Literature DB >> 18547054

Applications of physiologically based absorption models in drug discovery and development.

Neil Parrott1, Thierry Lave.   

Abstract

This article describes the use of physiologically based models of intestinal drug absorption to guide the research and development of new drugs. Applications range from lead optimization in the drug discovery phase through clinical candidate selection and extrapolation to human to phase 2 formulation development. Early simulations in preclinical species integrate multiple screening data and add value by transforming these individual properties into a prediction of in vivo absorption. Comparison of simulations to plasma levels measured after oral dosing in animals highlights unexpected behavior, and parameter sensitivity analysis can explore the impact of uncertainties in key properties, point toward factors which are limiting absorption and contribute to assessment of compound developability. Physiological models provide reliable prediction of human absorption and with refinement based on phase 1 data are useful guides to further market formulation development. Improvements in the accuracy of simulations are expected as better in vitro methods generate more in vivo relevant solubility and permeability data, and modeling will play a central role in the development of more predictive methods for transporter-related effects on drug absorption.

Entities:  

Mesh:

Year:  2008        PMID: 18547054     DOI: 10.1021/mp8000155

Source DB:  PubMed          Journal:  Mol Pharm        ISSN: 1543-8384            Impact factor:   4.939


  30 in total

Review 1.  The use of modeling tools to drive efficient oral product design.

Authors:  Neil R Mathias; John Crison
Journal:  AAPS J       Date:  2012-05-30       Impact factor: 4.009

Review 2.  Oral bioavailability: issues and solutions via nanoformulations.

Authors:  Kamla Pathak; Smita Raghuvanshi
Journal:  Clin Pharmacokinet       Date:  2015-04       Impact factor: 6.447

Review 3.  The role of transporters in the pharmacokinetics of orally administered drugs.

Authors:  Sarah Shugarts; Leslie Z Benet
Journal:  Pharm Res       Date:  2009-06-30       Impact factor: 4.200

4.  Variance based global sensitivity analysis of physiologically based pharmacokinetic absorption models for BCS I-IV drugs.

Authors:  Nicola Melillo; Leon Aarons; Paolo Magni; Adam S Darwich
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-12-14       Impact factor: 2.745

5.  Development of an RTD-Based Flowsheet Modeling Framework for the Assessment of In-Process Control Strategies.

Authors:  Geng Tian; Abdollah Koolivand; Zongyu Gu; Michael Orella; Ryan Shaw; Thomas F O'Connor
Journal:  AAPS PharmSciTech       Date:  2021-01-05       Impact factor: 3.246

6.  Characterising Drug Release from Immediate-Release Formulations of a Poorly Soluble Compound, Basmisanil, Through Absorption Modelling and Dissolution Testing.

Authors:  Cordula Stillhart; Neil J Parrott; Marc Lindenberg; Pascal Chalus; Darren Bentley; Anikó Szepes
Journal:  AAPS J       Date:  2017-02-24       Impact factor: 4.009

Review 7.  A physiologically based pharmacokinetic model of the minipig: data compilation and model implementation.

Authors:  Claudia Suenderhauf; Neil Parrott
Journal:  Pharm Res       Date:  2012-11-21       Impact factor: 4.200

8.  Pharmacokinetics and pharmacodynamics of three oral formulations of curcumin in rats.

Authors:  Lujing Wang; Wenji Li; David Cheng; Yue Guo; Renyi Wu; Ran Yin; Shanyi Li; Hsiao-Chen Kuo; Rasika Hudlikar; Hilly Yang; Brian Buckley; Ah-Ng Kong
Journal:  J Pharmacokinet Pharmacodyn       Date:  2020-02-04       Impact factor: 2.745

Review 9.  Predicting pharmacokinetics of drugs using physiologically based modeling--application to food effects.

Authors:  N Parrott; V Lukacova; G Fraczkiewicz; M B Bolger
Journal:  AAPS J       Date:  2009-01-29       Impact factor: 4.009

10.  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

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