Solubility Optimization of Loxoprofen as a Nonsteroidal Anti-Inflammatory Drug: Statistical Modeling and Optimization.

Industrial-based application of supercritical CO2 (SCCO2) 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 C15H18O3) 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 SCCO2, 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 × 10-4, 7.814 × 10-5, and 1.664 × 10-4 for the KNN, NU-SVR, and GPR models, respectively. MAE metrics of 1.116 × 10-4, 6.197 × 10-5, and 8.777 × 10-5errors 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 (x1 = 40.0, x2 = 338.0, Y = 1.27 × 10-3) vector.

The efficacy and safety of itopride in feeding intolerance of critically ill patients receiving enteral nutrition: a randomized, double-blind study.

BACKGROUND: Enteral feeding intolerance (EFI) is a frequent problem in the Intensive care unit (ICU) and is associated with poor clinical outcomes leading to worse prognosis in terms of mortality and ICU stay. Nowadays, prokinetic drugs are the mainstay of therapy in EFI. However, available prokinetics have uncertain efficacy and safety profiles. Itopride, is a prokinetic agent which is different and unique from the available prokinetics because of its dual mode of action as well as its tolerability and safety. The current study compared the efficacy and safety of Itopride against metoclopramide for EFI in critically ill patients. Moreover, it tested the utility and applicability of ultrasonography to measure gastric residual volume (GRV) in this population. METHODS: This randomized, double-blind study included 76 EFI patients who were randomly assigned to either Itopride or metoclopramide group. The primary outcome was to measure GRV by ultrasonography. Secondary outcomes included the percentage ratio of enteral feed volume, energy and protein received by patients over 7 days of treatment, ICU length of stay, safety parameters and occurrence of infectious complications or vomiting. RESULTS: Thirty-five patients of each group completed the study. At day 7, itopride significantly decreased GRV compared with metoclopramide group (p = 0.001). Moreover, there was a significant increase in the ratios of received enteral nutrition feed volume, calories, and protein after the one-week therapy in the itopride group more than the metoclopramide group (p = 0.001), (p = 0.002), (p = 0.01), respectively and there were no differences in any secondary outcomes or adverse events between the two groups. CONCLUSION: In critically ill patients with EFI, itopride was well tolerated with superior efficacy to metoclopramide. In addition, we demonstrated that ultrasonography is a simple, non-invasive, inexpensive, and undemanding method for GRV measurements and can offer reliable assessments in the gastric emptying modality. TRIAL REGISTRATION: The trial was registered in ClinicalTrials.gov (NCT03698292). Date: October 5, 2018.