In industrialized countries, 20 - 30% of the population are affected by allergies, tendency rising. Our immune system is confronted with many substances that could trigger irritating or sensibilizing reactions. The spectrum of these substances reaches from well defined chemicals to complex mixtures. With ongoing development, materials used for medical devices, textiles, plastics and other products in contact with skin grow more and more complex, which warrants sensible and accurate methods to test their sensitizing and irritating potential. Up to now, the "gold standard" are experiments in animals. However, mounting ethical and political pressure will lead to a stepwise banishment of these. Although reliable in vitro methods have been suggested by several authors, noen of them has been validated with complex mixtures. The aim of this project is the development of a validated in vitro screening method to estimate the skin irritating and sensitizing potential of new materials with a focus on complex mixtures. It will encompass the establishment of suitable extraction methods to mimic the situation on the skin, combined with sensible tests in relevant cell systems. These tests will be designed combining maximal sensibility and sensitivity with reasonable costs and upscalability. ScienceConsult contributes to this effort by developing inexpensive alternatives to the MUSST and h-CLAT test and providing know how to integrate these tests into the envisioned test-panel. This work is done in concert of a consortium consisting of the OFI Innovations und Technologie GmbH (chair of the consortium), the FH Campus Vienna and the Medical University of Vienna, Researchgroup Cell Biology.

To put the results of mass throughput experiments into biological context, modern bioinformatics has to rely on fast state-of-the-art hard and software. For this reason, ScienceConsult has leased another modern server, based on OpenSuSE linux and providing a panel of open-source tools that will facilitate the analysis of next generation sequencing, microarray or proteomics data.