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Träfflista för sökning "L773:0261 1929 srt2:(2010-2014)"

Sökning: L773:0261 1929 > (2010-2014)

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1.
  • Brandmaier, Stefan, et al. (författare)
  • The QSPR-THESAURUS : The Online Platform of the CADASTER Project
  • 2014
  • Ingår i: ATLA (Alternatives to Laboratory Animals). - : SAGE Publications. - 0261-1929. ; 42:1, s. 13-24
  • Tidskriftsartikel (refereegranskat)abstract
    • The aim of the CADASTER project (CAse Studies on the Development and Application of in Silico Techniques for Environmental Hazard and Risk Assessment) was to exemplify REACH-related hazard assessments for four classes of chemical compound, namely, polybrominated diphenylethers, per and polyfluorinated compounds, (benzo)triazoles, and musks and fragrances. The QSPR-THESAURUS website (http: / /qspr-thesaurus.eu) was established as the project's online platform to upload, store, apply, and also create, models within the project. We overview the main features of the website, such as model upload, experimental design and hazard assessment to support risk assessment, and integration with other web tools, all of which are essential parts of the QSPR-THESAURUS.
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2.
  • Cassani, Stefano, et al. (författare)
  • Evaluation of CADASTER QSAR Models for the Aquatic Toxicity of (Benzo)triazoles and Prioritisation by Consensus Prediction
  • 2013
  • Ingår i: ATLA (Alternatives to Laboratory Animals). - : SAGE Publications. - 0261-1929. ; 41:1, s. 49-64
  • Tidskriftsartikel (refereegranskat)abstract
    • QSAR regression models of the toxicity of triazoles and benzotriazoles ([B] TAZs) to an alga (Pseudokirchneriella subcapitata), Daphnia magna and a fish (Onchorhynchus mykiss), were developed by five partners in the FP7-EU Project, CADASTER. The models were developed by different methods - Ordinary Least Squares (OLS), Partial Least Squares (PLS), Bayesian regularised regression and Associative Neural Network (ASNN) - by using various molecular descriptors (DRAGON, PaDEL-Descriptor and QSPR-THESAURUS web). In addition, different procedures were used for variable selection, validation and applicability domain inspection. The predictions of the models developed, as well as those obtained in a consensus approach by averaging the data predicted from each model, were compared with the results of experimental tests that were performed by two CADASTER partners. The individual and consensus models were able to correctly predict the toxicity classes of the chemicals tested in the CADASTER project, confirming the utility of the QSAR approach. The models were also used for the prediction of aquatic toxicity of over 300 (B)TAZs, many of which are included in the REACH pre-registration list, and were without experimental data. This highlights the importance of QSAR models for the screening and prioritisation of untested chemicals, in order to reduce and focus experimental testing.
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3.
  • Durjava, Mojca Kos, et al. (författare)
  • Experimental Assessment of the Environmental Fate and Effects of Triazoles and Benzotriazole
  • 2013
  • Ingår i: ATLA (Alternatives to Laboratory Animals). - : SAGE Publications. - 0261-1929. ; 41:1, s. 65-75
  • Tidskriftsartikel (refereegranskat)abstract
    • The environmental fate and effects of triazoles and benzotriazoles are of concern within the context of chemical regulation. As part of an intelligent testing strategy, experimental tests were performed on endpoints that are relevant for risk assessment. The experimental tests included the assessment of eco-toxicity to an alga, a daphnid and zebrafish embryos, and the assessment of ready biodegradability. Triazole and benzotriazole compounds were selected for testing, based on existing toxicity data for vertebrate and invertebrate species, as well as on the principal component analysis of molecular descriptors aimed at selecting the minimum number of test compounds in order to maximise the chemical domain spanned for both compound classes. The experimental results show that variation in the toxicities of triazoles and benzotriazole across species was relatively minor; in general, the largest factor was approximately 20. The study conducted indicated that triazoles are not readily biodegradable.
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4.
