S2DV HepG2 toxicity

The model uses Word2Vec, a natural language processing technique to represent SMILES strings. The model was trained on over <2000 small molecules with associated experimental HepG2 cytotoxicity data (IC50) to classify compounds as HepG2 toxic (IC50 <= 30 uM) or non-toxic. Data was gathered from the public repository ChEMBL.

Identifiers

• EOS model ID: eos2fy6
• Slug: s2dv-hepg2-toxicity

Characteristics

• Input: Compound
• Input Shape: Single
• Task: Classification
• Output: Experimental value
• Output Type: Float
• Output Shape: Single
• Interpretation: Probability of HepG2 Toxicity (IC50 < 30 uM)

References

• Publication
• Source Code
• Ersilia contributor: emmakodes

Ersilia model URLs

• GitHub
• AWS S3
• DockerHub (AMD64, ARM64)

Citation

If you use this model, please cite the original authors of the model and the Ersilia Model Hub.

License

This package is licensed under a GPL-3.0 license. The model contained within this package is licensed under a Apache-2.0 license.

Notice: Ersilia grants access to these models 'as is' provided by the original authors, please refer to the original code repository and/or publication if you use the model in your research.

About Us

The Ersilia Open Source Initiative is a Non Profit Organization (1192266) with the mission is to equip labs, universities and clinics in LMIC with AI/ML tools for infectious disease research.

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