Development and Validation of Reversed-Phase HPLC Method for the Determination of Epirubicin and Its Application to the Pharmacokinetic Study of Epirubicin Loaded Polymeric Nanoparticle Formulations in Rats.

Epirubicin, commonly used as anticancer drug for various types of tumors like breast, liver, lung, stomach, ovaries, and bladder for its improved antitumor efficacy and safety. A rapid, sensitive, and reliable bioanalytical method was developed and validated for epirubicin using conventional reverse phase HPLC with UV detection. The developed method was successfully applied to investigate the pharmacokinetics of epirubicin after intravenous administration of a reference epirubicin and its designed nano-formulations to rats. C18 column was used in an isocratic mode for analyte elution at a flow rate of 1.0 mL/min with UV detection of 234 nm. The mobile phase was composed of acetonitrile 22% (channel A) and 0.025% tri fluoro-acetic acid in water (channel B). Ondansetron was added as an internal standard, and the plasma samples were analyzed after protein precipitation. A concentration range of 0.016-1.024 µg/mL was selected for the construction of calibration curves, with LLOQ of 0.016 µg/mL. Results showed that the value of AUC, half-life, and mean residence time of designed nano-formulation were bounce to 10, 9, and 11 times higher, when compared to the reference epirubicin after intravenous dose of 10 mg/kg of epirubicin to rats, respectively. The designed epirubicin nano-formulations achieved clinically significant pharmacokinetic values in rats. Current method will help epirubicin future research using clinical samples and drug bioequivalence studies on various novel formulations for drug safety purposes.

A meta-analysis of genome-wide gene expression differences identifies promising targets for type 2 diabetes mellitus.

Aims/introduction: Due to the heterogeneous nature of type 2 diabetes mellitus and its complex effects on hemodynamics, there is a need to identify new candidate markers which are involved in the development of type 2 diabetes mellitus (DM) and can serve as potential targets. As the global diabetes prevalence in 2019 was estimated as 9.3% (463 million people), rising to 10.2% (578 million) by 2030 and 10.9% (700 million) by 2045, the need to limit this rapid prevalence is of concern. The study aims to identify the possible biomarkers of type 2 diabetes mellitus with the help of the system biology approach using R programming. Materials and methods: Several target proteins that were found to be associated with the source genes were further curated for their role in type 2 diabetes mellitus. The differential expression analysis provided 50 differentially expressed genes by pairwise comparison between the biologically comparable groups out of which eight differentially expressed genes were short-listed. These DEGs were as follows: MCL1, PTX3, CYP3A4, PTGS1, SSTR2, SERPINA3, TDO2, and GALNT7. Results: The cluster analysis showed clear differences between the control and treated groups. The functional relationship of the signature genes showed a protein-protein interaction network with the target protein. Moreover, several transcriptional factors such as DBX2, HOXB7, POU3F4, MSX2, EBF1, and E4F1 showed association with these identified differentially expressed genes. Conclusions: The study highlighted the important markers for diabetes mellitus that have shown interaction with other proteins having a role in the progression of diabetes mellitus that can serve as new targets in the management of DM.