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High-throughput screening data generation, scoring and FAIRification: a case study on nanomaterials.

Gergana Tancheva1,2, Vesa Hongisto3, Konrad Patyra3

  • 1Ideaconsult Ltd., 4 Angel Kanchev Str, 1000, Sofia, Bulgaria. gerganatancheva1@gmail.com.

Journal of Cheminformatics
|April 24, 2025
PubMed
Summary
This summary is machine-generated.

A new high-throughput screening (HTS) protocol, Tox5-score, standardizes in vitro toxicity testing for rapid hazard assessment of diverse agents, including nanomaterials (NMs). This FAIR-compliant computational tool automates data processing and analysis, enhancing safety evaluations.

Keywords:
Automatic workflowFAIRHTSNAMsNanomaterialsNanomaterials groupingToxPieNanoMapper

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Area of Science:

  • Toxicology and computational chemistry
  • Nanomaterial safety assessment
  • Data science in chemical hazard evaluation

Background:

  • High-throughput screening (HTS) offers a powerful approach for hazard-based ranking and grouping of various agents, including nanomaterials (NMs).
  • Standardized protocols are crucial for consistent and reliable in vitro toxicity data generation and interpretation.
  • Existing data processing methods for HTS can be manual and time-consuming, hindering rapid assessment.

Purpose of the Study:

  • To develop and present a standardized, automated HTS-derived protocol for toxic mode-of-action-based hazard assessment.
  • To introduce the Tox5-score, a comprehensive hazard value integrating data from five assays.
  • To facilitate FAIR data handling and integration for HTS-derived toxicity data.

Main Methods:

  • Development of a human cell-based HTS protocol combining five toxicological assays.
  • Implementation of automated data FAIRification, preprocessing, and score calculation.
  • Creation of a Python module (ToxFAIRy) and an Orange Data Mining add-on (Orange3-ToxFAIRy) for workflow management.
  • Conversion of FAIR HTS data into the NeXus format for integrated data and metadata handling.

Main Results:

  • A standardized HTS protocol yielding a broad toxic mode-of-action-based hazard value (Tox5-score).
  • Automated data FAIRification, preprocessing, and score calculation capabilities.
  • A computational tool (ToxFAIRy and Orange3-ToxFAIRy) for efficient HTS data analysis and visualization.
  • Facilitated conversion of HTS data into the NeXus format, enabling data integration and sharing.

Conclusions:

  • The developed HTS-driven computational tool enables rapid, simultaneous hazard analysis of multiple agents.
  • The protocol enhances the applicability of HTS-derived data in materials development and safety assessment.
  • This approach offers an alternative to manual data processing, improving efficiency and data enrichment for toxicity testing and mode-of-action research.