A rapid, synchronized liquid chromatographic method was established for the estimation of hydrochlorothiazide (HCZ), amlodipine (AMD), olmesartan (OLM), telmisartan (TEL), and irbesartan (IRB) in binary and ternary coformulations using the same chromatographic conditions. Five analytes were separated on a Zorbax C18 column using isocratic elution with a mobile phase consisting of acetonitrile, methanol, and 20 mM phosphate buffer (pH 3.5) in a ratio of 45:20:35% v/v. The analytes were detected at a wavelength of 230 nm at ambient temperature. Furthermore, the proposed liquid chromatographic procedure was validated for linearity, precision, accuracy, stability, and robustness using an experimental design. Analytes were separated with good resolution within 3.5 min. Analytes showed good linearity in a concentration satisfactory to analyze the different ratios of these analytes in the formulations. Pareto charts showed that the flow rate and mobile phase composition have a significant effect on the peak area of analytes and hence need to be carefully controlled, however, the method is robust. Finally, the different formulations consisting of HCZ, AMD, OLM, TEL, and IRB in different ratios were analyzed with high accuracy using an optimized HPLC method and compared with reported methods. Furthermore, the reported HPLC procedure is simple, rapid, and accurate and therefore can used for regular quality control of binary and ternary formulations using the same stationary and mobile phase.

A rapid and reproducible hydrophilic liquid chromatography (HILIC) process was established for concomitant determination of remogliflozin etabonate (RE), vildagliptin (VD), and metformin (MF) in a formulation. A face-centered central composite experimental design was employed to optimize and predict the chromatographic condition by statistically studying the surface response model and design space with desirability close to one. A HILIC column with a simple mobile phase of acetonitrile (65% v/v) and 20 mM phosphate buffer (35% v/v, pH 6, controlled with orthophosphoric acid) was used to separate RE, VD, and MF. RE, VD, and MF were separated in 3.6 min using an isocratic mode mobile phase flow at a flow rate of 1.4 mL at room temperature, and the analytes were examined by recording the absorption at 210 nm. The developed HILIC method was thoroughly validated for all parameters recommended by ICH, and linearity was observed in the ranges 20–150 µg/mL, 10–75 µg/mL, and 50–750 µg/mL for RE, VD, and MF, respectively, along with excellent regression coefficients (r² > 0.999). The calculated percentage relative deviation and relative error ascertained the precision and accuracy of the method. The selectivity and accuracy were further confirmed by the high percentage recovery of added standard drugs to the formulation using the standard addition technique. The robustness of the HILIC processes was confirmed by developing a half-normal probability plot and Pareto chart, as the slight variation of a single factor had no significant influence on the assay outcomes. Utilization of the optimized HILIC procedure for concurrent quantification of RE, VD, and MF in solid dosage forms showed accurate and reproducible results. Hence, the fast HILIC method can be regularly employed for the quality assurance of pharmaceutical preparations comprising RE, VD, and MF.

Major obstacles faced by the use of nonsteroidal anti-inflammatory drugs (NSAID) are their gastrointestinal toxicity induced by non-selective inhibition of both cyclooxygenases (COX) 1 and 2 and their cardiotoxicity associated with a certain class of COX-2 selective inhibitors. Recent studies have demonstrated that selective COX-1 and COX-2 inhibition generates compounds with no gastric damage. The aim of the current study is to develop novel anti-inflammatory agents with a better gastric profile. In our previous paper, we investigated the anti-inflammatory activity of 4-methylthiazole-based thiazolidinones. Thus, based on these observations, herein we report the evaluation of anti-inflammatory activity, drug action, ulcerogenicity and cytotoxicity of a series of 5-adamantylthiadiazole-based thiazolidinone derivatives. The in vivo anti-inflammatory activity revealed that the compounds possessed moderate to excellent anti-inflammatory activity. Four compounds 3, 4, 10 and 11 showed highest potency (62.0, 66.7, 55.8 and 60.0%, respectively), which was higher than the control drug indomethacin (47.0%). To determine their possible mode of action, the enzymatic assay was conducted against COX-1, COX-2 and LOX. The biological results demonstrated that these compounds are effective COX-1 inhibitors. Thus, the IC₅₀ values of the three most active compounds 3, 4 and 14 as COX-1 inhibitors were 1.08, 1.12 and 9.62 μΜ, respectively, compared to ibuprofen (12.7 μΜ) and naproxen (40.10 μΜ) used as control drugs. Moreover, the ulcerogenic effect of the best compounds 3, 4 and 14 were evaluated and revealed that no gastric damage was observed. Furthermore, compounds were found to be nontoxic. A molecular modeling study provided molecular insight to rationalize the COX selectivity. In summary, we discovered a novel class of selective COX-1 inhibitors that could be effectively used as potential anti-inflammatory agents.

