Artificial Neural Network Modeling of Drug Solubility in Cosolvent Systems

Published: 23 July 2025| Version 1 | DOI: 10.17632/3ztcsxvjyb.1
Contributors:
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Description

This notebook implements an artificial neural network (ANN) to predict drug solubility in cosolvent systems. It includes data preprocessing, model architecture definition, training, and performance evaluation using regression metrics. The goal is to explore the non-linear relationships between solubility and experimental variables such as temperature and cosolvent composition.

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, Artificial Neural Network, Data Science, Machine Learning, Applied Computer Science

Licence