New Version of the OECD eChemPortal is Now Online
News Dec 08, 2010
A new version of the eChemPortal has been launched by OECD. It provides free public access to information on more than 600 000 records on chemical substances.
By launching the new eChemPortal, the OECD has reached a new milestone in the long-standing international commitment to making publicly available information on chemical properties. This entirely revamped eChemPortal adds new useful features that enhance users’ search functionalities.
Improvements include a search by chemical property, in addition to a search by substance name and identification number. For the first time, users can search for chemical using properties criteria such as physical chemical properties, environmental fate and behavior, ecotoxicity and toxicity in the participating databases that can offer direct searching of endpoint data.
All participating databases offer direct searching by substance identification. The information on existing chemicals, new industrial chemicals, pesticides and biocides is being made available by 19 participating databases gathering information prepared for government chemical review programmes at national, regional, and international levels.
Some of these, such as the ECHA dissemination database, US EPA Aggregated Computational Toxicology Resource (ACToR), the United Kingdom Coordinated Chemicals Risk Management Programme Publications (UK CCRMP Outputs) and US Environmental Protection Agency Integrated Risk Information System (US EPA IRIS) have only recently adhered to this project.
New web links allow users to retrieve also information according to the Globally Harmonized System of Classification and Labelling of Chemicals (GHS). This includes the GHS classification of approximately 1,500 chemicals stored by the Japanese government.
The new eChemPortal is a project developed by OECD in collaboration with ECHA.
Computer bits are binary, with a value of 0 or 1. By contrast, neurons in the brain can have all kinds of different internal states, depending on the input that they received. This allows the brain to process information in a more energy-efficient manner than a computer. A new study hopes to bring the two closer together.
MIT researchers have developed a cryptographic system that could help neural networks identify promising drug candidates in massive pharmacological datasets, while keeping the data private. Secure computation done at such a massive scale could enable broad pooling of sensitive pharmacological data for predictive drug discovery.