A scheme to evaluate structural alerts to predict toxicity – Assessing confidence by characterising uncertainties

https://doi.org/10.1016/j.yrtph.2022.105249Get rights and content
Under a Creative Commons license
open access

Highlights

  • Structural alerts are useful tools for predictive toxicology.

  • 12 criteria to evaluate structural alerts have been identified.

  • A strategy to determine confidence of structural alerts is presented.

  • Different use cases require different characteristics of structural alerts.

  • A Scheme to Evaluate Structural Alerts to Predict Toxicity – Assessing Confidence By Characterising Uncertainties.

Abstract

Structure-activity relationships (SARs) in toxicology have enabled the formation of structural rules which, when coded as structural alerts, are essential tools in in silico toxicology. Whilst other in silico methods have approaches for their evaluation, there is no formal process to assess the confidence that may be associated with a structural alert. This investigation proposes twelve criteria to assess the uncertainty associated with structural alerts, allowing for an assessment of confidence. The criteria are based around the stated purpose, description of the chemistry, toxicology and mechanism, performance and coverage, as well as corroborating and supporting evidence of the alert. Alerts can be given a confidence assessment and score, enabling the identification of areas where more information may be beneficial. The scheme to evaluate structural alerts was placed in the context of various use cases for industrial and regulatory applications. The analysis of alerts, and consideration of the evaluation scheme, identifies the different characteristics an alert may have, such as being highly specific or generic. These characteristics may determine when an alert can be used for specific uses such as identification of analogues for read-across or hazard identification.

Keywords

Structural alert
Structure-activity relationship
Toxicity prediction
Confidence
Uncertainty
Evaluation scheme
Use case
Computational toxicology

Abbreviations

AChE
acetylcholinesterase
AOP
Adverse Outcome Pathway
EFSA
European Food Safety Authority
HPV
High Production Volume
KE
Key Event
MIE
Molecular Initiating Event
OECD
Organisation for Economic Cooperation and Development
QMRF
QSAR Model Reporting Format
QPRF
QSAR Prediction Report Format
QSAR
quantitative structure-activity relationship
RAAF
Read-Across Assessment Framework
SAR
structure-activity relationship

Cited by (0)