OpenChemFacts model

OpenChemFacts models are developed in Python using Jupyter Notebooks.

The OpenChemFacts modeling approach is designed to calculate the Effect Factor (EF) of chemicals based on reliable experimental test results.

Step 1 = Database aggregation

Two databases are used in v.0.2.0 :

• REACH

  • extract from May 2023

  • 536,357 test results available)

• DSSTOX _ US EPA

  • extract from Decembre 2025

  • 694,662 test results available

Initial test results = 1,231,019 values

Step 2 = Datapipeline

Several filtering steps are implemented to filter results on reliable data to derive EC10eq values and calculate Effect Factors :

• filter on relevant species

• filter on relevant endpoints

• filter on tests with metada (e.g. date of the test, etc.)

To be completed