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Background: The development of innovative approaches in drug analysis is a challenging task for medicine, pharmacy, and engineering sciences. For instance, the requirement of proper dosage forms in releasing active ingredients is crucial. It is essential to analyze drugs in biological liquids for early diagnosis and treatment purposes. Drug analysis is also of great importance to control the quality of pharmaceutical products, test their efficacy, and develop novel drug formulation. The present review is aimed to highlight the most recent spectrophotometric approaches applied to analyze various classes of drugs in biological media and/or dosage forms. Methods: Direct and derivative UV/UV-Vis spectrophotometry and a combination of various techniques with spectrophotometry, such as injection analysis and chemometrics, have most widely been applied in the analysis of dosage forms. In addition, emerging technologies, such as UV imaging allows to obtain the distribution of drug concentration in time-resolved 2D images based on UV light absorption, utilization of nanotechnology, self-assembled nanomaterials, and aptamer-based nanoparticles have gained interests to investigate drug assays and to quantify the proper drug release. Results: Due to their high versatility, ease of application, low cost, and fast response, spectrophotometric methods are one of the most preferable methods providing high accuracy and precision with a wide linear range in drug analysis. Conclusion: Selected examples demonstrating the applicability of spectrophotometric methods in pharmaceutical assays in this review might contribute to the overall importance of the analytical test used in modern pharmaceutical analysis.

Background: The number of validated quantification methods for rifampicin, a prototypical Oatp inhibitor, in biological rat samples was limited. Objective: This study was conducted to validate a modified reversed-phase liquid chromatographic method for the determination of rifampicin in rat liver tissue according to the current ICH M10 Bioanalytical Method Validation Draft Guideline (2019) for application to samples of in situ rat liver perfusion studies. Methods: Liver tissue samples were obtained from recirculatory in situ rat liver perfusion studies. The analysis was performed on a C18 column with a mobile phase composed of 0.05 M phosphate buffer (pH 4.58): acetonitrile (55:45, v/v). The assay was validated for selectivity, calibration curve and range, matrix effect, carry-over, accuracy and precision, reinjection reproducibility, and stability. Results: he method was considered selective and stable, without having carry-over and matrix effects. The calibration curve was linear (R2: 0.9983) within the calibration range (0.5-60 ppm). Accuracy and precision values fulfilled the required limits. Liver concentrations of rifampicin in liver tissue, obtained after 60 min perfusion with 10 μM and 50 μM of rifampicin, were 45.1 ± 11.2 and 313.4 ± 84.4 μM, respectively. Conclusion: The bioanalytical method validation was completed and the method was successfully applied for the determination of rifampicin in rat liver tissue.

Background: Metabolomics is one of the main areas to understand cellular process at molecular level by analyzing metabolites. In recent years metabolomics has emerged as a key tool to understand molecular basis of diseases, to find diagnostic and prognostic biomarkers and develop new treatment opportunities and drug molecules. Objective: In this study, untargeted metabolite and lipid analysis were performed to identify potential biomarkers on premature ovarian insufficiency plasma samples. 43 POI subject plasma samples were compared with 32 healthy subject plasma samples. Methods: Plasma samples were pooled and extracted using chloroform:methanol:water (3:3:1 v/v/v) mixture. Agilent 6530 LC/MS Q-TOF instrument equipped with ESI source was used for analysis. A C18 column (Agilent Zorbax 1.8 μM, 50 x 2.1 mm) was used for separation of the metabolites and lipids. XCMS, an “R software” based freeware program, was used for peak picking, grouping and comparing the findings. Isotopologue Parameter Optimization (IPO) software was used to optimize XCMS parameters. The analytical methodology and data mining process were validated according to the literature. Results: 83 metabolite peaks and 213 lipid peaks were found to be in semi-quantitatively and statistically different (fold change >1.5, p Conclusion: According to the results, two groups were successfully separated through principal component analysis. Among the peaks, phenyl alanine, decanoyl-L-carnitine, 1-palmitoyl lysophosphatidylcholine and PC(O-16:0/2:0) were identified through auto MS/MS and matched with human metabolome database and proposed as plasma biomarker for POI and monitoring the patients in treatment period.