ersiliaos/eos77w8 repository overview

⁠Adverse Drug Reactions

Anticipates which adverse reactions a marketed drug may provoke, grouped into 27 system organ classes. SIDER, distributed through MoleculeNet, links 1,427 approved drugs to the side effects recorded on their labels, and those associations form the training signal. A self-supervised graph transformer pretrained on 10 million molecules was fine-tuned across all classes at once, averaging three fine-tuned folds. Label text comes from package inserts rather than controlled trials, so the relationships captured are associative and reflect reporting practice as much as pharmacology.

This model was incorporated on 2021-05-12. Last packaged on 2026-11-03.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos77w8
• Slug: grover-sider

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: ADMET
• Target Organism: Homo sapiens
• Tags: Toxicity, Side effects

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 27
• Output Consistency: Fixed
• Interpretation: Probability of causing an adverse reaction in each of 27 organ system classes.

Below are the Output Columns of the model:

10 of 27 columns are shown

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://chstno1.isgood.host/r/ersiliaos/eos77w8⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos77w8.zip⁠

⁠Resource Consumption

• Model Size (Mb): 1323
• Environment Size (Mb): 2406
• Image Size (Mb): 3699.06

Computational Performance (seconds):

• 10 inputs: 31.42
• 100 inputs: 157.55
• 10000 inputs: -1

⁠References

• Source Code: https://github.com/tencent-ailab/grover⁠
• Publication: https://doi.org/10.48550/arXiv.2007.02835⁠
• Publication Type: Preprint
• Publication Year: 2020
• Ersilia Contributor: Amna-28⁠

⁠License

This 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.

⁠Use

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 eos77w8

Then, you can serve, run and close the model as follows:

# serve the model
ersilia serve eos77w8
# 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

⁠About Ersilia

The Ersilia Open Source Initiative⁠ is a tech non-profit organization fueling sustainable research in the Global South. Please cite⁠ the Ersilia Model Hub if you've found this model to be useful. Always let us know⁠ if you experience any issues while trying to run it. If you want to contribute to our mission, consider donating⁠ to Ersilia!