Using Gas Chromatography-Mass Spectrometry to Monitor Impurities and Safeguard Public Health

Using Gas Chromatography-Mass Spectrometry to Monitor Impurities and Safeguard Public Health

Introduction

Consistently and accurately monitoring product purity is critical in pharmaceutical manufacturing. Quality control is everything: it underpins the drug production process in its entirety, from regulatory compliance to commercial success to patient safety.

Impurities in pharmaceutical products can endanger human health and hinder the creation, approval and release of medicines, bringing additional cost, risk and difficulty to the manufacturing space. The importance of quality control and, more specifically, the detection of impurities, was made apparent by the recent discovery of nitrosamines in the widely used anti-hypertensive drug Valsartan [1]. This detection led to multiple global recalls of potentially affected batches of Valsartan in 2018 and 2019, and has sparked rising concern over the presence of impurities in pharmaceutical products. FDA recommendations and standards in this area are also rapidly evolving in the aftermath of the Valsartan crisis, introducing more pressing quality control demands that companies must follow in order to remain compliant and produce medicines that are certified safe.

While challenging, this situation has also opened up opportunities for meaningful innovation. Indeed, several forward-thinking technologies and solutions exist today that help pharmaceutical manufacturers navigate this fast-moving landscape, so they can confidently ensure that their products are safe and of the best possible quality.

The Aftermath of the Valsartan Crisis

Nitrosamines are classified as probable human carcinogens and are, therefore, strictly regulated in drug products. In 2018, unacceptable amounts of particular nitrosamines [N-nitrosodimethylamine (NDMA) and N-nitrodiethylamine (NDEA)] were found in batches of Valsartan, an angiotensin II receptor blocker (ARB) used to treat high blood pressure, heart and kidney failure, and chronic kidney disease.

Following this detection, the FDA announced a recall of several drugs containing Valsartan’s Active Pharmaceutical Ingredient (API). Valsartan is taken by approximately three million Americans, and the recall affected over half of the US supply of the drug. Since the recall, further nitrosamine impurities have been found in various other ARBs, prompting a wider recall from over 40 major manufacturers worldwide.

Investigations into the cause of these impurities suggest that they arose due to a mix of modifications in manufacturing processes, and the reuse of raw materials. Nitrosamine impurities form when producing sartans under specific conditions using particular solvents, reagents and raw materials. In the case of Valsartan, the use of dimethylformamide as a solvent in the manufacturing process, chosen to increase yields and reduce costs, appears to cause a side reaction that produces nitrosamine compounds in specific conditions, introducing impurities into the final product.

Overall, the FDA outlined multiple areas of concern across impurity control, change control and cross contamination risk, emphasizing the importance of maintaining current Good Manufacturing Practice for APIs.

A Rising Need for Accurate, Sensitive Methods of Analysis

Following a brief transition period that imposed strict temporary limits on impurity levels, ARB producers must demonstrate that their sartan products have no quantifiable levels of impurities by testing batches for nitrosamines [1]. The FDA imposes a maximum daily exposure to nitrosamines in the range of sub-ppm levels in the final product, due to their carcinogenic potential — but these limits are expected to decrease to undetectable levels as soon as manufacturing processes are modified to avoid nitrosamine formation [2]. Such limits have resulted in a growing demand for highly sensitive and compliant analytical solutions capable of accurately detecting and quantifying very low levels of nitrosamines in drug products.

Adding to the difficulty of nitrosamine analysis, the list of nitrosamine impurities to be monitored, initially limited to NDMA and NDEA, is evolving fast and growing steadily, expanding the number of impurities manufacturers must account for in their quality control and assurance processes. These quality control workflows are even more crucial in the case of ARBs given their current market position. The Valsartan patent expired in 2012, and generic manufacturers from India and China now dominate the US ARB market. As generic drugs represent the majority of widely consumed medicines on a global scale, the presence of harmful impurities could, therefore, have a potentially significant impact on public health [1].

The Capabilities of Gas Chromatography-Mass Spectrometry

To detect nitrosamines in sartans, the FDA and the Chinese Food and Drug Administration (CFDA) recommends multiple methodologies based on gas chromatography-mass spectrometry (GC-MS) combined with liquid or headspace injection. GC-MS systems bring together the capabilities of gas chromatography (GC) and mass spectrometry (MS) to provide reliable, efficient and specific ways to detect impurities at trace levels.

Headspace injection with single quadrupole GC-MS (HS-GC-MS)

Headspace methods enable simple, efficient, solvent-less extraction of volatile impurities from solid API and drug product samples. Headspace injection is a clean technique with benefits over direct liquid injection: almost no sample preparation is required, and there is no need to inject the matrix into the system. It is highly robust against possible instrument contamination as a result, increasing system uptime.

The FDA recommends two different headspace-GC-MS methods for analyzing impurities in sartans: one that targets NDMA using dimethyl sulfoxide to dissolve the drug, and one that targets both NDMA and NDEA using 1-methyl-2-pyrrolidinone to dissolve the drug [3,4]. In both cases, the method must be robust against possible carryover effects, and capable of effectively recovering target analytes. A highly effective approach to achieving both of these objectives—low carryover, high recovery—was demonstrated using equipment capable of minimizing sample path through a direct GC column connection to the headspace autosampler: a Thermo Scientific TRACE 1310 GC with a split/splitless inlet coupled to a Thermo Scientific ISQ 7000 single quadrupole MS [5]. Headspace sampling can be effectively coupled to either single or tandem quadrupole GC-MS/MS to target multiple nitrosamines [NDMA, NDEA, N-Nitrosodiisopropylamine (NDIPA), N-Nitrosoethylisopropylamine (NEIPA), and more] [6].

