sairamkrish / drug-release-analysis

Drug release analysis based on different statistical metrics

drug-release-analysis

Drug release analysis based on different statistical metrics. This app is deployed to Streamlit cloud - https://drug-release.streamlit.app/.

Community guidelines

Feel free to clone this repo and use it for your own analysis. If you like to contribute, please raise a PR. If you have a feature request, please raise an issue with more details.

Pre-requisites

• Docker

Getting started - running with docker

# build and run the docker container
docker compose up --build

# Build docker image
# docker build \
#   -t drug-release-analysis:local .
# docker run -p 8501:8501 drug-release-analysis:local

Git commands

# To revert all local changes
git restore .
# To get code changes from remote
git pull --rebase

# To push code changes to remote
git add .
git commit -m "commit message"
git push origin main

Advanced usage - running python from local

This is not required. Optional if you want to run the app locally using python & not docker.

• Python version - v3.12+
• pyenv - Simple Python version management
  • Only needed if you have multiple versions of python and want to have a better developer experience.
• Poetry - For python dependency management

First time setup

pyenv update # if --list doesn't have updated python versions
pyenv install --list # list available versions that can be installed
pyenv install 3.12.3 # only needed for installing this python
pyenv local 3.12.3  # Activate Python

Development flow

eval "$(pyenv init --path)"
# install dependencies
poetry install
poetry shell
python -m streamlit run drug_release_analysis/streamlit_app.py

Todo

Capability

• Handling multiple groups
  • Add dropdown to select group
  • Show the selected group data in observation & observation scatter plots
• Cumulative Release
  • Scatter Plot
    • Need to check correctness for multiple groups with valid data
    • Time in hours on x-axis
    • percentage cumulative release on y-axis
    • Add trendline
    • Show equation
    • Show R^2
• Fractional values - is it wrong in the calculated data ? Validate this.
• Higuchi plot
  • Don't focus on this, till the correctness of till now calculations are validated

References

• trendline calculation - https://plotly.com/python/linear-fits/