  • Mandenius, Carl-Fredrik, et al. (författare)
  • Toward Preclinical Predictive Drug Testing for Metabolism and Hepatotoxicity by Using In Vitro Models Derived from Human Embryonic Stem Cells and Human Cell Lines - A Report on the Vitrocellomics EU-project
  • 2011
  • Ingår i: ATLA-ALTERNATIVES TO LABORATORY ANIMALS. - : Fund for Replacement of Animals in Medical Experiments; 1999. - 0261-1929 .- 2632-3559. ; 39:2, s. 147-171
  • Tidskriftsartikel (refereegranskat)abstract
    • Drug-induced liver injury is a common reason for drug attrition in late clinical phases, and even for post-launch withdrawals. As a consequence, there is a broad consensus in the pharmaceutical industry, and within regulatory authorities, that a significant improvement of the current in vitro test methodologies for accurate assessment and prediction of such adverse effects is needed. For this purpose, appropriate in vivo-like hepatic in vitro models are necessary, in addition to novel sources of human hepatocytes. In this report, we describe recent and ongoing research toward the use of human embryonic stem cell (hESC)-derived hepatic cells, in conjunction with new and improved test methods, for evaluating drug metabolism and hepatotoxicity. Recent progress on the directed differentiation of human embryonic stem cells to the functional hepatic phenotype is reported, as well as the development and adaptation of bioreactors and toxicity assay technologies for the testing of hepatic cells. The aim of achieving a testing platform for metabolism and hepatotoxicity assessment, based on hESC-derived hepatic cells, has advanced markedly in the last 2-3 years. However, great challenges still remain, before such new test systems could be routinely used by the industry. In particular, we give an overview of results from the Vitrocellomics project (EU Framework 6) and discuss these in relation to the current state-of-the-art and the remaining difficulties, with suggestions on how to proceed before such in vitro systems can be implemented in industrial discovery and development settings and in regulatory acceptance.
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5.
  • Sahlin, Ullrika, et al. (författare)
  • Arguments for considering uncertainty in QSAR predictions in hazard and risk assessments
  • 2013
  • Ingår i: ATLA (Alternatives to Laboratory Animals). - : SAGE Publications. - 0261-1929. ; 41:1, s. 91-110
  • Tidskriftsartikel (refereegranskat)abstract
    • Chemical regulation allows non-in vivo testing (i.e. in silico-derived and in vitro-derived) information to replace experimental values from in vivo studies in hazard and risk assessments. Although non-in vitro testing information on chemical activities or properties is subject to added uncertainty as compared to in vivo testing information, this uncertainty is commonly not (fully) taken into account. Considering uncertainty in predictions from quantitative structure-activity relationships (QSARs), which are a form of non-in vivo testing information, may improve the way that QSARs support chemical safety assessment under the EU Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) system. We argue that it is useful to consider uncertainty in QSAR predictions, as it: a) supports rational decision-making; b) facilitates cautious risk management; c) informs uncertainty analysis in probabilistic risk assessment; d) may aid the evaluation of QSAR predictions in weight-of-evidence approaches; and e) provides a probabilistic model to verify the experimental data used in risk assessment. The discussion is illustrated by using case studies of QSAR integrated hazard and risk assessment from the EU-financed CADASTER project.
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6.
  • Sahlin, Ullrika (författare)
  • Uncertainty in QSAR Predictions
  • 2013
  • Ingår i: ATLA (Alternatives to Laboratory Animals). - : SAGE Publications. - 0261-1929. ; 41:1, s. 111-125
  • Tidskriftsartikel (refereegranskat)abstract
    • It is relevant to consider uncertainty in individual predictions when quantitative structure-activity (or property) relationships (QSARs) are used to support decisions of high societal concern. Successful communication of uncertainty in the integration of QSARs in chemical safety assessment under the EU Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) system can be facilitated by a common understanding of how to define, characterise, assess and evaluate uncertainty in QSAR predictions. A QSAR prediction is, compared to experimental estimates, subject to added uncertainty that comes from the use of a model instead of empirically-based estimates. A framework is provided to aid the distinction between different types of uncertainty in a QSAR prediction: quantitative, i.e. for regressions related to the error in a prediction and characterised by a predictive distribution; and qualitative, by expressing our confidence in the model for predicting a particular compound based on a quantitative measure of predictive reliability. It is possible to assess a quantitative (i.e. probabilistic) predictive distribution, given the supervised learning algorithm, the underlying QSAR data, a probability model for uncertainty and a statistical principle for inference. The integration of QSARs into risk assessment may be facilitated by the inclusion of the assessment of predictive error and predictive reliability into the "unambiguous algorithm", as outlined in the second OECD principle.
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