Tools and Technologies for Robust Method Lifecycle Management in Liquid Chromatography

Many industries need faster, more sensitive and robust liquid chromatography (LC) methods capable of meeting stringent regulatory requirements. As part of meeting these requirements and ensuring product quality and safety, it is often the case that an LC method must be able to reliably separate and detect all compounds and impurities within a sample. To do this, scientists must complete extensive method development and optimization for different analytes, often across different instruments and laboratories.

Despite advances in LC technology improving analysis speed, however, method development and validation phases still cause bottlenecks that can take weeks or months to complete, especially if there is a need to test and optimize multiple different column sizes. This process requires multiple chromatographic runs to test different parameters, which reduces productivity and increases operational costs. In addition, once optimized for one instrument, methods are often transferred to other instruments within a lab, or to other labs, presenting a new set of challenges in terms of optimization and validation.

Every LC method also needs to be reviewed regularly to ensure that it continues to perform as initially intended. In practice, this is a time-consuming and costly process, requiring multiple experimental runs for each instrument. This article explores how advanced LC technologies can help streamline this task.

The lifecycle of method management

Every analytical method has a lifecycle that begins when a method is first developed and validated and continues as the method is verified and modernized to keep pace with technology advances and as new analytical approaches emerge. Method lifecycle management (MLCM) is a control strategy that ensures analytical instruments perform as intended throughout their lifetime.

In an optimal MLCM strategy, effort is invested upfront in building robust methods, resulting in a complete understanding of the method variables and the impact they have on analysis.By doing so, analysts can quickly assess the impact of a mistake or change further down the line.

Taking LC as an example, for any method there is a lifecycle that comprises three main stages: method development, method transfer, and method qualification or validation. In method development, separation parameters are optimized or modernized, ensuring the best techniques and instrumentation are used to properly assess the goal of the analysis, such as detecting impurities within a sample. In method transfer, a method that is optimized on one instrument may be rolled out to other laboratories or multiple instruments/platforms. Finally, in method qualification or validation, the robustness of the method and—if appropriate—its compliance with regulatory standards is assured and monitored long-term.

Automation is often used upfront to develop LC methods. Yet, at each stage in the LC method lifecycle, there is a range of common instrument challenges. The remainder of this article illustrates how advanced technologies can support a robust MLCM strategy.

Automated options for method development

At the initial LC method development stage, there are several parameters to optimize. These include the mobile phase pH, column chemistry, separation temperature, and the gradient profile.

The mobile phase pH value is paramount when analyzing ionizable compounds and should be optimized for separation target compounds and impurities. This optimization can be particularly challenging for acidic and basic compound mixtures and requires screening of various pH values. Separation may need to be tested on a range of columns because selectivity can vary dramatically between different chemistries. Similarly, the optimal separation temperature should be explored during method development because this can dramatically alter selectivity.

Optimizing all these parameters during method development can require many chromatographic runs. Moreover, users must consider the complex interactions between various separation parameters and then review large amounts of data from multiple runs, testing multiple parameters, to decide on the optimal conditions for their analysis goal. As a result, method development can be a laborious, resource-intensive, and somewhat subjective process for chromatographers.

By contrast, advanced automated LC instruments and software can accelerate method development by offering the potential to screen multiple columns and an extensive range of solvents easily and efficiently. For example, an automated method scouting solution was used to develop an LC method for separating two isomeric forms of budesonide, a steroid used to treat asthma (1) . Through automated switching between port valves, it was possible to scout four columns spanning a broad selectivity range with six different aqueous buffers, from pH 3 to pH 8.

A predefined eWorkflow template with methods for scouting and column switching made set-up easy while also allowing changes to key custom variables such as flow rate and column temperature.

After analysis, advanced LC software objectively selected the optimal run conditions from the test data based on pre-determined criteria for a specific analysis goal—in this case, the ability to resolve a critical peak pair representing the budesonide epimers. In total, it was possible to test 24 different chromatographic conditions in less than 20 hours with a total data processing time of less than one hour, without the need for manual interaction.

For improved separation of the isomers, the optimal separation temperature was investigated using advanced thermostatting options (Figure 1). An optimal sub-ambient separation temperature of 10 °C improved the resolution. With advanced LC systems, it’s possible to scout temperature settings while simultaneously using a passive eluent pre-heater for all four columns to avoid any thermal mismatch.

In conclusion, using an automated method scouting solution with advanced LC analysis software accelerated the method development process for budesonide analysis significantly.

Smooth and seamless method transfer

The next stage of an MLCM strategy is method transfer. Instrument-to-instrument transfer of an LC method is a frequent challenge for most analytical laboratories, occurring when methods are rolled out to other laboratories or transferred to additional or more modern instruments. The complexity of the method transfer process will depend on the requirements of the analytical outcome and the defined limits of acceptable deviation. During method transfer, only minimal modifications of method parameters are permissible without the need for time-consuming revalidation. Ultimately, for most laboratories, method transfer is a pain point that can cause delays in the implementation of an analysis method. The technical characteristics of a transferring or receiving system often differ, and even small mismatches between flow path volumes on different instruments can influence peak retention times or resolution, causing inconsistencies in analysis.

