K-Nearest Neighbors Approach for Predicting Drug Solubility in Cosolvent Mixtures
Published: 23 July 2025| Version 1 | DOI: 10.17632/8cmgv5v2js.1
Contributors:
, , Description
This notebook develops a KNN model to predict drug solubility based on its physicochemical properties and system conditions. The process includes data loading and cleaning, hyperparameter optimization of k, and performance evaluation of the final model.
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
Computer Science, Chemistry, Data Science, Machine Learning, Applied Computer Science