Michael Gertz
Hoffmann-La Roche
24 Papers
60 Citations
Michael Gertz is an academic researcher from Hoffmann-La Roche. The author has contributed to research in topics: Physiologically based pharmacokinetic modelling & Medicine. The author has an hindex of 13, co-authored 18 publications. Previous affiliations of Michael Gertz include University of Manchester & RMIT University.
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Papers
Prediction of human intestinal first-pass metabolism of 25 CYP3A substrates from in vitro clearance and permeability data
TL;DR: The FG predictions were most successful when Papp data from Caco-2 and Madin-Darby canine kidney cells transfected with human MDCK-MDR1 cells were used directly; in contrast, the use of physicochemical parameters resulted in significant FG underpredictions.
300
Hepatocellular binding of drugs: correction for unbound fraction in hepatocyte incubations using microsomal binding or drug lipophilicity data.
TL;DR: The proposed nonlinear equations provide an accurate predictive tool to estimate fuhep for the in vitro-in vivo extrapolation of intrinsic clearance and inhibition parameters and results in higher prediction accuracy and lower bias in comparison to the linear relationship.
157
Physiologically based pharmacokinetic modeling of intestinal first-pass metabolism of CYP3A substrates with high intestinal extraction.
TL;DR: Overall, the PBPK model improved FG predictions in comparison with the QGut model; this was apparent by a reduced bias and increased precision.
134
Contribution of Intestinal Cytochrome P450-Mediated Metabolism to Drug-Drug Inhibition and Induction Interactions
TL;DR: The current review provides an assessment of the contribution of intestinal inhibition and induction in conjunction with different perpetrator and victim drug-related properties, focusing in particular on victim drugs with high intestinal first-pass extraction.
120
Potential role of intestinal first-pass metabolism in the prediction of drug-drug interactions.
TL;DR: This review will focus on the ability of the current approaches to estimate the extent of intestinal DDI accurately, addressing predominantly the most abundant intestinal P450 enzyme, CYP3A4.
116