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Rigorous control of N-nitrosamine impurities within drug products is essential due to their potential carcinogenicity. Nitrosamines are often formed through the reaction of vulnerable amines present in the drug substance with nitrite from excipients, where nitrite is often the limiting reagent. Therefore, it is important to understand the level of nitrite in excipients to assess the risk of nitrosamine formation in a drug product. For this purpose, the Lhasa Nitrites database was created to collate and curate nitrite data in excipients, reagents and solvents contributed by member companies worldwide. This data is generated using different methods by different companies, it is therefore necessary to understand the accuracy and variability of this data. A comparative testing study was conducted, by the Lhasa Nitrites consortium, involving six independent labs using their analysis procedure including ion chromatography with conductivity detection (IC-CD), pre-column derivatisation with Griess reagent followed by LC-UV analysis (Griess/LC-UV), or pre-column derivatisation with 2,3-diaminonaphthalene followed by LC-FLR analysis (DAN/LC-FLR). Three common excipients were selected including microcrystalline cellulose, magnesium stearate and lactose. The results were evaluated with respect to detection method, sample extraction procedure, and clarification method. Consistent results were obtained across different laboratories for lactose. However, no quantifiable nitrite levels were detected in the MCC lots used due to matrix interference during sample selection. Highest variability was observed for magnesium stearate, primarily due to the use of sonication as part of the sample preparation to overcome the challenges to extract nitrite from the matrix. This study reveals the potential variability for the analysis of trace level nitrite in excipients, underscoring the need for more rigorous method characterisation including specificity, accuracy and precision. As an initial response, the Lhasa Nitrites consortium developed and disseminated updated guidance for method validation, reflecting the collective knowledge gained through comparative testing and data sharing.