Literature DB >> 21541937

PHRMA CPCDC initiative on predictive models of human pharmacokinetics, part 5: prediction of plasma concentration-time profiles in human by using the physiologically-based pharmacokinetic modeling approach.

Patrick Poulin1, Rhys D O Jones, Hannah M Jones, Christopher R Gibson, Malcolm Rowland, Jenny Y Chien, Barbara J Ring, Kimberly K Adkison, M Sherry Ku, Handan He, Ragini Vuppugalla, Punit Marathe, Volker Fischer, Sandeep Dutta, Vikash K Sinha, Thorir Björnsson, Thierry Lavé, James W T Yates.   

Abstract

The objective of this study is to assess the effectiveness of physiologically based pharmacokinetic (PBPK) models for simulating human plasma concentration-time profiles for the unique drug dataset of blinded data that has been assembled as part of a Pharmaceutical Research and Manufacturers of America initiative. Combinations of absorption, distribution, and clearance models were tested with a PBPK approach that has been developed from published equations. An assessment of the quality of the model predictions was made on the basis of the shape of the plasma time courses and related parameters. Up to 69% of the simulations of plasma time courses made in human demonstrated a medium to high degree of accuracy for intravenous pharmacokinetics, whereas this number decreased to 23% after oral administration based on the selected criteria. The simulations resulted in a general underestimation of drug exposure (Cmax and AUC0- t ). The explanations for this underestimation are diverse. Therefore, in general it may be due to underprediction of absorption parameters and/or overprediction of distribution or oral first-pass. The implications of compound properties are demonstrated. The PBPK approach based on in vitro-input data was as accurate as the approach based on in vivo data. Overall, the scientific benefit of this modeling study was to obtain more extensive characterization of predictions of human PK from PBPK methods.
Copyright © 2011 Wiley-Liss, Inc.

Entities:  

Keywords:  PBPK modeling; absorption; animal alternative; computational ADME; disposition; distribution; drug development; drug discovery; in vitro-in vivo correlation; pharmacokinetics

Mesh:

Substances:

Year:  2011        PMID: 21541937     DOI: 10.1002/jps.22550

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  40 in total

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