PMID- 35889230
OWN - NLM
STAT- MEDLINE
DCOM- 20220728
LR  - 20230710
IS  - 1420-3049 (Electronic)
IS  - 1420-3049 (Linking)
VI  - 27
IP  - 14
DP  - 2022 Jul 7
TI  - Solubility Optimization of Loxoprofen as a Nonsteroidal Anti-Inflammatory Drug: 
      Statistical Modeling and Optimization.
LID - 10.3390/molecules27144357 [doi]
LID - 4357
AB  - Industrial-based application of supercritical CO(2) (SCCO(2)) has emerged as a 
      promising technology in numerous scientific fields due to offering brilliant 
      advantages, such as simplicity of application, eco-friendliness, and high 
      performance. Loxoprofen sodium (chemical formula C(15)H(18)O(3)) is known as an 
      efficient nonsteroidal anti-inflammatory drug (NSAID), which has been long 
      propounded as an effective alleviator for various painful disorders like 
      musculoskeletal conditions. Although experimental research plays an important 
      role in obtaining drug solubility in SCCO(2), the emergence of operational 
      disadvantages such as high cost and long-time process duration has motivated the 
      researchers to develop mathematical models based on artificial intelligence (AI) 
      to predict this important parameter. Three distinct models have been used on the 
      data in this work, all of which were based on decision trees: K-nearest neighbors 
      (KNN), NU support vector machine (NU-SVR), and Gaussian process regression (GPR). 
      The data set has two input characteristics, P (pressure) and T (temperature), and 
      a single output, Y = solubility. After implementing and fine-tuning to the 
      hyperparameters of these ensemble models, their performance has been evaluated 
      using a variety of measures. The R-squared scores of all three models are greater 
      than 0.9, however, the RMSE error rates are 1.879 x 10(-4), 7.814 x 10(-5), and 
      1.664 x 10(-4) for the KNN, NU-SVR, and GPR models, respectively. MAE metrics of 
      1.116 x 10(-4), 6.197 x 10(-5), and 8.777 x 10(-5)errors were also discovered for 
      the KNN, NU-SVR, and GPR models, respectively. A study was also carried out to 
      determine the best quantity of solubility, which can be referred to as the (x(1) 
      = 40.0, x(2) = 338.0, Y = 1.27 x 10(-3)) vector.
FAU - Alqarni, Mohammed
AU  - Alqarni M
AUID- ORCID: 0000-0002-9028-2288
AD  - Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, 
      Taif 21944, Saudi Arabia.
FAU - Namazi, Nader Ibrahim
AU  - Namazi NI
AD  - Pharmaceutics and Pharmaceutical Technology Department, College of Pharmacy, 
      Taibah University, Al Madinah Al Munawarah 30001, Saudi Arabia.
FAU - Alshehri, Sameer
AU  - Alshehri S
AUID- ORCID: 0000-0003-2119-867X
AD  - Department of Pharmaceutics and Industrial Pharmacy, College of Pharmacy, Taif 
      University, Taif 21944, Saudi Arabia.
FAU - Naguib, Ibrahim A
AU  - Naguib IA
AUID- ORCID: 0000-0002-5923-1466
AD  - Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, 
      Taif 21944, Saudi Arabia.
FAU - Alsubaiyel, Amal M
AU  - Alsubaiyel AM
AD  - Department of Pharmaceutics, College of Pharmacy, Qassim University, Buraidah 
      52571, Saudi Arabia.
FAU - Venkatesan, Kumar
AU  - Venkatesan K
AUID- ORCID: 0000-0001-5077-9380
AD  - Department of Pharmaceutical Chemistry, College of Pharmacy, King Khalid 
      University, Abha 62529, Saudi Arabia.
FAU - Elmokadem, Eman Mohamed
AU  - Elmokadem EM
AD  - Department of Pharmacy Practice and Clinical Pharmacy, Faculty Pharmacy, Future 
      University in Egypt, New Cario 11835, Egypt.
FAU - Pishnamazi, Mahboubeh
AU  - Pishnamazi M
AD  - Institute of Research and Development, Duy Tan University, Da Nang 550000, 
      Vietnam.
AD  - The Faculty of Pharmacy, Duy Tan University, Da Nang 550000, Vietnam.
FAU - Abourehab, Mohammed A S
AU  - Abourehab MAS
AUID- ORCID: 0000-0003-1348-6567
AD  - Department of Pharmaceutics, Faculty of Pharmacy, Umm Al-Qura University, Makkah 
      21955, Saudi Arabia.
AD  - Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Minia 
      University, Minia 61519, Egypt.
LA  - eng
PT  - Journal Article
DEP - 20220707
PL  - Switzerland
TA  - Molecules
JT  - Molecules (Basel, Switzerland)
JID - 100964009
RN  - 0 (Anti-Inflammatory Agents)
RN  - 0 (Anti-Inflammatory Agents, Non-Steroidal)
RN  - 0 (Phenylpropionates)
RN  - 3583H0GZAP (loxoprofen)
SB  - IM
MH  - Anti-Inflammatory Agents
MH  - *Anti-Inflammatory Agents, Non-Steroidal/pharmacology
MH  - *Artificial Intelligence
MH  - Phenylpropionates
MH  - Solubility
PMC - PMC9321224
OTO - NOTNLM
OT  - loxoprofen
OT  - machine learning
OT  - optimization
OT  - solubility
OT  - supercritical fluids
COIS- The authors declare no conflict of interest.
EDAT- 2022/07/28 06:00
MHDA- 2022/07/29 06:00
PMCR- 2022/07/07
CRDT- 2022/07/27 01:33
PHST- 2022/05/19 00:00 [received]
PHST- 2022/06/22 00:00 [revised]
PHST- 2022/06/30 00:00 [accepted]
PHST- 2022/07/27 01:33 [entrez]
PHST- 2022/07/28 06:00 [pubmed]
PHST- 2022/07/29 06:00 [medline]
PHST- 2022/07/07 00:00 [pmc-release]
AID - molecules27144357 [pii]
AID - molecules-27-04357 [pii]
AID - 10.3390/molecules27144357 [doi]
PST - epublish
SO  - Molecules. 2022 Jul 7;27(14):4357. doi: 10.3390/molecules27144357.