Study of degradation behaviour of montelukast sodium and its marketed formulation in oxidative and accelerated test conditions and prediction of physicochemical and ADMET properties of its degradation products using ADMET Predictor™

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Study of oxidative stability of pharmaceutical actives and formulations is important as oxidation pathway is the second most significant route for the decay of pharmaceuticals. Montelukast sodium, a leukotriene receptor antagonist, is prone to oxidation reactions owing to sensitive moieties in its structure. It is also known to be light sensitive. This study was aimed to understand the degradation behaviour of the drug in different oxidative media containing hydrogen peroxide, AIBN, Fe3+, Fenton’s reagent and O2 environment under normal laboratory light conditions. The degradation behaviour of the drug was also evaluated in solid sate under ICH recommended accelerated stability condition of 40°C/75% RH to correlate with the degradation products (DPs) formed in a solid oral formulation. A total of nine DPs (MTK 1 to MTK 9) were formed from both the drug substance and the marketed tablet formulation on storage under controlled oxygen environment in normal laboratory light and temperature conditions. These DPs were well separated on a C-18 column using a gradient HPLC method. The characterization of DPs was done based on HRMS and multi-stage tandem mass spectrometric (MSn) data. The knowledge of the structure of DPs helped in laying down degradation pathway of the drug. Also, mechanism for the formation of each DP was postulated. Finally, physicochemical as well as absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of the DPs were predicted by ADMET Predictor™ software.HIGHLIGHTSNine degradation products of montelukast sodium were detected by HPLC-PDA.The products were characterized using mass tools.Degradation pathway of the drug and the mechanisms are proposed.Absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of the degradation products were predicted using ADMET Predictor™ software.

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