XGBoost Based Prediction of Drug Solubility in Cosolvent Systems
Published: 23 July 2025| Version 1 | DOI: 10.17632/r4c3v43xgn.1
Contributors:
, , Description
This notebook explores the use of Extreme Gradient Boosting (XGBoost) for predicting drug solubility in cosolvent systems. It demonstrates the model's ability to capture complex feature interactions.
Files
Steps to reproduce
The dataset DatasetSolubilityDrugV1, used for training the neural network, is available at the following link: https://data.mendeley.com/datasets/g686s23sy5/1. It should be cited as: Delgado, Daniel Ricardo; Vergara, Mateo; Cardenas Torres, Rossember Edén (2025), “Database of drug solubility in cosolvent mixtures at different temperatures.”, Mendeley Data, V1, https://doi.org/10.17632/g686s23sy5.1
Institutions
- Universidad de America
- Universidad Cooperativa de Colombia
Categories
Chemistry, Data Science, Machine Learning, Applied Computer Science