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

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.

Keywords:

• data quality
• reliability
• Klimisch scheme
• ToxRTool
• Good Laboratory Practice (GLP)
• REACH
• integrated testing strategies (ITS)

Acknowledgments

Funding was provided by the European Union 6th Framework Programme OSIRIS Integrated Project (GOCE-037017-OSIRIS) and via the eTOX project, grant agreement number 115002 under the Innovative Medicines Initiative Joint Undertaking (IMI-JU). Neither the OSIRIS or eTOX projects had any influence or involvement in the production of this article.