The enhanced sensitivity of the SCIEX 7500 System will allow lower compound concentrations to be used in transporter assays, more closely align with the lower predicted systemic exposures for more potent drug candidates. Higher quality data will better guide compound rank ordering and selection in early stage drug development.
As drug candidates progress through early to late stage drug discovery, more comprehensive metabolic studies are performed to characterize the site of metabolism, to inform researchers working to improve drug performance. MS/MS data is often required to fully characterize the metabolites, but this is difficult when the resulting metabolites become labile. Here, two orthogonal fragmentation techniques were compared to determine the in vitro metabolism of the drug darunavir. Using the ZenoTOF 7600 system and EAD fragmentation, the confident assignment and differentiation of O- and N-glucuronide conjugates was achieved.
Echo MS System was used for routine, early stage bioanalytical quantification. Three plasma sample preparation techniques were explored, and showed the feasibility of minimizing sample preparation, minimal differences were observed in lower detection limits for dilution, basic protein precipitation and simply analyzing plasma directly without any treatment at all. This simple sample preparation combined with the speed and simplicity of analysis using the Echo MS System offers an attractive approach for high turnaround bioanalytical laboratories.
Since the discovery of genotoxic nistrosamines in pharmaceutical products in 2018, sensitive and selective methods for quantification of these contaminants has become critical. The method presented here provides good chromatographic separation of the six analyzed nitrosamine compounds from the losartan API. Good linearity over the concentration range monitored was observed and the lower limits of quantification for each compound translate to daily intake limits significantly lower than those currently specified by the FDA and EMA.
Since the discovery of genotoxic nitrosamines in various drug products, guidances have been released to control for the presence of these impurities. LC-MS assays have been developed to detect the various nitrosamines in numerous drug classes. Here, a method for the quantification of eight nitrosamines in telmisartan using the SCIEX QTRAP 5500+ system is described that easily meets current regulatory action limits. System sensitivity allows for the detection of nitrosamines down to the 0.005 ppm (µg/g) level, below the FDA specified limit of daily exposure of 0.03 ppm in API.
Since 2018, there has been high concern about the presence of nitrosamine impurities in certain drug products. More recently concerns have been raised about the potential presence of NDMA in pioglitazone manufactured in India. Here a method has been developed using the X500 QTOF system for the detection of six nitrosamines in pioglitazone. Good chromatographic separation of the drug product from the impurities was achieved. Using both MS and MS/MS data, good sensitivity was observed for detection below the required limit of 30 µg/g. Concentration curves showed good linearity across the range tested.
Recently, certain Valsartan drugs have been recalled due to contamination with N-nitrosodimethylamine (NDMA), which is a potential human carcinogen. Here, an LC-MSMS method was developed and partially validated for the quantitative analysis of six Nitrosamines. Good linearity, sensitivity and reproducibility was achieved over a broad concentration range, meeting regulatory requirements.
An LC-MS/MS General Unknown Comparative Screening (GUCS) workflow using X500R QTOF System that enables quantitative detection of impurities, allow batch-to-batch monitoring for comparison, and is easy to learn and implement in QC labs, working to improve drug safety.
In this work, a small group of known extractable and leachable compounds were selected to showcase the workflows on the X500R QTOF System, using SWATH® Acquisition and SCIEX OS Software. Three workflows were demonstrated, a targeted screening workflow, a non-targeted screening workflow and finally a targeted quantification workflow.
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