In March 2013 the final deadline to phase out animal testing for cosmetic products in Europe passed. This resulted in a ban on cosmetics that were tested on animals being marketed within the European Union (EU).
The regulation Directive 2003/15/EC introduced provisions in relation to animal testing into the Cosmetic Directive 76/768/EEC. Animal testing has been banned for finished cosmetic products since 2004, and prohibited for cosmetic ingredients as of 2009; it has been aptly named the testing ban. In order to meet the requirements of the Directive, the new 'marketing ban' has also prohibited market cosmetic products containing ingredients which have been tested on animals in the EU.
For the most complex tests such as repeated-dose toxicity, including skin sensitisation and carcinogenicity, reproductive toxicity and toxicokinetics the marketing ban deadline had been extended to March 2013. This meant that companies could still carry out tests outside of the EU for cosmetic purposes, and rely on the results for the safety assessment in the EU. However, this is no longer possible.
The number of animals used for cosmetic purposes in the EU has been declining. In 2004, the number stood at 8,988 but remarkably this had reduced to 344 by 2009. Any animal testing conducted for EU cosmetic purposes since 2009 has been undertaken outside of the EU, with between 15,000 and 27,000 animals estimated to have been used yearly.
The European Commission has been supporting research into finding alternatives to animal testing, and between 2007 to 2011 around 238 million was made available for this purpose, in addition to contributions from the cosmetics industry, which is worth more than 70 billion annually.
Researchers have made a great deal of progress and several alternative testing methods have been validated by the EU Reference Laboratory for Alternatives to Animal Testing which have subsequently been included in the Organisation for Economic Co-Operation and Development testing guidelines.
One such research initiative, dedicated to developing and optimising in vitro test strategies that could reduce or replace animal testing for sensitisation studies, was lead by Malin Lindstedt, Associate Professor at the Department of Immunotechnology at Lund University, Sweden, and Professor Carl Borrebaeck, Vice Chancellor of Lund University. In this study, named Genomic Allergen Rapid Detection (GARD), a substantial amount of the analyses currently focuses on two key areas: looking for new biomarkers in cancer studies, and performing important research on allergens.
Most of the software that has been designed for use in this area has mainly focused on the ability to handle increasingly vast amounts of data, which means that the role of the scientist/researcher has been largely set aside. As a result, a lot of data analysis has been passed on to bioinformaticians and biostatisticians. However, in most cases, this model has several drawbacks, since it is typically the scientists themselves who know the most about biology.
The latest generation of bioinformatics software now enables scientists to analyse large data sets easily by using a combination of statistical methods such as analysis of variance and visualisation techniques such as heatmaps and principal component analysis (PCA). Heatmaps are a 2D visualisation technique, whereas PCA makes it possible to use 3D. PCA is a good way of visualising large datasets, since the method does not make any assumptions regarding potential groups or clusters in the data, but presents an optimal projection of the dataset to the first three principal components.
With the benefit of instant user feedback on all actions, as well as an intuitive user interface that can present all data in 3D, researchers can now easily analyse their data in real-time, directly on their computer screen. The effects of instant data visualisation, powered by an easy-to-understand user interface, makes it possible for scientists and bioinformaticians to work side by side and creatively discuss alternative hypothesis. A fast and intuitive software programme also allows scientists to test multiple ideas in a short amount of time and allows the team to enhance the results.
With the freedom, speed and flexibility provided by this approach, it is now possible to evaluate and test a number of different scenarios in a short amount of time, and to fully understand the data being examined. This technique makes it possible for researchers to combine large amounts of data, and thereby conduct analyses in ways that were not possible before.
This approach was used by the team at GARD for the prediction of sensitising chemicals (1). By analysing the transcriptome of the human cell line MUTZ-3 after 24-hour stimulation using 20 different sensitising chemicals, 20 non-sensitising chemicals and vehicle controls the researchers identified a biomarker signature of 200 genes with potent discriminatory ability.
In addition to this, by categorising the chemicals according to the local lymph node assay, this gene signature showed potential as a way of predicting sensitising potency. The identified markers are involved in biological pathways with immunological relevant functions, which can shed light on the process of human sensitisation.
As a result of these studies, a highly accurate gene signature predicting sensitisation, using a human cell line in vitro, has now been identified, with the potential to completely replace or drastically reduce the utilisation of test systems based on experimental animals. Being based on human cells and biology, the assay is proposed to be more accurate for predicting sensitisation in humans than the traditional animal-based tests.
1. Albrekt AS and Borrebaeck CAK, BMC Genomics 12: p399, 2011