris and Sobol methods (suitable for independent model parameters) were compared to those determined by the extended Sobol method (which considers model parameter correlations). For the three drugs investigated, the Morris method was as informative as the Sobol method. The extended Sobol method identified different sets of influential parameters to Morris and Sobol. These methods overestimated the influence of volume of distribution at steady state (Vss) on AUC24h for quinidine and alprazolam. They also underestimated the effect of volume of liver (Vliver) for all three drugs, the impact of enzyme intrinsic clearance of CYP2C9 and CYP2E1 for quinidine, and that of UGT1A4 abundance for midazolam. Our investigation showed that the interpretation of GSA results is not straightforward. Dismissing existing model parameter correlations, GSA methods such as Morris and Sobol can lead to biased determination of the key parameters for the selected outputs of interest. Decisions regarding parameters’ influence (or otherwise) should be made in light of available knowledge including the model assumptions, GSA method limitations, and inter-correlations between model parameters, particularly in complex models. KEY WORDS: Global sensitivity analysis; Morris method; Sobol method; extended Sobol method; physiologically based pharmacokinetic (PBPK) modelling.
INTRODUCTION Sensitivity analysis, in its broad sense, has been widely used to identify and rank the most influential model parameters affecting the model outputs. Many factors determine the sensitivity of a model’s outputs to its parameters. Those are most notably: the number of input parameters, uncertainty, correlation, and interactions between them, and the non-linearity or non-monotonicity of the model (1). Correlation between two parameters means that the values of one parameter relate in some way to the values of the
Electronic supplementary material The online version of this article (https://doi.org/10.1208/s12248-020-00480-x) contains supplementary material, which is available to authorized users. 1
Simcyp Division, Certara UK Limited, Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, UK. 2 To whom correspondence should be addresse
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