Literature DB >> 24534000

Regulatory acceptance and use of 3R models for pharmaceuticals and chemicals: expert opinions on the state of affairs and the way forward.

Marie-Jeanne W A Schiffelers1, Bas J Blaauboer2, Wieger E Bakker3, Sonja Beken4, Coenraad F M Hendriksen5, Herman B W M Koëter6, Cyrille Krul7.   

Abstract

Pharmaceuticals and chemicals are subjected to regulatory safety testing accounting for approximately 25% of laboratory animal use in Europe. This testing meets various objections and has led to the development of a range of 3R models to Replace, Reduce or Refine the animal models. However, these models must overcome many barriers before being accepted for regulatory risk management purposes. This paper describes the barriers and drivers and options to optimize this acceptance process as identified by two expert panels, one on pharmaceuticals and one on chemicals. To untangle the complex acceptance process, the multilevel perspective on technology transitions is applied. This perspective defines influences at the micro-, meso- and macro level which need alignment to induce regulatory acceptance of a 3R model. This paper displays that there are many similar mechanisms within both sectors that prevent 3R models from becoming accepted for regulatory risk assessment and management. Shared barriers include the uncertainty about the value of the new 3R models (micro level), the lack of harmonization of regulatory requirements and acceptance criteria (meso level) and the high levels of risk aversion (macro level). In optimizing the process commitment, communication, cooperation and coordination are identified as critical drivers.
Copyright © 2014 Elsevier Inc. All rights reserved.

Keywords:  3R models; Chemicals; Drivers and barriers; Multilevel perspective on technology transitions; Pharmaceuticals; Regulatory acceptance and use; Risk assessment

Mesh:

Year:  2014        PMID: 24534000     DOI: 10.1016/j.yrtph.2014.02.007

Source DB:  PubMed          Journal:  Regul Toxicol Pharmacol        ISSN: 0273-2300            Impact factor:   3.271


  2 in total

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Authors:  Satwant Kaur; Susan Jobling; Catherine S Jones; Leslie R Noble; Edwin J Routledge; Anne E Lockyer
Journal:  PLoS One       Date:  2015-04-07       Impact factor: 3.240

2.  Anti-adenoviral Artificial MicroRNAs Expressed from AAV9 Vectors Inhibit Human Adenovirus Infection in Immunosuppressed Syrian Hamsters.

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Journal:  Mol Ther Nucleic Acids       Date:  2017-07-08       Impact factor: 8.886

  2 in total

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