Literature DB >> 20017579

Physiologically-based simulation modelling for the reduction of animal use in the discovery of novel pharmaceuticals.

Simon Thomas1.   

Abstract

The global pharmaceutical industry is estimated to use close to 20 million animals annually, in in vivo studies which apply the results of fundamental biomedical research to the discovery and development of novel pharmaceuticals, or to the application of existing pharmaceuticals to novel therapeutic indications. These applications of in vivo experimentation include: a) the use of animals as disease models against which the efficacy of therapeutics can be tested; b) the study of the toxicity of those therapeutics, before they are administered to humans for the first time; and c) the study of their pharmacokinetics - i.e. their distribution throughout, and elimination from, the body. In vivo pharmacokinetic (PK) studies are estimated to use several hundred thousand animals annually. The success of pharmaceutical research currently relies heavily on the ability to extrapolate from data obtained in such in vivo studies to predict therapeutic behaviour in humans. Physiologically-based modelling has the potential to reduce the number of in vivo animal studies that are performed by the pharmaceutical industry. In particular, the technique of physiologically-based pharmacokinetic (PBPK) modelling is sufficiently developed to serve as a replacement for many in vivo PK studies in animals during drug discovery. Extension of the technique to incorporate the prediction of in vivo therapeutic effects and/or toxicity is less well-developed, but has potential in the longer-term to effect a significant reduction in animal use, and also to lead to improvements in drug discovery via the increased rationalisation of lead optimisation. 2009 FRAME.

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Year:  2009        PMID: 20017579     DOI: 10.1177/026119290903700507

Source DB:  PubMed          Journal:  Altern Lab Anim        ISSN: 0261-1929            Impact factor:   1.303


  3 in total

Review 1.  Optimizing nanomedicine pharmacokinetics using physiologically based pharmacokinetics modelling.

Authors:  Darren Michael Moss; Marco Siccardi
Journal:  Br J Pharmacol       Date:  2014-07-02       Impact factor: 8.739

2.  An engineering approach to biomedical sciences: advanced testing methods and pharmacokinetic modeling.

Authors:  Gaetano Lamberti; Sara Cascone; Giuseppe Titomanlio
Journal:  Transl Med UniSa       Date:  2012-10-11

Review 3.  The use of integrated and intelligent testing strategies in the prediction of toxic hazard and in risk assessment.

Authors:  Michael Balls; Robert D Combes; Nirmala Bhogal
Journal:  Adv Exp Med Biol       Date:  2012       Impact factor: 2.622

  3 in total

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