Literature DB >> 25794480

Ensuring confidence in predictions: A scheme to assess the scientific validity of in silico models.

Mark Hewitt1, Claire M Ellison2, Mark T D Cronin3, Manuel Pastor4, Thomas Steger-Hartmann5, Jordi Munoz-Muriendas6, Francois Pognan7, Judith C Madden8.   

Abstract

The use of in silico tools within the drug development process to predict a wide range of properties including absorption, distribution, metabolism, elimination and toxicity has become increasingly important due to changes in legislation and both ethical and economic drivers to reduce animal testing. Whilst in silico tools have been used for decades there remains reluctance to accept predictions based on these methods particularly in regulatory settings. This apprehension arises in part due to lack of confidence in the reliability, robustness and applicability of the models. To address this issue we propose a scheme for the verification of in silico models that enables end users and modellers to assess the scientific validity of models in accordance with the principles of good computer modelling practice. We report here the implementation of the scheme within the Innovative Medicines Initiative project "eTOX" (electronic toxicity) and its application to the in silico models developed within the frame of this project.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Good computer modelling practice; Model reliability; Peer-verification; QSAR; Toxicity prediction; Validation

Mesh:

Year:  2015        PMID: 25794480     DOI: 10.1016/j.addr.2015.03.005

Source DB:  PubMed          Journal:  Adv Drug Deliv Rev        ISSN: 0169-409X            Impact factor:   15.470


  2 in total

1.  Legacy data sharing to improve drug safety assessment: the eTOX project.

Authors:  Ferran Sanz; François Pognan; Thomas Steger-Hartmann; Carlos Díaz; Montserrat Cases; Manuel Pastor; Philippe Marc; Joerg Wichard; Katharine Briggs; David K Watson; Thomas Kleinöder; Chihae Yang; Alexander Amberg; Maria Beaumont; Anthony J Brookes; Søren Brunak; Mark T D Cronin; Gerhard F Ecker; Sylvia Escher; Nigel Greene; Antonio Guzmán; Anne Hersey; Pascale Jacques; Lieve Lammens; Jordi Mestres; Wolfgang Muster; Helle Northeved; Marc Pinches; Javier Saiz; Nicolas Sajot; Alfonso Valencia; Johan van der Lei; Nico P E Vermeulen; Esther Vock; Gerhard Wolber; Ismael Zamora
Journal:  Nat Rev Drug Discov       Date:  2017-10-13       Impact factor: 84.694

2.  Development of an Infrastructure for the Prediction of Biological Endpoints in Industrial Environments. Lessons Learned at the eTOX Project.

Authors:  Manuel Pastor; Jordi Quintana; Ferran Sanz
Journal:  Front Pharmacol       Date:  2018-10-11       Impact factor: 5.810

  2 in total

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