Validating read-across workflows for N-nitrosamines
To reach conclusions during chemical safety assessments, risk assessors need to ensure sufficient information is present to satisfy the decision criteria. This often requires data to be generated and, in some cases, insufficient knowledge is present, or it is not feasible to generate new data through experiments. Read-across workflows are a powerful technique to fill such data gaps, however the expert-driven process can be time intensive and subjective in nature resulting in variation of approach.
To overcome these barriers a prototype software application has been developed by Lhasa Limited to support decision making about the toxicity and potency of chemicals using a read-across approach. The application supports a workflow which allows the user to gather data and knowledge about a chemical of interest and possible read-across candidates. Relevant information is then presented that enables the user to decide if read-across can be performed and, if so, which analogue or category can be considered the most appropriate. Data and knowledge about the toxicity of a compound and potential analogues include assay and metabolism data, toxicophore identification and its local similarity, physico-chemical and pharmacokinetic properties and observed and predicted metabolic profile. The utility of the approach is demonstrated with case studies using N-nitrosamine compounds, where the conclusions from using the workflow supported by the software are concordant with the evidence base. The components of the workflow have been further validated by demonstrating that conclusions are significantly better than would be expect from the distribution of data in test sets.
The read-across workflows implemented in this software demonstrate how intuitive, guided processes can support expert decisions while validation of these methods enhances confidence in the overall approach.
Digital copy from Computational Toxicology 29 (2024) 100300, is being made available under a CLA licence for online viewing only on 20th December 2024.