A Systematic Approach for Evaluating the Quality of Experimental Toxicological and Ecotoxicological Data

Klimisch, H.-J.; Andreae, Meinrat O.; Tillmann, U

doi:10.1006/rtph.1996.1076

Cited by 977 publications

(756 citation statements)

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“…concordance between two or more independently conducted tests. The CS is the ratio of number of test values (n) and relative standard deviation (RSD) of test results, as defined in Equation 1. Thus, if the same compound was tested independently with the same 4 assay and the results were comparable, there will be a high CS for this compound and the associated experimental values.…”

Section: Introductionmentioning

confidence: 99%

Data Quality in the Human and Environmental Health Sciences: Using Statistical Confidence Scoring to Improve QSAR/QSPR Modeling

Steinmetz

Madden

Cronin

2015

J. Chem. Inf. Model.

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ABSTRACT:A greater number of toxicity data are becoming publicly available allowing for in silico modelling. However, questions often arise as how to incorporate data quality and how to deal with contradicting data if more than a single datum point is available for the same compound. In this study, two well-known and studied QSAR/QSPR models for skin permeability and aquatic toxicology have been investigated in the context of statistical data quality. In particular, the potential benefits of the incorporation of the statistical Confidence Scoring (CS) approach within modelling and validation. As a result, robust QSAR/QSPR models for the skin permeability coefficient and the toxicity of non-polar narcotics to Aliivibrio fischeri assay were created. CSweighted linear regression for training and CS-weighted root mean square error (RMSE) for validation were statistically superior compared to standard linear regression and standard RMSE.Strategies are proposed as to how to interpret data with high and low CS, as well as how to deal with large datasets containing multiple entries.

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Section: Introductionmentioning

confidence: 99%

Data Quality in the Human and Environmental Health Sciences: Using Statistical Confidence Scoring to Improve QSAR/QSPR Modeling

Steinmetz

Madden

Cronin

2015

J. Chem. Inf. Model.

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“…The four evaluation methods used in this study are described by Klimisch et al [10], Durda and Preziosi [11], Hobbs et al [12], and Schneider et al [13]. The reporting requirements from the OECD guidelines 201, 210, and 211 were used as a reference in the evaluation of the four methods.…”

Section: Evaluation Of Existing Reliability Evaluation Methodsmentioning

confidence: 99%

“…Both Klimisch et al [10] and Durda and Preziosi [11] have evaluation criteria that are wide and imprecise which opens up for a variety of different interpretations and opinions. Schneider et al [13] evaluation question is also wide and concerns relevance, rather than reliability.…”

Section: Usefulness Of Proposed Criteriamentioning

confidence: 99%

Comparison of four different methods for reliability evaluation of ecotoxicity data: a case study of non-standard test data used in environmental risk assessments of pharmaceutical substances

2011

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Background: Standard test data are still preferred and recommended for regulatory environmental risk assessments of pharmaceuticals even though data generated by non-standard tests could improve the scientific basis of risk assessments by providing relevant and more sensitive endpoints. The aim of this study was to investigate if non-standard ecotoxicity data can be evaluated systematically in risk assessments of pharmaceuticals. This has been done by evaluating the usefulness of four reliability evaluation methods, and by investigating whether recently published non-standard ecotoxicity studies from the open scientific literature fulfill the criteria that these methods propose.Results: The same test data were evaluated differently by the four methods in seven out of nine cases. The selected non-standard test data were considered reliable/acceptable in only 14 out of 36 cases. Conclusions: The four evaluation methods differ in scope, user friendliness, and how criteria are weighted and summarized. This affected the outcome of the data evaluation. The results suggest that there is room for improvements in how data are reported in the open scientific literature. Reliability evaluation criteria could be used as a checklist to ensure that all important aspects are reported and thereby increasing the possibility that the data could be used for regulatory risk assessment.

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“…The reliability, relevance, and adequacy of all the data that included acute and chronic lethal toxicity data and chronic reproductive toxicity data were then evaluated by standard methods (European Commission, 2003;Klimisch et al, 1997). Data were collected for at least 10 species at three trophic levels (e.g., algae, crustaceans, and fish).…”

Section: Toxicological Data Collectionmentioning

confidence: 99%

Predicted no-effect concentrations for mercury species and ecological risk assessment for mercury pollution in aquatic environment

Wei

Tan

et al. 2015

Journal of Environmental Sciences

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Mercury (Hg) exists in different chemical forms presenting varied toxic potentials. It is necessary to explore an ecological risk assessment method for different mercury species in aquatic environment. The predicted no-effect concentrations (PNECs) for Hg(II) and methyl mercury (MeHg) in the aqueous phase, calculated using the species sensitivity distribution method and the assessment factor method, were 0.39 and 6.5 × 10 −3 μg/L, respectively. The partition theory of Hg between sediment and aqueous phases was considered, along with PNECs for the aqueous phase to conduct an ecological risk assessment for Hg in the sediment phase. Two case studies, one in China and one in the Western Black Sea, were conducted using these PNECs. The toxicity of mercury is heavily dependent on their forms, and their potential ecological risk should be respectively evaluated on the basis of mercury species.

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A Systematic Approach for Evaluating the Quality of Experimental Toxicological and Ecotoxicological Data

Cited by 977 publications

References 0 publications

Data Quality in the Human and Environmental Health Sciences: Using Statistical Confidence Scoring to Improve QSAR/QSPR Modeling

Data Quality in the Human and Environmental Health Sciences: Using Statistical Confidence Scoring to Improve QSAR/QSPR Modeling

Comparison of four different methods for reliability evaluation of ecotoxicity data: a case study of non-standard test data used in environmental risk assessments of pharmaceutical substances

Predicted no-effect concentrations for mercury species and ecological risk assessment for mercury pollution in aquatic environment

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