دورية أكاديمية
أعرض في EDS

Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen.

التفاصيل البيبلوغرافية
العنوان: Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen.
المؤلفون: Cysewski P; Department of Physical Chemistry, Pharmacy Faculty, Collegium Medicum of Bydgoszcz, Nicolaus Copernicus University in Toruń, Kurpińskiego 5, 85-096 Bydgoszcz, Poland., Jeliński T; Department of Physical Chemistry, Pharmacy Faculty, Collegium Medicum of Bydgoszcz, Nicolaus Copernicus University in Toruń, Kurpińskiego 5, 85-096 Bydgoszcz, Poland., Przybyłek M; Department of Physical Chemistry, Pharmacy Faculty, Collegium Medicum of Bydgoszcz, Nicolaus Copernicus University in Toruń, Kurpińskiego 5, 85-096 Bydgoszcz, Poland., Mai A; Department of Physical Chemistry, Pharmacy Faculty, Collegium Medicum of Bydgoszcz, Nicolaus Copernicus University in Toruń, Kurpińskiego 5, 85-096 Bydgoszcz, Poland., Kułak J; Department of Physical Chemistry, Pharmacy Faculty, Collegium Medicum of Bydgoszcz, Nicolaus Copernicus University in Toruń, Kurpińskiego 5, 85-096 Bydgoszcz, Poland.
المصدر: Molecules (Basel, Switzerland) [Molecules] 2024 May 14; Vol. 29 (10). Date of Electronic Publication: 2024 May 14.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Country of Publication: Switzerland NLM ID: 100964009 Publication Model: Electronic Cited Medium: Internet ISSN: 1420-3049 (Electronic) Linking ISSN: 14203049 NLM ISO Abbreviation: Molecules Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Basel, Switzerland : MDPI, c1995-
مواضيع طبية MeSH: Ketoprofen*/chemistry , Ibuprofen*/chemistry , Solubility* , Machine Learning* , Deep Eutectic Solvents*/chemistry, Cyclooxygenase Inhibitors/chemistry ; Hydrogen Bonding ; Solvents/chemistry
مستخلص: Deep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental solubility data were collected for all DES systems. A machine learning model was developed using COSMO-RS molecular descriptors to predict solubility. All studied DESs exhibited a cosolvency effect, increasing drug solubility at modest concentrations of water. The model accurately predicted solubility for ibuprofen, ketoprofen, and related analogs (flurbiprofen, felbinac, phenylacetic acid, diphenylacetic acid). A machine learning approach utilizing COSMO-RS descriptors enables the rational design and solubility prediction of DES formulations for improved pharmaceutical applications.
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فهرسة مساهمة: Keywords: COSMO-RS; deep eutectic solvents; ibuprofen; ketoprofen; machine learning; non-selective COX inhibitors; solubility
المشرفين على المادة: 90Y4QC304K (Ketoprofen)
WK2XYI10QM (Ibuprofen)
0 (Deep Eutectic Solvents)
0 (Cyclooxygenase Inhibitors)
0 (Solvents)
تواريخ الأحداث: Date Created: 20240525 Date Completed: 20240525 Latest Revision: 20240527
رمز التحديث: 20240527
مُعرف محوري في PubMed: PMC11124057
DOI: 10.3390/molecules29102296
PMID: 38792157
قاعدة البيانات: MEDLINE
الوصف
تدمد:1420-3049
DOI:10.3390/molecules29102296