Computational intelligence analysis on drug solubility using thermodynamics and interaction mechanism via models comparison and validation
Abstract This study investigates the application of various regression models for predicting drug solubility in polymer and API-polymer interactions in complex datasets. Four models—Gaussian Process Regression (GPR), Support Vector Regression (SVR), Bayesian Ridge Regression (BRR), and Kernel Ridge...
Saved in:
| Main Authors: | Ahmad J. Obaidullah, Wael A. Mahdi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-80952-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Estimation and validation of solubility of recombinant protein in E. coli strains via various advanced machine learning models
by: Wael A. Mahdi, et al.
Published: (2025-04-01) -
Computational intelligence investigations on evaluation of salicylic acid solubility in various solvents at different temperatures
by: Adel Alhowyan, et al.
Published: (2025-02-01) -
Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique
by: Lijie Jiang, et al.
Published: (2025-06-01) -
Machine learning-based analysis on pharmaceutical compounds interaction with polymer to estimate drug solubility in formulations
by: Ahmad J. Obaidullah, et al.
Published: (2025-07-01) -
Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models
by: Wael A. Mahdi, et al.
Published: (2025-06-01)