Exploring a Versatile LC–HRMS Strategy for NDSRI Determination in Beta Blocker Drug Substances

The increasing focus on nitrosamine impurities has prompted analytical development teams across the industry to revisit long-standing assumptions about sensitivity, selectivity, and method versatility. Among the impurity classes now receiving heightened attention are nitrosamine drug substance–related impurities (NDSRIs), a group distinguished by their structural resemblance to parent APIs and their tendency to form under specific manufacturing or storage conditions. For beta blockers, which often contain amine functionalities susceptible to nitrosation, this presents a particularly relevant analytical challenge.

Colorful capsules and pills scattered beside an open prescription bottle.

A recent Thermo Fisher Scientific application note examines this challenge through the lens of LC–HRMS, presenting a unified analytical approach capable of addressing NDSRI quantitation across six different beta blocker drug substances.

Revisiting the complexity of NDSRIs

The scientific and regulatory landscape surrounding NDSRIs continues to evolve. As outlined early in the study (pages 2–3), the scarcity of toxicological data for many of these impurities has led agencies to adopt structure-based frameworks such as the Carcinogenic Potency Categorization Approach (CPCA). These classifications, coupled with low acceptable-intake values, have placed new emphasis on achieving both trace-level sensitivity and high structural specificity.

For many labs, that means rethinking the interplay between chromatographic separations, ionization behavior, adduct formation, and mass accuracy, especially when the impurity under investigation differs only subtly from its corresponding drug substance.

A single method across six APIs

One aspect of the work that may be of interest to analytical scientists is the decision to pursue one LC–HRMS method applicable across six beta blocker drug substances: atenolol, bisoprolol fumarate, carvedilol, labetalol HCl, metoprolol fumarate, and propranolol HCl.

This required careful consideration of:

Column chemistry and dimensions
Mobile phase composition and gradient design
Ion source settings suitable for diverse analyte structures
Product ion selection guided by theoretical fragmentation analysis (pages 6–8)
Valve switching to manage potential interferences

The resulting method offers a perspective on how unified analytical strategies may help streamline workflows in environments where multiple drug substances must be assessed for similar impurity risks.

Method performance: key observations

The study presents a series of experimental evaluations, reproducibility, robustness, linearity, recovery, and ion-ratio confirmation, that provide insight into how the method behaves under different analytical conditions.

A few noteworthy observations include:

Linearity (R² > 0.99 for all NDSRIs): Calibration plots (page 11) illustrate consistent detector response across a broad concentration range.
Sensitivity at low levels: LOQs aligned to 10% of each impurity specification limit (Table 14, page 10), with LODs at approximately one-third of the LOQ.
Long-run robustness: A 21-hour sequence showed stable peak-area performance, with cumulative %RSD values that speak to the system’s suitability for extended runs (page 9).
Chromatographic clarity: Representative chromatograms (pages 13–14) demonstrate distinct separation between NDSRIs and their related APIs, even within a 20-minute gradient.

These results collectively provide a framework for understanding how LC–HRMS can be optimized for structurally similar, low-level impurities in complex matrices.

Key considerations

While every laboratory faces unique constraints, sample types, regulatory expectations, and throughput demands, the work offers several themes that may resonate with teams currently evaluating or refining nitrosamine methodologies:

The emphasis on accurate mass and interference avoidance highlights the value of high-resolution MS when dealing with closely related structures.
The method’s consistency across structurally diverse beta blockers underscores how column and gradient design influence versatility.
The detailed precursor and product ion selection process illustrates a practical approach to balancing sensitivity and selectivity in impurity analysis.

These elements, taken together, form a basis for discussion as laboratories consider how best to adapt their workflows to emerging impurity requirements.

A closer look at the study

For those interested in the nuances of CPCA-driven specification setting, chromatographic optimization, or the application of Orbitrap-based mass spectrometry to low-level impurity work, the full application note provides additional technical depth. It includes complete parameter tables, ion-ratio confirmation data, chromatographic profiles, and experimental rationales that further illuminate the method’s development and evaluation.

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