The present study focuses on the method development and validation for detection of selective elemental impurities in Clarithromycin active pharmaceutical ingredient (API) using Inductively Coupled Plasma–Mass Spectrometry (ICP-MS). Elemental impurities, originating from catalysts, raw materials, or manufacturing processes, can adversely affect product safety and efficacy. Hence, a sensitive and precise analytical method was developed in accordance with ICH Q3D, USP <232>, and <233> guidelines. The optimized ICP-MS parameters ensured accurate quantification of 23 elemental impurities, including Cd, Pb, As, Hg, Co, Ni, V, Pd, Pt, Ir, Rh, Ru, Se, Ag, Mo, Sb, Cu, Sn, Cr, Ba, Li, Tl, and Au, in a single analytical run without the need for internal standards. The developed method was validated for linearity, accuracy, precision, specificity, limit of detection (LOD), and limit of quantification (LOQ). The method exhibited strong linear correlation (r² ≥ 0.99), recovery within 70–150%, and relative standard deviation (RSD) <20%, satisfying USP acceptance criteria. The Kinetic Energy Discrimination (KED) mode minimized polyatomic interference, improving signal stability and reducing analysis time. This validated method proved to be simple, rapid, rugged, cost-effective, and suitable for routine quality control analysis of Clarithromycin API to ensure compliance with elemental impurity regulations and pharmaceutical safety standards.

Background: Stigma maydis are becoming more popular as a healthy substitute for people with lifestyle disorders. They offer dietary fiber, polyphenols, minerals, vitamins, protein, and antioxidants. The evidence that is now available indicates that the leading causes of sickness, disability, and death in India are chronic obstructive and mental disorders, hypertension, cardiovascular illnesses, cancer, diabetes, lung disease, chronic renal disease, trauma, and stroke. When it comes to treating the illness and its repercussions, allopathic medications are not very effective. However, how the Stigma maydis-derived chemical compounds work in treating diabetes remains unclarified. Herein, we integrate molecular docking and network pharmacology to elucidate the active constituents and potential mechanisms of Stigma maydis against diabetes. Purpose: This study aimed to validate the antidiabetic effect of Stigma maydis silk lead molecule through in-silico molecular docking. Method: α-amylase was chosen as the target proteins in the current investigation of antidiabetic effect respectively. The bond was found using the Auto Dock software using a grid-based docking method. Compounds' 2D structures were generated, converted to 3D, and subsequently energetically lowered up to an arms gradient of 0.01 using the Merck Molecular Force Field (MMFF). Result: Maysin and isoorientin found to be effective component for anti-diabetic potential and effectively binds to be target protein α-amylase with binding energy-8.11 & -5.96 kcal/mol respectively and showed potent inhibitory action on target proteins. Conclusion: The results of the current investigation demonstrated that the chosen lead molecule (Maysin and isoorientin) had significant inhibitory effects on the selected target proteins, consequently showed potent antidiabetic efficacy. The molecular docking analysis demonstrated significant binding energy.