Literature DB >> 22507180

Assessing toxicological data quality: basic principles, existing schemes and current limitations.

K R Przybylak1, J C Madden, M T D Cronin, M Hewitt.   

Abstract

Existing toxicological data may be used for a variety of purposes such as hazard and risk assessment or toxicity prediction. The potential use of such data is, in part, dependent upon their quality. Consideration of data quality is of key importance with respect to the application of chemicals legislation such as REACH. Whether data are being used to make regulatory decisions or build computational models, the quality of the output is reflected by the quality of the data employed. Therefore, the need to assess data quality is an important requirement for making a decision or prediction with an appropriate level of confidence. This study considers the biological and chemical factors that may impact upon toxicological data quality and discusses the assessment of data quality. Four general quality criteria are introduced and existing data quality assessment schemes are discussed. Two case study datasets of skin sensitization data are assessed for quality providing a comparison of existing assessment methods. This study also discusses the limitations and difficulties encountered during quality assessment, including the use of differing quality schemes and the global versus chemical-specific assessments of quality. Finally, a number of recommendations are made to aid future data quality assessments.

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Year:  2012        PMID: 22507180     DOI: 10.1080/1062936X.2012.664825

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  4 in total

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Journal:  Nanoscale       Date:  2016-05-04       Impact factor: 7.790

2.  From data point timelines to a well curated data set, data mining of experimental data and chemical structure data from scientific articles, problems and possible solutions.

Authors:  Villu Ruusmann; Uko Maran
Journal:  J Comput Aided Mol Des       Date:  2013-07-25       Impact factor: 3.686

3.  In Silico Models for Repeated-Dose Toxicity (RDT): Prediction of the No Observed Adverse Effect Level (NOAEL) and Lowest Observed Adverse Effect Level (LOAEL) for Drugs.

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Journal:  Methods Mol Biol       Date:  2022

Review 4.  Functional Role of circRNAs in the Regulation of Fetal Development, Muscle Development, and Lactation in Livestock.

Authors:  Tianle He; Qingyun Chen; Ke Tian; Yinzhao Xia; Guozhong Dong; Zhenguo Yang
Journal:  Biomed Res Int       Date:  2021-02-19       Impact factor: 3.411

  4 in total

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