Literature DB >> 8748422

A simple index for representing the discrepancy between simulations of physiological pharmacokinetic models and experimental data.

K Krishnan1, S Haddad, M Pelekis.   

Abstract

The objective of this study was to develop an index that would provide a quantitative measure of the degree of discrepancy between simulations of physiologically based pharmacokinetic (PBPK) models and experimental data. The approach we developed involves the calculation of the root mean square of the error (representing the difference between the individual simulated and experimental values for each sampling point in a time course curve), and dividing it by the root mean square of the experimental values. The resulting numerical values of discrepancy measures for several data sets (each corresponding to an end point) obtained in a single experimental study are then combined on the basis of a weighting proportional to the number of data points contained in each data set. Such consolidated discrepancy indices obtained from several experiments (e.g., exposure scenarios, doses, routes, species) are averaged to get an overall discrepancy index, referred to as the PBPK index. This empirical index reflects the overall, weighted average percent difference between the a priori PBPK model simulations and experimental data. The proposed methodology is illustrated using previously published experimental and simulated data on dichloromethane pharmacokinetics in humans. The application of this kind of a "quantitative" method should help remove the ambiguity in communicating the degree of concordance or discrepancy between PBPK model simulations and experimental data.

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Year:  1995        PMID: 8748422     DOI: 10.1177/074823379501100404

Source DB:  PubMed          Journal:  Toxicol Ind Health        ISSN: 0748-2337            Impact factor:   2.273


  6 in total

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Authors:  Hisham A El-Masri; Elaina M Kenyon
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-10-18       Impact factor: 2.745

3.  Extrapolating In Vitro Screening Assay Data for Thyroperoxidase Inhibition to Predict Serum Thyroid Hormones in the Rat.

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5.  Evaluation of a Physiologically Based Pharmacokinetic (PBPK) Model for Inorganic Arsenic Exposure Using Data from Two Diverse Human Populations.

Authors:  Hisham A El-Masri; Tao Hong; Cara Henning; William Mendez; Edward E Hudgens; David J Thomas; Janice S Lee
Journal:  Environ Health Perspect       Date:  2018-07-16       Impact factor: 9.031

6.  Mechanistic Computational Model for Extrapolating In Vitro Thyroid Peroxidase (TPO) Inhibition Data to Predict Serum Thyroid Hormone Levels in Rats.

Authors:  Sakshi Handa; Iman Hassan; Mary Gilbert; Hisham El-Masri
Journal:  Toxicol Sci       Date:  2021-08-30       Impact factor: 4.109

  6 in total

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