Advanced LC systems make method transfer much more straightforward, owing to their ability to adjust parameters flexibly and automatically. This ability removes the burden of manually matching parameters, such as the gradient delay volume (GDV), pump mixing mode, and column and eluent thermostatting options, all of which can influence peak retention times or resolution and need careful attention during method transfer.

One example is the transfer of a compendial method for impurity analysis of the antiseptic and disinfectant chlorhexidine digluconate from one LC instrument to another (2). Figure 2 (top) shows the congruence in the peak area between the two instruments.

Although the relative retention times were similar, there were small deviations in absolute retention time, with all peaks eluting slightly earlier on the Vanquish Core instrument. To compensate for this, the GDV was fine-tuned on the Vanquish instrument. Analysts can achieve this through two means. First, it is possible to tune the idle volume setting of the autosampler’s metering device within a 230-uL range (the default setting is 25 uL). Second, using an optional method transfer kit, it becomes feasible to insert a 200-uL volume loop into the flow path between pump and autosampler. Together, these adjustments make it possible to tune the GDV to up to 430 uL. In the chlorhexidine example, it was possible to fine-tune the receiving system’s GDVs by increasing the idle volume from default (25 uL) to 200 uL, and this decreased the deviations in retention time for chlorhexidine impurity peaks (Figure 2, bottom).

Challenges in method validation

The third stage of a method’s lifecycle is its validation, or qualification, to assure its robustness and compliance with relevant regulatory standards. To validate an LC method, laboratories typically create injection sequences, data processing steps, and reports—all of which can be complex and time-consuming. Moreover, the data processing step is often laborious and error-prone, involving manual or semi-automated export to an external analysis program or spreadsheet.

Using an advanced LC system with an accompanying data management system makes it possible to automate every step of validation. A further advantage is the pre-configuration for regulatory compliance (e.g., with International Council for Harmonisation [ICH]). By contrast, this is not the case for many non-specialized external analysis programs, such as spreadsheets.

The power of this approach is illustrated by the validation of an assay method for acetaminophen based on the United States Pharmacopeia (USP) and in compliance with guidelines from ICH. (3)

To enable quick and easy creation of injection sequences, it is possible to use a software extension package with predefined eWorkflow templates based on ICH method validation guidelines. Here, the eWorkflow provides pre-populated injection lists with the options to tailor to user needs clearly highlighted.

The injection list was run twice on different days and by several analysts, with one analysis failing the precision test and the other passing it. Six different injection series were run with ±10% variations in temperature and flow rate to find the optimal parameters. Three different options were used to analyze the limits of detection and quantification: signal-to-noise ratio, standard deviation of the blank, and calibration curve.

After following the injection sequences, the next step was to manually adapt the data processing method for each workflow to meet the specific evaluation criteria, such as recovery range. Once this was completed, the data management system automatically generated a report showing the examined validation parameters and whether the method passed or failed—avoiding the tedious step of creating reports manually (Table I).

For other tests, such as linearity, results were reported graphically (Figure 3).

Significant time savings were achieved for a comprehensive method validation using the predefined workflows and templates of advanced LC software, compared with conventional validation processes in which every sequence is set up and run individually and analyzed manually.

Conclusion

LC methods in an analytical laboratory must be reviewed and updated regularly to ensure they are fit-for-purpose and remain up to date with relevant regulatory guidelines. MLCM is a strategy to ensure a laboratory’s long-term analytical methods perform as intended throughout its lifetime. A robust MLCM strategy requires analysts to invest considerable time upfront to fully understand how each LC parameter influences analysis and then review the method regularly, but conventional methods of completing these steps are time-consuming, inefficient, and error prone.

Advanced, automated LC technologies and software can reduce the time and resources required to carry out the multiple chromatographic runs needed to evaluate different parameters, making it possible to test various column particle sizes, eluent solutions, and column temperatures in parallel. Combining these automated features with intelligent data management systems can make MLCM easier and faster by using predefined, regulatory-compliant workflows and data processing templates. Together, these technologies will help analytical laboratories get new and modernized methods up and running faster, realizing the full efficiency benefits of advanced high-performance liquid chromatography.

References

1. Paul, C.; Fabel, S.; Squibb, A. A UHPLC Method Development System for Efficient Scouting of Chromatographic Elution Parameters. Thermo Fisher Scientific Technical Note 185. F. (2016).
2. Grübner, M. Transfer of a Compendial LC Method for Impurity Analysis of Chlorhexidine from a Waters Alliance HPLC System to a Vanquish Core HPLC system. Thermo Fisher Scientific Application Note 73309 (2021).
3. Grosse, S.; Quinn, S.; De Pra, M.; Steiner, F. Method Validation Based on ICH Guidelines of a USP Assay Method of Acetaminophen. Thermo Fisher Scientific Application Note 73374 (2020).

About the author

Jon Bardsley is market development manager, Pharma & BioPharma, at Thermo Fisher Scientific.