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In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs.

Raymond R Tice1, Arianna Bassan2, Alexander Amberg3

  • 1RTice Consulting, Hillsborough, North Carolina, 27278, USA.

Computational Toxicology (Amsterdam, Netherlands)
|April 4, 2022
PubMed
Summary

Developing robust in silico carcinogenicity models is crucial for regulatory science. This study assesses current computational tools for key characteristics of carcinogens, identifying gaps for improved regulatory acceptance.

Keywords:
(Q)SARCancerCarcinogenesisComputational ToxicologyExpert AlertsHazard IdentificationIn SilicoKey CharacteristicsRead-acrossRisk Assessment

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Area of Science:

  • Toxicology
  • Computational Science
  • Regulatory Science

Background:

  • Traditional rodent carcinogenicity studies are resource-intensive.
  • Existing in silico models for carcinogen prediction lack broad regulatory acceptance due to protocol and performance limitations.
  • There is a need for improved, human-relevant in silico carcinogenicity models for research and regulatory use.

Purpose of the Study:

  • To evaluate the availability of in silico models for the 10 key characteristics (KCs) of carcinogens.
  • To identify data gaps hindering the development of comprehensive in silico carcinogenicity assessment protocols.
  • To inform future development of in silico toxicological protocols for regulatory applications.

Main Methods:

  • An international consortium of toxicologists, computational scientists, and regulatory scientists was formed.
  • The consortium assessed the current status of in silico tools for each of the 10 KCs of carcinogens.
  • Data gaps were identified for each KC to guide future research and development.

Main Results:

  • The study provides a summary of existing in silico tools for assessing carcinogen KCs.
  • Significant data gaps were identified across multiple KCs, limiting current comprehensive assessment.
  • The current landscape of in silico models for carcinogenicity assessment is detailed.

Conclusions:

  • Further development and validation of in silico models are required for regulatory acceptance.
  • Addressing identified data gaps is essential for creating a comprehensive in silico carcinogenicity protocol.
  • Improved human-relevant in silico models will support more efficient and ethical toxicological assessments.