The development of an environmentally friendly analytical technique for simultaneous measurement of medicines with large concentration differences is difficult yet critical for environmental protection. Hence, in this work, new manipulated UV-spectroscopic methods with high scaling factors were established for concurrent quantification of telmisartan (TEL) and benidipine (BEN) in fixed-dose combinations. Two different methods were developed and established by calculation of peak height at zero crossing point of second derivative and the ratio of first derivative spectra with a scaling factor of 200 and 100, respectively. The absorption difference between the peaks and troughs of the ratio spectra, as well as continuous subtraction from ratio spectra, were established as additional methods. In addition, new procedures were validated using ICH recommendations. The proposed methods’ linearity curves were constructed in the range of 0.5–10 µg mL⁻¹ and 1–30 µg mL⁻¹ for BEN and TEL, respectively, under optimized conditions. Furthermore, both the detection (0.088–0.139 µg mL⁻¹ for BEN and 0.256–0.288 µg mL⁻¹ for TEL) and quantification limits (0.293–0.465 µg mL⁻¹ for BEN and 0.801–0.962 µg mL⁻¹ for TEL) were adequate for quantifying both analytes in the formulation ratios. The accuracy and precision were confirmed by the good recovery percent (98.37%–100.6%), with low percent relative error (0.67%–1.70%) and less than 2 percent relative standard deviation, respectively. The specificity of the methods was proven by accurate and precise outcomes from the standard addition method and analysis of laboratory mixed solutions with large differences in concentrations of both analytes. Finally, the BEN and TEL content of the formulations was determined simultaneously without prior separation using these first ever reported spectroscopic methods. Furthermore, developed UV derivative spectroscopic methods demonstrated high greenness and whiteness when compared to the reported HPLC methods. These findings show that the projected methods were effective, practical, and environmentally acceptable for quality control of BEN and TEL in multicomponent formulations.

Background: HIV-1 RT inhibitors were the first drugs approved to treat AIDS and remain key components of highly active antiretroviral therapy (HAART). While HAART effectively suppresses viral replication and slows disease progression, it has limitations, including long-term side effects and the emergence of drug-resistant strains, highlighting the need for new treatments. Objectives: Based on our previous experience, and insights from existing inhibitors of HIV-1 RT and RNase H, we aim to design and synthesize safer, multifunctional molecules. Methods: Using molecular docking studies, these compounds will incorporate pharmacophores targeting multiple stages of the HIV life cycle to enhance efficacy, reduce resistance, and improve pharmacokinetics. The compounds were synthesized via a one-pot three component reaction. The synthesized compounds were identified using spectroscopy and tested in vitro for activity against key HIV targets, including RNA-dependent DNA polymerase (RDDP) and RNAse H. Results: Among the synthesized compounds, several demonstrated strong inhibitory activity, with compound 11 showing IC₅₀ values comparable to the reference drug Nevirapine, and compound 4 exhibiting dual inhibition of both RT and RNase H activities. Conclusions: These findings emphasize the importance of a multidisciplinary approach, combining computational modeling with experimental validation, to identify promising leads for therapeutic development.

This paper evaluates various machine learning models for predicting vector-borne diseases, focusing on performance metrics that reveal insights into their efficacy. The Multilayer Perceptron (MLP) model demonstrated the highest accuracy at 92%, surpassing the Simple Logistic (SL) and Support Vector Machine (SVM) models, which achieved 88% and 90.87% accuracy, respectively. Notably, the MLP model excelled in precision, recall, and F-Measure, indicating superior classification accuracy. Conversely, the SVM model exhibited noteworthy computational efficiency with the lowest processing time at 0.3 seconds, emphasizing its potential for real-time applications in public health interventions. In contrast, the Radial Basis Function Network (RBFN) lagged in accuracy and other metrics. The results underscore the trade-offs between accuracy and computational efficiency, emphasizing the need for a nuanced model selection. Considering the holistic evaluation, the SVM model emerged as a compelling choice, balancing high accuracy and efficient processing, making it promising for real-time public health applications. This study contributes valuable insights into machine learning model performance, emphasizing the importance of selecting models tailored to the specific needs of vector-borne disease prediction. As we confront emerging infectious diseases, the SVM model stands as an indispensable tool, supporting a proactive and data-driven approach to mitigate the global health impact of vector- borne diseases.