Ersilia Model Hub Identifier: eos6fza
5.9K
Using the Molecule Net dataset ClinTox, the authors trained a classification model to predict the likelihood of failure in clinical trials due to toxicity. The dataset has been built using FDA approved drugs (non-toxic) and a set of drugs that have failed at advanced clinical trial stages. This model has been trained using the GROVER transformer (see eos7w6n or grover-embedding for a detail of the molecular featurization step with GROVER).
This model was incorporated on 2022-07-13.Last packaged on 2026-05-20.
eos6fzagrover-clintoxAnnotationActivity predictionADMETHomo sapiensToxicity, Chemical graph model, Side effectsCompound12FixedBelow are the Output Columns of the model:
| Name | Type | Direction | Description |
|---|---|---|---|
| fda_approved | float | high | Probability that the drug is FDA approved |
| ct_tox | float | high | Probability that the drug has clinical toxicity |
LocalExternalAMD64, ARM64131025476502.53Computational Performance (seconds):
29.8252.06-1Preprint2020This package is licensed under a GPL-3.0 license. The model contained within this package is licensed under a MIT license.
Notice: Ersilia grants access to models as is, directly from the original authors, please refer to the original code repository and/or publication if you use the model in your research.
To use this model locally, you need to have the Ersilia CLI installed. The model can be fetched using the following command:
# fetch model from the Ersilia Model Hub
ersilia fetch eos6fza
Then, you can serve, run and close the model as follows:
# serve the model
ersilia serve eos6fza
# generate an example file
ersilia example -n 3 -f my_input.csv
# run the model
ersilia run -i my_input.csv -o my_output.csv
# close the model
ersilia close
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Content type
Image
Digest
sha256:16e3d23b2…
Size
4.6 GB
Last updated
6 months ago
docker pull ersiliaos/eos6fzaPulls:
11
Oct 19 to Oct 25