By leveraging molecular features and descriptors, the application assists researchers in identifying promising compounds, accelerating the development of effective treatments for breast cancer.

✔️ Accelerating Progress through Machine Learning ✔️ Machine learning-driven application predicts pIC50 values of chemical compounds. ✔️ Identification of potential drug candidates for breast cancer. ✔️ Analysis of compound structures and their relationships with biological activities. ✔️ Valuable insights into the efficacy of drug candidates. ✔️ Accelerates the identification and development of promising compounds. ✔️ Significant contribution to the battle against breast cancer. ✔️ Potential to transform patient outcomes and bring new hope for the future.

See owner's GitHub Repo for more info: https://github.com/getdaniel/bc-drug

See owner's GitHub Repo for more info: https://github.com/getdaniel/bc-drug

This application was not uploaded by the author, but through their publicly available Github repository (https://github.com/getdaniel/bc-drug).

MIT License

Copyright (c) 2023 Daniel G. Endalamaw S.