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Pharmageddon

1. Install Dependencies: pip install poetry

2. Download data and models here: https://drive.google.com/file/d/1hinxrf1u1hMRsR6_g1fP84wumLJKvKce/view?usp=sharing
   The folder structure should look like this:

├── data <-- You added this from the google drive link
│   └── ...
├── design
│   └── ...
├── src
│   └── ...
├── Dockerfile
...
└── README.me

1. Run make venv to create virtual environment

2. Activate venv source .venv/bin/activate

3. Install Torch Geometric pip install torch-geometric==2.3.1\

4. Run Streamlit: streamlit run src/webapp.py\

5. (Optional) To train the model using your own polypharmacy datasets rn:

   pharmageddon train --train <path to training set> --test <path to test set> --out <path to output directory> [--config <path to config file> --checkpoint <path to trained model>]

6. (Optional) Use the trained model to predict side effects for your chemical compound of interest. The --checkpoint parameter can be omitted - the default model will then be used. --effects can also be omitted, probabilities for all available effects are predicted then.

   pharmageddon predict --graph <path to polypharmacy graph> --drugs <drug1> <drug2>  [--checkpoint <path_to_model> --effects <effect1> <effect2>]

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