Combination of machine learning and COSMO-RS thermodynamic model in predicting solubility parameters of coformers in production of cocrystals for enhanced drug solubility-Reference-Cited by-同舟云学术

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Combination of machine learning and COSMO-RS thermodynamic model in predicting solubility parameters of coformers in production of cocrystals for enhanced drug solubility

Published:2024-10 Issue: Volume:253 Page:105219
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Mahdi Wael A.,Obaidullah Ahmad J.

Funder

King Saud University

Publisher

Elsevier BV

Reference33 articles.

1. Overview of nanoparticulate strategies for solubility enhancement of poorly soluble drugs;Khan;Life Sci.,2022

2. Bioavailability enhancement techniques for poorly aqueous soluble drugs and therapeutics;Bhalani;Biomedicines,2022

3. Poly(vinylpyridine-co-vinylpyridine N-oxide) excipients mediate rapid dissolution and sustained supersaturation of posaconazole amorphous solid dispersions;Liu;Mol. Pharm.,2024

4. Amorphous solid dispersion of a binary formulation with felodipine and HPMC for 3D printed floating tablets;Mora-Castaño;Int. J. Pharm.,2024

5. Co-release of paclitaxel and encequidar from amorphous solid dispersions increase oral paclitaxel bioavailability in rats;Petersen;Int. J. Pharm.,2024

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