Insilicofirst to debut at SOT, Baltimore March 2009
The first fruits of this initial collaboration will be on show during the Society of Toxicology's 48th Annual Meeting, Baltimore, USA, March 15-19, 2009.
At SOT, Insilicofirst will demonstrate its collaborative capabilities with an integrated common user interface to support chemical toxicity prediction. As a new Alliance with a challenging objective, the four partners are keen to demonstrate their collaborative capabilities by developing a Common User Interface (CUI) using their respective toxicity tools to query their databases, access prediction capabilities and generate metabolites. While their existing tools do not fully cover the environmental space at this stage, the CUI is meant to demonstrate collaborative alliance between the four Founding Partners and give customers a single point-of-access to their powerful technologies.
The success of this endeavour will provide demonstrable evidence of the way Insilicofirst will set about creating the world's fastest and easiest to use suite of tools to support the prediction of environmental toxicity. Insilicofirst will collaborate next on developing an integrated prediction system to support environmental toxicological assessment.
Next, Insilicofirst will collaborate on developing an integrated prediction system to support environmental toxicological assessment. The success of this endeavour will provide demonstrable evidence of the way Insilicofirst will set about creating the world's fastest and easiest to use suite of tools to support the prediction of toxicity.
The Mission of Insilicofirst
Via one simple interface the new environmental toxicity application from Insilicofirst will integrate tools commonly available in silico prediction methodologies to provide the data and predictions detailed below, relating to the environmental impact of a chemical structure input by the user.
- Toxicity assessment covering both ecological and human health hazards. These will include metabolism and chemical reactivity predictions such as those provided by Lhasa Limited's METEOR, abiotic and biotic reactions from Molecular Networks and results from external models.
- Data about similar chemicals.
- Physicochemical data and data from in vitro or in chemico screens potentially relevant to (Q)SAR models.
- Information about confidence and reliability plus qualitative guidance on how successful the model has been for other, similar chemicals.
Reports will allow the user to see overall conclusions and details with accompanying reasoning. Supporting evidence and data, potential biodegradants and the tools and models that trigger the results will all be available for the user to explore. Insilicofirst exists to deliver the best tools to support the prediction of environmental toxicity to those immediately affected by REACH.
The Benefits for those using the Insilicofirst tool
The Insilicofirst collaboration will address the need to reduce the amount of time spent by scientists in referencing disparate sources of data to aid decision making related to environmental toxicity. Also, it will offer an efficient and cost-effective response to the EU REACH legislation and the desire to reduce animal testing. Financial and time costs will be dramatically reduced through the provision of a predictive in silico software device containing a high quality knowledge base built from diverse and reliable data sources.
Insilicofirst is a new collaboration of the world's leading organisations in toxicity prediction systems, uniting:
in a partnership combining highly regarded scientific knowledge with expertise in in silico predictive software development.
Join the Insilicofirst collaboration now as a Founding Member
Insilicofirst seeks sponsor organisations who want to be founding members of this collaborative programme. The first four Founding Partners of Insilicofirst are seeking further sponsor organisations to join this collaborative group.
A key contribution of these new members will be their contribution of expert knowledge and existing data relating to environmental chemistry. This valuable input will provide the basis of deriving generic structure activity rules for the Insilicofirst predictive software programs.
Confidential data sharing between various sponsoring organisations will lead to the development of a high quality knowledge base for Insilicofirst, thereby increasing the reliability of results provided by the software.
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