Liquid injection with single quadrupole GC-MS

In this method, recommended by the CFDA [7], methanol is used for liquid-liquid extraction of the Valsartan sample. The sample is then centrifuged before an aliquot of the supernatant is injected and tested for nitrosamines via single quadrupole GC-MS. Research using this method, based on the same equipment as in the headspace method, has detected NDMA in Valsartan, with good linearity, sensitivity, repeatability and sample recovery [5].

Liquid injection using triple quadrupole tandem MS (GC-MS/MS)

GC-MS/MS [8] combines the benefits of both the aforementioned methods. This approach uses deuterated and carbon-13 double-labeled NDMA as an internal standard, and then triple quadrupole GC-MS/MS to detect and quantify levels of NDMA and NDEA. Research using this method, although using external standards in place of deuterated NDMA standards, detected both NDMA and NDEA at excellent sensitivity and selectivity (particularly for NDEA; this high selectivity allowed the researchers to reach far lower detection limits for NDEA and achieve more accurate quantitation) [5]. The use of a triple, rather than single, quadrupole mass spectrometer brings improved sensitivity of detection and matrix selectivity, making this method the currently preferred solution to reach lower levels of detection.

These recommended methods can identify and quantify multiple different nitrosamines in ARB APIs and drug products. Each configuration has been tested for robustness, repeatability and compliance, and returns results that meet or exceed official required sensitivity levels.

The analytical challenges and requirements around nitrosamine detection in drug products are growing and expanding from sartans to different APIs [9] — and, in some cases, require the use of complementary LC-MS analytical methodology [10]. Moreover, the steady increase of nitrosamines to be detected is causing laboratories to proactively screen for untargeted impurities using increasingly sophisticated analytical systems (such as high-resolution accurate-mass [HRAM] GC-MS). As methodologies continue to develop, the use of sensitive and reliable analytical technologies is crucial for detecting impurities in pharmaceutical manufacturing and ensuring that patient health remains of top priority.

Conclusion

Pharmaceutical manufacturers can benefit from effective sampling approaches coupled to sensitive GC-MS analytical systems that can be selected and configured to suit desired laboratory use. These advanced, robust solutions offer significant potential to manufacturers needing to confidently ensure that their products are of high quality and free from potentially harmful impurities. The GC-MS systems described here are compliant with all recommended standards for nitrosamine detection and quantification in sartans. They provide excellent sensitivity, flexibility, reliability and analytical performance, and are suitable for the routine detection of impurities — something that has never been more important or pressing in improving product safety, protecting manufacturing workflows and safeguarding patient health.

 

Daniela Cavagnino is the product marketing manager for Thermo Fisher Scientific.

References

  1.  Cavagnino, D. (2019) Quality Concern Rises Over Valsartan Crisis [online] Available at: https://analyteguru.com/quality-concern-rises-over-valsartan-crisis/ [Accessed 27/03/20]
  2. U.S. Food & Drug Administration. FDA Updates and Press Announcements on Angiotensin II Receptor Blocker (ARB) Recalls, 11/07/19. Available at: https://www.fda.gov/drugs/drug-safety-and-availability/fda-updates-and-press-announcements-angiotensin-ii-receptor-blocker-arb-recalls-valsartan-losartan#interimlimits2 [Accessed 16/04/20].
  3. U.S. Food & Drug Administration (2019) GC/MS Headspace Method for Detection of NDMA in Valsartan Drug Substance and Drug Products, 01/25/19. Available at: https://www.fda.gov/media/115965/download [Accessed 06/04/20].
  4. U.S. Food & Drug Administration (2019) Combined N-Nitrosodimethylamine (NDMA) and N-Nitrosodiethylamine (NDEA) Impurity Assay by GC/MS-Headspace, 01/28/2019. Available at: https://www.fda.gov/media/117843/download [Accessed 06/04/20].
  5.  Zhang, Y., Che, J., Wang, S. (2019) Determination of genotoxic nitrosamines in Valsartan with gas chromatography and mass spectrometry (Application Note 21922) Available at: https://assets.thermofisher.com/TFS-Assets/CMD/Application-Notes/an-21922-gc-nitrosamines-valsartan-an21922-en.pdf [Accessed 27/03/20]
  6. Cavagnino, D. (n.d.). Attacking the opportunity of Nitrosamine impurities in pharmaceuticals: Opportunities for GC-MS and LC-MS Solutions. Presentation.
  7. Chinese Pharmacopoeia Commission (2018) Public notice on the revised version of Valsartan National Standard. Available at: http://www.chp.org.cn/view/ff80808164eede7e016545903eea6d2f?a=BZHXYP [Accessed 06/04/20].
  8. U.S. Food & Drug Administration (2018) Combined Direct Injection N-Nitrosodimethylamine (NDMA) and N-Nitrosodiethylamine (NDEA) Impurity Assay by GC/MS, 12/11/2018. Available at: https://www.fda.gov/media/117807/download [Accessed 06/04/20].
  9. https://www.fda.gov/drugs/drug-safety-and-availability/fda-updates-and-press-announcements-ndma-metformin
  10. U.S. Food & Drug Administration (2019) Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) Method for the Determination of Six Nitrosamine Impurities in ARB Drugs. Available at: https://www.fda.gov/media/125478/download [Accessed 15/04/20].
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