Open Access

New regulations for animal research – a chance to shine for in silico approaches

In Silico Pharmacology20153:1

DOI: 10.1186/s40203-015-0006-1

Received: 30 January 2015

Accepted: 30 January 2015

Published: 10 February 2015

The legal landscape for animal experimentation is rapidly changing. Progress in global regulatory frameworks to improve the protection of animals already has significant implications well beyond academic research. Particularly, the European Union Directives Directive 2010/63/EU 2010 on the protection of animals used for scientific purposes, and Cosmetics Directive 76/768/EEC 1976, a complete ban on the use of animals for cosmetic testing in 2013, impose strong constraints on academia and industry. Hence there is a strong need to improve the welfare of animals, fortify the three R’s principles (Replace, Reduce and Refine use of animals) in EU legislation, and provide alternative approaches for animal research and the testing of new cosmetics. The new regulations are by no means an exclusive European affaire, as they have been reinforced globally by bi- and multi-lateral cooperations.

Therefore, these new regulations will ultimately reshape our way of thinking about basic and preclinical experimental design, by not only limiting the sample size of experiments, but also adding critical restrictions on procedures that require alternative, quantitatively-defined frameworks for experimental setups and analyses. While the three R’s challenge traditional concepts in animal studies, which equate an increase in sample size with an improvement in the robustness of experimental results, they provide a great chance for in silico approaches (Noori and Spanagel 2013) to shine.

Ligand- and structure-based virtual screening procedures for drug discovery (Rester 2008), computational pharmacokinetics (Bois 2013), in silico screening procedures to investigate systemic drug effects (Noori and Jäger 2010; Noori et al. 2012a), mathematically-based optimal experimental design (Fedorov et al. 2002) and novel biostatistical approaches (Beery and Zucker 2011; Noori et al. 2012b) not only bear the potential to improve animal experiments, but can also reduce the number of animals used by eliminating unnecessary testing (e.g., via meta-analysis studies).

In Silico Pharmacology provides an optimal electronic platform for studies in these fields, and through emphasis on the three R’s intends to assist animal researchers in overcoming present and future challenges, contributing to a modernization of their research concepts. In particular, by being indexed in the largest database of biomedical articles established by the US National Library of Medicine (PubmedCentral:, it has begun to bring its computer-based publications closer to end-user experimentalist readership and facilitate communication in the interface area of dry- and wet-laboratories.

Authors’ Affiliations

Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg


  1. (2010) Directive 2010/63/Eu of the European parliament and of the council of 22 September 2010 on the protection of animals used for scientific purposes.
  2. (1976) Cosmetics directive 76/768/EEC.
  3. Beery AK, Zucker I (2011) Sex bias in neuroscience and biomedical research. Neurosci Biobehav Rev 35(3):565–572View ArticlePubMed CentralPubMedGoogle Scholar
  4. Bois FY (2013) Computational pharmacokinetics at a crossroads. In Silico Pharmacol 1:5View ArticlePubMed CentralPubMedGoogle Scholar
  5. Fedorov V, Gagnon R, Leonov S (2002) Design of experiments with unknown parameters in variance. Appl Stoch Model Bus Ind 18:207–218View ArticleGoogle Scholar
  6. Noori HR, Spanagel R (2013) In silico pharmacology: drug design and discovery’s gate to the future. In Silico Pharmacol 1:1View ArticlePubMed CentralPubMedGoogle Scholar
  7. Noori HR, Spanagel R, Hansson AC (2012a) Neurocircuitry for modeling drug effects. Addict Biol 17(5):827–864View ArticlePubMedGoogle Scholar
  8. Noori HR, Fliegel S, Brand I, Spanagel R (2012b) The impact of acetylcholinesterase inhibitors on the extracellular acetylcholine concentrations in the adult rat brain: a meta-analysis. Synapse 66(10):893–901View ArticlePubMedGoogle Scholar
  9. Noori HR, Jäger W (2010) Neurochemical oscillations in the basal ganglia. Bull Math Biol 72(1):133–147View ArticlePubMedGoogle Scholar
  10. Rester U (2008) From virtuality to reality - virtual screening in lead discovery and lead optimization: a medicinal chemistry perspective. Curr Opin Drug Discov Devel 11(4):559–568PubMedGoogle Scholar


© Noori and Spanagel; licensee Springer. 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.