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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, 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: As well as direct and derivative UV/UV–Vis spectrophotometry, combination of various techniques with spectrophotometry, such as injection analysis and chemometrics, has been most widely applied in the analysis of dosage forms. In addition, emerging technologies, such as UV imaging allowing to obtain the distribution of drug concentration in a time-resolved 2D images based on UV light absorption, utilization of nanotechnology, self-assembled nanomaterials, and aptamer-based nanoparticles have been 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 the modern pharmaceutical analysis.

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Background: Metabolomics is one of the main areas to understand cellular process at molecular level by analyzing metabolites. In recent years metabolomics has been emerged as key tool to understand molecular basis of disease, find diagnostic and prognostic biomarkers, and develop new treatment opportunities and drug molecules. Objective: In this study, an 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 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 in order 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 <0.05) between the POI plasma samples and control subjects. Conclusion: According to the results, two groups were successfully separated through principal component analysis. Among the peaks, phenyl alanine, decanoyl-L-carnitine, 1-palmitoyllysophosphatidylcholine 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.