Literature DB >> 22759901

Application of PBPK modeling to predict human intestinal metabolism of CYP3A substrates - an evaluation and case study using GastroPlus.

Aki T Heikkinen1, Guillaume Baneyx, Antonello Caruso, Neil Parrott.   

Abstract

First pass metabolism in the intestinal mucosa is a determinant of oral bioavailability of CYP3A substrates and so the prediction of intestinal availability (Fg) of potential drug candidates is important. Although intestinal metabolism can be modeled in commercial physiologically based pharmacokinetic (PBPK) software tools, a thorough evaluation of prediction performance is lacking. The current study evaluates the accuracy and precision of GastroPlus Fg predictions for 20 CYP3A substrates using in vitro and in silico input data for metabolic clearance and membrane permeation, and illustrates a potential impact of intestinal metabolism modeling on decision making in a drug Research and Development project. This analysis supports that CYP3A mediated metabolic clearance measured in human liver microsomes can be used to predict gut wall metabolism. Using values scaled from in vitro cell permeability as input for effective jejunal permeability resulted in good Fg prediction accuracy (no significant bias and ∼95% of predictions within 2 fold from in vivo estimated Fg), whereas simulations with in silico predicted permeability tended to overestimate gut metabolism (40% of Fg predictions under predicted more than 2 fold) ±2 fold range as an estimate of imprecision in metabolic clearance and permeability inputs propagated to >5 and <2 fold ranges of predicted Fg for compounds with <30% and >75% in vivo Fg, respectively, suggesting lower precision of predictions for high extraction compounds. Furthermore, parameter sensitivity analysis suggests that limitations in solubility or dissolution may either decrease Fg by preventing saturation of metabolism or increase Fg by shifting the site of absorption towards the colon where expression of CYP3A is low. The case example illustrates how, when accounting for the associated uncertainty in predicted pharmacokinetics and linking to predictive models for efficacy, PBPK modeling of intestinally metabolized compounds can support decision making in drug Research and Development.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22759901     DOI: 10.1016/j.ejps.2012.06.013

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  14 in total

1.  Evaluation of the GastroPlus™ Advanced Compartmental and Transit (ACAT) Model in Early Discovery.

Authors:  N Gobeau; R Stringer; S De Buck; T Tuntland; B Faller
Journal:  Pharm Res       Date:  2016-06-08       Impact factor: 4.200

Review 2.  Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine.

Authors:  Clara Hartmanshenn; Megerle Scherholz; Ioannis P Androulakis
Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-09-19       Impact factor: 2.745

Review 3.  Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies.

Authors:  Neil A Miller; Micaela B Reddy; Aki T Heikkinen; Viera Lukacova; Neil Parrott
Journal:  Clin Pharmacokinet       Date:  2019-06       Impact factor: 6.447

4.  Physiologically Based Absorption Modeling to Explore the Impact of Food and Gastric pH Changes on the Pharmacokinetics of Alectinib.

Authors:  Neil J Parrott; Li J Yu; Ryusuke Takano; Mikiko Nakamura; Peter N Morcos
Journal:  AAPS J       Date:  2016-07-22       Impact factor: 4.009

5.  Physiologically based pharmacokinetic modelling to predict single- and multiple-dose human pharmacokinetics of bitopertin.

Authors:  Neil Parrott; Dominik Hainzl; Daniela Alberati; Carsten Hofmann; Richard Robson; Bruno Boutouyrie; Meret Martin-Facklam
Journal:  Clin Pharmacokinet       Date:  2013-08       Impact factor: 6.447

6.  Quantitative ADME proteomics - CYP and UGT enzymes in the Beagle dog liver and intestine.

Authors:  Aki T Heikkinen; Arno Friedlein; Mariette Matondo; Oliver J D Hatley; Aleksanteri Petsalo; Risto Juvonen; Aleksandra Galetin; Amin Rostami-Hodjegan; Ruedi Aebersold; Jens Lamerz; Tom Dunkley; Paul Cutler; Neil Parrott
Journal:  Pharm Res       Date:  2014-07-18       Impact factor: 4.200

Review 7.  Prediction of drug disposition on the basis of its chemical structure.

Authors:  David Stepensky
Journal:  Clin Pharmacokinet       Date:  2013-06       Impact factor: 6.447

8.  Investigating Oral Absorption of Carbamazepine in Pediatric Populations.

Authors:  Philip Kohlmann; Cordula Stillhart; Martin Kuentz; Neil Parrott
Journal:  AAPS J       Date:  2017-10-02       Impact factor: 4.009

9.  Simulating Intestinal Transporter and Enzyme Activity in a Physiologically Based Pharmacokinetic Model for Tenofovir Disoproxil Fumarate.

Authors:  Darren M Moss; Paul Domanico; Melynda Watkins; Seonghee Park; Ryan Randolph; Steve Wring; Rajith Kumar Reddy Rajoli; James Hobson; Steve Rannard; Marco Siccardi; Andrew Owen
Journal:  Antimicrob Agents Chemother       Date:  2017-06-27       Impact factor: 5.191

10.  A Whole-Body Physiologically Based Pharmacokinetic Model Characterizing Interplay of OCTs and MATEs in Intestine, Liver and Kidney to Predict Drug-Drug Interactions of Metformin with Perpetrators.

Authors:  Yiting Yang; Zexin Zhang; Ping Li; Weimin Kong; Xiaodong Liu; Li Liu
Journal:  Pharmaceutics       Date:  2021-05-11       Impact factor: 6.321

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