Identification and characterization of two new oxidation degradation impurities in cinnarizine through LC‐HRMS/MS and 1H NMR, along with in silico toxicity predictions of its degradation products
Abstract
Abstract Cinnarizine (CIN) drug substance is a US FDA and EMA approved antihistaminic drug, There is no report available on CIN for the identification of degradation products and their degradation pathway. Herein, we report a stability‐indicating assay method for CIN, the formation and characterization of its major degradation products using LC‐HRMS/MS and 1H‐NMR techniques. CIN was subjected to oxidation, acid, base, thermal and photolytic degradation conditions. Two unknown degradation products (DP‐1 and DP‐2) of CIN were formed under oxidative conditions. We successfully separated these degradants using gradient elution on an Inertsil ODS 3 V column (150 × 4.6 mm, 5 μm) using mobile phase A consisting of 0.1% formic acid and the mobile phase B consisting of 0.1% formic acid/acetonitrile (20/80, v/v). CIN was labile to oxidative conditions and stable to acidic, alkaline hydrolytic, photolytic and thermal conditions. The degradation pathways were derived from the nature of the product formed under oxidative degradation conditions and available reports for confirmation of the mechanism. Since the stability‐indicating assay method can be utilized for stability studies and routine quality control of CIN in both the pharmaceutical industry and research laboratories. This method has been validated in compliance with the guidelines set forth by the ICH.
How strong is the evidence?
Evidence Hub reads this as a simulation / modelling, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- The Prediction of the In Vitro Release Curves for PLGA-Based Drug Delivery Systems with Neural Networks
- Promising Ursolic Acid as a Novel Antituberculosis Agent: Current Progress and Challenges
- Proof of principle concept for the analysis and functional prediction of rare genetic variants in the CYP2C19 and CYP2D6 genes
- Fabrication, characterization, and docking studies of furosemide-loaded nanosponges using the emulsion solvent diffusion method
- The Effect of Concomitant Administration of Proton Pump Inhibitors on the Pharmacokinetics of CDK4/6 Inhibitors in Rats: Implications for the Evaluation of Hepatic and Transporter-Mediated Drug–Drug Interactions
- Mining the Metabolic Capacity of Clostridium sporogenes Aided by Machine Learning
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.