Literature DB >> 12453607

In silico prediction of ADME and pharmacokinetics. Report of an expert meeting organised by COST B15.

Alan Boobis1, Ursula Gundert-Remy, Pierre Kremers, Panos Macheras, Olavi Pelkonen.   

Abstract

The computational approach is one of the newest and fastest developing techniques in pharmacokinetics, ADME (absorption, distribution, metabolism, excretion) evaluation, drug discovery and toxicity. However, to date, the software packages devoted to ADME prediction, especially of metabolism, have not yet been adequately validated and still require improvements to be effective. Most are 'open' systems, under constant evolution and able to incorporate rapidly, and often easily, new information from user or developer databases. Quantitative in silico predictions are now possible for several pharmacokinetic (PK) parameters, particularly absorption and distribution. The emerging consensus is that the predictions are no worse than those made using in vitro tests, with the decisive advantage that much less investment in technology, resources and time is needed. In addition, and of critical importance, it is possible to screen virtual compounds. Some packages are able to handle thousands of molecules in a few hours. However, common experience shows that, in part at least for essentially irrational reasons, there is currently a lack of confidence in these approaches. An effort should be made by the software producers towards more transparency, in order to improve the confidence of their consumers. It seems highly probable that in silico approaches will evolve rapidly, as did in vitro methods during the last decade. Past experience with the latter should be helpful in avoiding repetition of similar errors and in taking the necessary steps to ensure effective implementation. A general concern is the lack of access to the large amounts of data on compounds no longer in development, but still kept secret by the pharmaceutical industry. Controlled access to these data could be particularly helpful in validating new in silico approaches.

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Year:  2002        PMID: 12453607     DOI: 10.1016/s0928-0987(02)00185-9

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


  18 in total

1.  Prediction of in vitro metabolic stability of calcitriol analogs by QSAR.

Authors:  Berith F Jensen; Morten D Sørensen; Anne-Marie Kissmeyer; Fredrik Björkling; Kim Sonne; Søren B Engelsen; Lars Nørgaard
Journal:  J Comput Aided Mol Des       Date:  2003-12       Impact factor: 3.686

2.  Prediction of the tissue/blood partition coefficients of organic compounds based on the molecular structure using least-squares support vector machines.

Authors:  H X Liu; X J Yao; R S Zhang; M C Liu; Z D Hu; B T Fan
Journal:  J Comput Aided Mol Des       Date:  2005-11-30       Impact factor: 3.686

3.  Prediction of metabolic reactions based on atomic and molecular properties of small-molecule compounds.

Authors:  Fangping Mu; Clifford J Unkefer; Pat J Unkefer; William S Hlavacek
Journal:  Bioinformatics       Date:  2011-04-08       Impact factor: 6.937

4.  In vivo-in vitro-in silico pharmacokinetic modelling in drug development: current status and future directions.

Authors:  Olavi Pelkonen; Miia Turpeinen; Hannu Raunio
Journal:  Clin Pharmacokinet       Date:  2011-08       Impact factor: 6.447

5.  In silico modeling of non-linear drug absorption for the P-gp substrate talinolol and of consequences for the resulting pharmacodynamic effect.

Authors:  Marija Tubic; Daniel Wagner; Hilde Spahn-Langguth; Michael B Bolger; Peter Langguth
Journal:  Pharm Res       Date:  2006-08       Impact factor: 4.200

6.  Searching for plant-derived antivirals against dengue virus and Zika virus.

Authors:  Emerson de Castro Barbosa; Tânia Maria Almeida Alves; Markus Kohlhoff; Soraya Torres Gaze Jangola; Douglas Eduardo Valente Pires; Anna Carolina Cançado Figueiredo; Érica Alessandra Rocha Alves; Carlos Eduardo Calzavara-Silva; Marcos Sobral; Erna Geessien Kroon; Luiz Henrique Rosa; Carlos Leomar Zani; Jaquelline Germano de Oliveira
Journal:  Virol J       Date:  2022-02-22       Impact factor: 4.099

7.  Reduction and lumping of physiologically based pharmacokinetic models: prediction of the disposition of fentanyl and pethidine in humans by successively simplified models.

Authors:  Sven Björkman
Journal:  J Pharmacokinet Pharmacodyn       Date:  2003-08       Impact factor: 2.745

8.  Homology modeling and virtual screening studies of FGF-7 protein-a structure-based approach to design new molecules against tumor angiogenesis.

Authors:  Rajender Vadija; Kiran Kumar Mustyala; Navaneetha Nambigari; Ramasree Dulapalli; Rama Krishna Dumpati; Vishwanath Ramatenki; Santhi Prada Vellanki; Uma Vuruputuri
Journal:  J Chem Biol       Date:  2016-06-18

9.  Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates.

Authors:  Patrizia Crivori; Ismael Zamora; Bill Speed; Christian Orrenius; Italo Poggesi
Journal:  J Comput Aided Mol Des       Date:  2004-03       Impact factor: 3.686

Review 10.  The role of multiscale computational approaches for rational design of conventional and nanoparticle oral drug delivery systems.

Authors:  Nahor Haddish-Berhane; Jenna L Rickus; Kamyar Haghighi
Journal:  Int J Nanomedicine       Date:  2007
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