The objective of this present investigation was to develop and formulate sustained release (SR) matrix tablets of Itopride HCl, by using different polymer combinations and fillers, to optimize by Central Composite Design response surface methodology for different drug release variables and to evaluate drug release pattern of the optimized product. Sustained release matrix tablets of various combinations were prepared with cellulose-based polymers: hydroxy propyl methyl cellulose (HPMC) and polyvinyl pyrolidine (pvp) and lactose as fillers. Study of pre-compression and post-compression parameters facilitated the screening of a formulation with best characteristics that underwent here optimization study by response surface methodology (Central Composite Design). The optimized tablet was further subjected to scanning electron microscopy to reveal its release pattern. The in vitro study revealed that combining of HPMC K100M (24.65 MG) with pvp(20 mg)and use of LACTOSE as filler sustained the action more than 12 h. The developed sustained release matrix tablet of improved efficacy can perform therapeutically better than a conventional tablet.

Objective: Metformin hydrochloride and sitagliptin are the oral anti-hyperglycemic medications used to treat type 2 diabetes and are used in combination to treat patients. In this work, we have developed a bioanalytical method for simultaneous estimation of both the drugs form some formulation and subsequently the validation of the developed method metformin and sitagliptin in human plasma. Methods: The stability studies were done as per USFDA and EMA guidelines. The sample extraction approach presented here was a straightforward liquid extraction. The linearity range of metformin was 11.72 ng/ml to 3000 ng/ml, and sitagliptin was 4.68 ng/ml. to 1200 ng/ml. For metformin, the LOD was 1.0 ng/ml, and LLOQ was 11.72 ng/ml. and for sitagliptin, the LOD was 0.75 ng/ml, and LLOQ was 4.68 ng/ml. LC-ESI-MS/MS was used to develop and validate this method using the Phenomenex Kinetex C18 column. Milli-Q water containing 10 mmol Ammonium Acetate (pH =3.6) and Acetonitrile containing 0.1% Formic Acid (pH =2.4) as solvent systems for the estimation of Sitagliptin in a single dose. Metoprolol is used as an Internal Standard. Results: The total chromatographic run time was only 7.0 min, and the elute time of metformin and sitagliptin was 3.94 min and 3.97 min, respectively. Relative Bioavailability was found at 101.14% for Metformin and 96.96% for Sitagliptin. The overall results show that the Cmax, AUC0-t, and AUC0-∞ for metformin and sitagliptin were within the acceptable limit of 80%-125%. Conclusion: This bioanalytical method was successfully applied in the bioequivalence study. The study design was a randomized, open-label, two treatment, two-period, two sequences, single-dose, crossover bioequivalence study under fasting conditions.

: Cystic Fibrosis (CF) is a fatal hereditary condition marked by thicker mucus production, which can cause problems with the digestive and respiratory systems. The quality of life and survival rates of CF patients can be improved by early identification and individualized therapy measures. With an emphasis on its applications in diagnosis and therapy, this paper investigates how Artificial Intelligence (AI) is transforming the management of Cystic Fibrosis (CF). AI-powered algorithms are revolutionizing CF diagnosis by utilizing huge genetic, clinical, and imaging data databases. In order to identify CF mutations quickly and precisely, machine learning methods evaluate genomic profiles. Furthermore, AI-driven imaging analysis helps to identify lung and gastrointestinal issues linked to cystic fibrosis early and allows for prompt treatment. Additionally, AI aids in individualized CF therapy by anticipating how patients will react to already available medications and enabling customized treatment regimens. Drug repurposing algorithms find prospective candidates from already-approved drugs, advancing treatment choices. Additionally, AI supports the optimization of pharmacological combinations, enhancing therapeutic results while minimizing side effects. AI also helps with patient stratification by connecting people with CF mutations to therapies that are best for their genetic profiles. Improved treatment effectiveness is promised by this tailored strategy. The transformational potential of artificial intelligence (AI) in the field of cystic fibrosis is highlighted in this review, from early identification to individualized medication, bringing hope for better patient outcomes, and eventually prolonging the lives of people with this difficult ailment.

Background: Mesoporous silica-loaded docetaxel trihydrate nanoparticles are the potential to target drug delivery toward a specific region with high stability and predictable release at the target region. They have large surface areas and mesoporous structures with large pore volumes, leading to high bioavailability and therapeutic efficacy at the disease site. This study demonstrates how nanoparticles can be prepared using an emulsion technique. Results: The ratios of eudragit S100 to eudragit L100 polymers, along with phosphatidylcholine, were varied according to the response surface methodology. Differential scanning colorimetry and fluorinated transmitted infrared spectroscopy studies showed that mesoporous silica particles were successful. All formulations had average particle sizes ranging from 70.65 to 143.01 nm, with a range of zeta potential from 17.6 ± 026 to 21 ± 011. In vitro drug delivery studies were achieved for all formulations with a zeta potential of 17.6 ± 026 to 21 ± 011. As per the statistical optimization by RSM that response model for percentage drug loading (Y₁) was found to be 0.0002 which is p-value < 0.05. Hence, the model is significance. Accordingly percentage drug release at 6 h. (Y₂) p-value was found to be 0.0001 and percentage drug release at 10 h (Y₃) p-value was found to be 0.0002, respectively. So all the models are significant. After oral administration of the docetaxel, plasma levels were measured in vivo bioavailability testing of docetaxel. Docetaxel nanosuspension had a significantly higher C_max amount than docetaxel microsuspension (98.03 ± 23.40 ng/ml and 213.67 ± 72.21 ng/ml, respectively, with t_max 45 min). Docetaxel was more bioavailable in nanosuspension formulations, according to a bioavailability test of rats. Conclusion: The results suggested that the mesoporous silica could be a great potential nanocarrier in colonic delivery with optimal drug content and controlled release docetaxel trihydrate.