New method for semi-automated harmonization and selection of chemical data
An article with the title Semi-automated harmonization and selection of chemical data for risk and impact assessment, written by the Mistra SafeChem researcher Peter Fantke together with Nicolò Aurisano, both from DTU, is published in the journal Chemosphere.
– In this study, we developed a semi-automated method for deriving appropriate substance property values as input for various risk and impact assessment frameworks with different requirements for resolution and data quality, says Peter Fantke.
The proposed method was tested on a set of octanol-water partition coefficients (Kow) reported for a set of 20 example substances.
The method applies to any set of substances and can assess specific distribution in quality and variability across reported data. Further research can likely extend the method for mining information from text fields and adapt it to available data reported or collected from other sources and other substance properties to improve the reliability of input data for risk and impact assessment.
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