Computational simulation and target prediction studies of solubility optimization of decitabine through supercritical solvent.

Autor: Alshahrani SM; Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj, 11942, Saudi Arabia. Sm.Alshahrani@psau.edu.sa., Almutairy BK; Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj, 11942, Saudi Arabia., Alfadhel MM; Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj, 11942, Saudi Arabia., Belal A; Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, Taif, 21944, Saudi Arabia. a.belal@tu.edu.sa.; Medicinal Chemistry Department, Faculty of Pharmacy, Beni-Suef University, Beni-Suef, 62514, Egypt. a.belal@tu.edu.sa., Abourehab MAS; Department of Pharmaceutics, College of Pharmacy, Umm Al-Qura University, Makkah, 21955, Saudi Arabia.; Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Minia University, Minia, 61519, Egypt., Saqr AA; Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj, 11942, Saudi Arabia., Alshetaili AS; Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj, 11942, Saudi Arabia., Venkatesan K; Department of Pharmaceutical Chemistry, College of Pharmacy, King Khalid University, Abha, 62529, Kingdom of Saudi Arabia., Alsubaiyel AM; Department of Pharmaceutics, College of Pharmacy, Qassim University, Buraidah, 52571, Saudi Arabia. asbiel@qu.edu.sa., Pishnamazi M; Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam. pishnamazi.m@gmail.com.; The Faculty of Pharmacy, Duy Tan University, Da Nang, 550000, Vietnam. pishnamazi.m@gmail.com.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2022 Nov 07; Vol. 12 (1), pp. 18875. Date of Electronic Publication: 2022 Nov 07.
DOI: 10.1038/s41598-022-21233-0
Abstrakt: Computational analysis of drug solubility was carried out using machine learning approach. The solubility of Decitabine as model drug in supercritical CO 2 was studied as function of pressure and temperature to assess the feasibility of that for production of nanomedicine to enhance the solubility. The data was collected for solubility optimization of Decitabine at the temperature 308-338 K, and pressure 120-400 bar used as the inputs to the machine learning models. A dataset of 32 data points and two inputs (P and T) have been applied to optimize the solubility. The only output is Y = solubility, which is Decitabine mole fraction solubility in the solvent. The developed models are three models including Kernel Ridge Regression (KRR), Decision tree Regression (DTR), and Gaussian process (GPR), which are used for the first time as a novel model. These models are optimized using their hyper-parameters tuning and then assessed using standard metrics, which shows R 2 -score, KRR, DTR, and GPR equal to 0.806, 0.891, and 0.998. Also, the MAE metric shows 1.08E-04, 7.40E-05, and 9.73E-06 error rates in the same order. The other metric is MAPE, in which the KRR error rate is 4.64E-01, DTR shows an error rate equal to 1.63E-01, and GPR as the best mode illustrates 5.06E-02. Finally, analysis using the best model (GPR) reveals that increasing both inputs results in an increase in the solubility of Decitabine. The optimal values are (P = 400, T = 3.38E + 02, Y = 1.07E-03).
(© 2022. The Author(s).)
Databáze: MEDLINE
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