Development and Validation of 1H Nuclear Magnetic Resonance Quantitative Method for Efavirenz API Quality Control

Abstract

Background: The pharmaceutical industry is constantly looking for a better way to ensure and improve its products' safety, quality, and effectiveness. Since there are many attributes of the drug substance and excipients that could potentially affect the Critical Quality Attributes (CQAs) of the intermediates and the final product, the evaluation of the raw material's physicochemical characteristics is crucial as they directly affect the quality, safety, efficacy, and lot-to-lot consistency. Scientists rely on methods, like HPLC, HPTLC, LC-MS, GC-MS, and NMR, to analyze these substances. The advantage of NMR is that it is considered a primary analytical method compared to other analytical techniques. Objective: This work aimed to present a simple, rapid, specific, and accurate method by proton Nuclear Magnetic Resonance spectroscopy (1H-NMR) developed to determine the activity of the antiretroviral Efavirenz’s (EFZ) Active Pharmaceutical Ingredient (API). The method was based on quantitative NMR spectroscopy (qNMR). Methods: A Bruker Avance spectrometer (11.7 Tesla, 500 MHz for 1H) with a 5mm probe was used. The 1H-NMR signal at 7.54 ppm corresponding to the analyte of interest was employed to quantify the drug. The method was validated for specificity, selectivity, intermediate precision, linearity, range of work, accuracy, and robustness. Results: The method developed was specific and linear (r2 = 0.9998) with a value between 4.30 mg/mL and 12.40 mg/mL. The relative standard deviation for accuracy and precision was 0.4% or less. The method's robustness was demonstrated by changing four different parameters, and the difference among each was 1.2% or less. The results of this work have been found to be in agreement with those obtained from High-performance Liquid Chromatography (HPLC) analysis. Conclusion: The proposed method has been found to be a valuable and practical tool for quality control. Its applicability to determining many APIs and saving solvent use and time is highlighted.