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Such systems will be illustrated through examples like antidepressants and (daily exposure) environmental chemicals. Rhodes, September 19-24, 2010 37 PLENARY LECTURE 9 RODENT TOXICITY STUDIES ON PERFLUORINATED CHEMICALS FOR REACH Barun Bhhatarai, Paola Gramatica Department of Structural and Functional Biology (DBSF), University of Insubria, 21100 Varese, Italy Perfluorooctane sulfonic acid (PFOSH) and Perfluoro-octanoic acid (PFOA) are long chain perfluorinated chemicals (PFCs) which are categorized by US-EPA and EU-REACH as toxic chemicals1.
2008, 6 (4), 709-725 Rhodes, September 19-24, 2010 61 ORAL PRESENTATION 8 USING LOCAL MODELS TO IMPROVE QSAR PREDICTIVITY Fabian Buchwald, Tobias Girschick, Madeleine Seeland and Stefan Kramer Institut für Informatik I12, Technische Universität München, Germany In a recent paper, Benigni and Bossa  found that local QSAR models can produce results that are mechanistically interpretable and compare favorably with the known limits in reproducibility of the experimental systems. However, many existing large databases cannot be used directly to build local QSAR models, because they contain diverse sets of non-congeneric structures.
The results demonstrated the use and importance of predictive QSAR models highlighting the utility of QSAR for REACH. (Financial support by European Union through the project CADASTER FP7-ENV-2007-1-212668) References: 1. 2. 3. 4. 5. 6. 7. reference=IP/06/1479 Renner R. Environ. Sci. Technol. 2003, 37, 201A. , Gramatica P. Chem. Res. , 2010, 23, 528–539. Gramatica, P. QSAR Comb. Sci. aspx 18th European Symposium on Quantitative Structure-Activity Relationships PLENARY LECTURE 10 INTEGRATIVE PHAMACOINFORMATICS APPROACHES IN THE PREDICTION OF CLINICAL OUTCOMES OF DRUGS Ferran Sanz Research Programme on Biomedical Informatics (GRIB) IMIM - Universitat Pompeu Fabra Barcelona, Spain The final aim of most (Q)SAR studies is the computer-aided prediction of clinical outcomes of drugs by means of the (quantitative) modeling of the relationships existing between the chemical, structural and biological features.
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