- Publisher:Lhasa Limited
- Publication Date:Mar 2016
- Publication Type:Poster
- Scientific Area:
- Industry Type:
Improvements to In Silico Skin Sensitization Predictivity After Access to Proprietary Data
Skin sensitisation, leading to allergic contact dermatitis, is one of the most common health issues encountered in occupational settings. Occupational dermal sensitisation affects numerous industries, including the cosmetic, pharmaceutical, and construction industries, and is estimated to cost the EU €600 million per year and 3 million working days. Similarly, in the United States skin conditions are amongst the most frequently reported occupational illnesses and cost upwards of $1 billion annually. For hazard identification purposes, there exists a need for tools capable of providing rapid and accurate assessments of this sensitisation potential. Given the desire to comply with the 3Rs principle (reduce, refine, replace), these tools should rely on in vitro and/or in silico methods rather than in vivo animal testing such as the local lymph node assay (LLNA). Of particular importance are sensitisers mispredicted in silico as non-sensitisers (false negatives) - as these can cause significant harm to exposed individuals.
Derek Nexus and data sharing
Derek Nexus skin sensitisation alerts are built almost entirely on public data. Proprietary data often covers novel chemical space - therefore sharing of said data can lead to new alerts and improve existing alert domains. Despite this, there have been few skin sensitisation data-sharing initiatives thus far. This is in direct contrast to the genetic toxicology field where collaborations on areas of mutual interest are becoming the norm (e.g. Consortium for the Investigation of Genotoxicity of Aromatic Amines (CIGAA)). As a consequence of this, 25% of Derek Nexus mutagenicity alerts have been derived from proprietary data. This is not the case for skin sensitisation alerts.
Poster presented by Donna Macmillan at the 55th SOT, New Orleans, USA; 14th March 2016