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Since the initial 2018 recall of angiotensin receptor blockers due to unacceptable levels of mutagenic N-nitrosodimethylamine (NDMA) impurity, numerous drug products delivering diverse active pharmaceutical ingredients (APIs) have been recalled. Regulators and the industry are working together to understand and address this widescale problem. Conventional analysis of NDMA utilizes liquid or gas chromatography-based procedures that can involve complicated sample preparation and slow sample analysis. Selected ion flow tube mass spectrometry (SIFT-MS) analyses NDMA directly in the gas phase using soft chemical ionization, with an LOQ of 2 ng g−1. Through the novel application of the multiple headspace extraction (MHE) technique, NDMA was quantified directly and rapidly from the drug product without dissolution, at levels well below the regulatory acceptable intake of 96 ng day−1. A comparative analysis of recalled metformin using MHE-SIFT-MS and a conventional liquid chromatography–mass spectrometry/mass spectrometry (LC-MS/MS) method showed good agreement. Use of the novel MHE-SIFT-MS approach may enable a wider screening of drug products to be conducted, since it provides around a three-fold increase in daily sample throughput. [ABSTRACT FROM AUTHOR]

Procedures for determination of the residual solvent and volatile impurity content in pharmaceutical products usually rely on dissolution in a solvent, followed by headspace-gas chromatography (HS-GC) analysis. Whereas chromatographic systems can utilize a wide variety of solvents, direct-injection mass spectrometry (DIMS) techniques have fewer solvent options, because elimination of the chromatographic column means that the instrument is more susceptible to saturation. Since water has the lowest impact, it has almost always been the default solvent for DIMS. In this study, selected ion flow tube mass spectrometry (SIFT-MS)—a DIMS technique—was applied to the systematic evaluation of the proportion of solvent that can be utilized (with aqueous diluent) without causing instrument saturation and while maintaining satisfactory analytical performance. The solvents evaluated were N,N-dimethylacetamide (DMAC), N,N-dimethylformamide (DMF), 1,3-dimethyl-2-imidazolidinone (DMI), dimethyl sulfoxide (DMSO), methanol, and triacetin. All solvents are compatible with headspace-SIFT-MS analysis at 5% (min) in water, while DMI, DMAC, and DMSO can be used at higher concentrations (50, 100, and 25%, respectively), though suffering substantial diminution of the limit of quantitation for non-polar analytes at higher proportions of non-aqueous solvent. Analytical performance was also evaluated using linearity, repeatability, and recovery measurements. This work demonstrates that organic solvents diluted in water can be utilized with headspace-SIFT-MS and provide an approach for evaluation of additional diluent solvents. [ABSTRACT FROM AUTHOR]

Residual solvents in pharmaceutical excipients, active pharmaceutical ingredients (APIs), and finished products are usually analyzed using gas chromatography (GC)-based techniques according to a pharmacopeial monograph, such as the United States Pharmacopeia's (USP) chapter <467>. GC analyses are often slow, which limits sample throughput. Selected ion flow tube mass spectrometry (SIFT-MS) removes the rate-limiting chromatographic separation step, potentially offering faster sample analyses. This approach was demonstrated recently with the publication of an alternative SIFT-MS procedure which was successfully validated against the performance criteria in USP chapter <1467>. The present study expands upon the previous work by conducting a head-to-head comparison of GC-flame ionization detection (GC-FID) and SIFT-MS procedures. The results obtained in this cross-platform study demonstrated similar performance for the GC-FID and SIFT-MS procedures for linearity (R2 > 0.94 and 0.97, respectively) and repeatability (<17%RSD and <10%RSD). For accuracy and recovery, acceptance criteria (within 20%) were achieved for most compounds across the two drug products (SIFT-MS suffered fewer failures, possibly due to shorter wait times prior to analysis). Additionally, SIFT-MS analyzed samples over 11-fold faster than GC-FID, increasing daily sample throughput and reducing the time taken to determine the result. This study therefore suggests that residual solvent analysis using SIFT-MS may support workflow improvements for pharmaceutical manufacturers. [ABSTRACT FROM AUTHOR]

Rationale: Recycled plastics are increasingly used for packaging of fast‐moving consumer goods (FMCG). Compared with packaging made from virgin polymers, there is greater risk of taints entering products due to prior use of the polymers and incomplete cleaning. Increased quality assurance testing of polymer feedstock is required for recycled packaging. Selected ion flow tube mass spectrometry (SIFT‐MS) analysis coupled with multivariate statistical data processing can provide high‐throughput untargeted screening of recycled polymers at low cost per sample. Methods: SIFT‐MS is a direct‐injection MS technique that provides high‐throughput automated headspace analysis of polymer samples when coupled with a syringe‐injection autosampler (12 incubated samples per hour). Full‐scan SIFT‐MS data were processed using multivariate statistical analysis (specifically, the soft independent modeling by class analogy (SIMCA) algorithm). Results: SIFT‐MS full‐scan data were acquired for ten replicates each of ten recycled and four virgin high‐density polyethylene (HDPE) pellet products from multiple manufacturers. The samples varied approximately 20‐fold in terms of total volatile residue, while showing very high repeatability across replicates. SIFT‐MS scan data were dominated by aliphatic and monoterpene hydrocarbon residues, and – to a lesser extent – alcohols. Application of the SIMCA algorithm to the data resulted in successful classification by both individual samples and manufacturers. Conclusions: Automated, untargeted SIFT‐MS analysis coupled with multivariate statistical data analysis has the potential to provide rapid, effective screening of recycled polymer products, which would provide increased quality assurance of recycled polymers used for FMCG. [ABSTRACT FROM AUTHOR]

The article discusses the use of selected ion flow tube mass spectrometry (SIFT-MS) for monitoring inorganic gases and volatile organic compounds (VOCs). Topics discussed include the use of autosampler integration for leveraging high sample throughput, elimination of chromatographic separation and application of continuous headspace analysis (CHA) such as fragrance analysis.

Selected ion flow tube mass spectrometry (SIFT-MS) is a recent addition to the routine analysis and research laboratory toolkit, primarily as a quantitative tool. SIFT-MS employs ultra-soft chemical ionisation to directly analyse volatile organic compounds (VOCs) in air and headspace in real-time with high specificity and sensitivity. Coupling SIFT-MS with conventional laboratory automation equipment ( i.e. , that used with chromatography systems) has proved straightforward and enables unattended operation, processing up to 230 samples per day per SIFT-MS instrument. Automated SIFT-MS systems have been applied to analysis of headspace (static, continuous, multiple headspace extraction, and standard additions), sample bags, and thermal desorption tubes. Applications using these approaches include consumer and drug product testing for volatile impurities (such as benzene, formaldehyde, and nitrosamines), environmental samples, clinical research, and materials testing. The stability of the SIFT-MS technique, coupled with its ability to analyse diverse VOCs in a single run, removes the need for system configuration changes and hence reduces calibration demand and streamlines workflows, reducing the time to report the first results in a sequence schedule and increasing sample throughput compared to chromatographic systems. This article reviews the development of the automated-SIFT-MS approach using a variety of application examples and recommends hardware and software improvements that could further enhance its adoption.