Computer-assisted UHPLC method development and optimization for the determination of albendazole and its related substances

Optimization of resolution as a simultaneous function of solvent composition, pH and temperature in reversed-phase liquid chromatography

BACKGROUND

The latest chromatographic retention models are capable of accurately describe the dependencies of retention over a wide range of experimental conditions. By using a suitable conversion, these models can be transformed into equations expressing the optimization criteria as function of multiples variables. Even though that theoretical models significantly reduce the experimental requirements for optimizations, these models have been barely used. Instead, most optimizations rely on empirical exploration of the relationships between criterions and variables. There is a need for a strategy to reduce the required number of experiments in multivariated optimization of separations, and Fundamental Models offer a clear opportunity for addressing it.

RESULTS

A Fundamental Model is used to give the simultaneous dependence of chromatographic retention of seven ionizable pesticides on the three variables: solvent composition, temperature and pH (w, T, pH). Based on few experiments, the 10 parameters required to predict the chromatographic retention of those compounds, taken as model analytes, can be obtained. Two mathematical treatments to convert retentions into resolutions between pairs are used: one considering extracolumn dispersions and other neglecting these contributions. Using the Overlapped Resolutions Maps, extended to four dimensions, two optimal conditions can be found for the two different mathematical conversions. Chromatographic conditions were empirically evaluated obtaining the best results for the optimization considering extracolumn dispersions, proving that this condition is a true optimal. It was demonstrated that any small shift in any of the variables from this true optimal leads to a loss in resolution.

SIGNIFICANCE

Fundamental Models describing chromatographic retention as a simultaneous function of multiple variables are nowadays very accurate. In this work is demonstrated that these models are useful not only to predict retentions, but also to optimize separations, even in the more challenging mode: isocratic, isothermal and iso-pH. However, the success in the optimization procedure depends also on the proper definition of the mathematical conversion of the Fundamental Models into optimization criteria.

Revisiting column selectivity choices in ultra-high performance liquid chromatography-Using multidimensional analytical Design Spaces to identify column equivalency

Current guides and column selection system (CSS) platforms can provide some helpful insights with regard to the selection of alternative phases. Their practical reliability however, can also turn out to be questionable, especially considering the lack of detailed specifics, such as a clear definition of points of equivalence-appropriate running conditions under which the given analytical mixture can be satisfactorily resolved on various stationary phases. In this context, the use of multivariate modeling tools can be highly beneficial. These tools, when applied systematically, are ideal for uniquely characterizing complex LC-separation systems, a fact supported by numerous peer-reviewed papers. Revisiting our earlier work [1] and the applied systematic workflow [2], we used a Design Space modeling software (DryLab), with the main focus on building and comparing 3-dimensional separation models of amlodipine and its related impurities to identify shared method conditions under which columns are conveniently interchangeable. Our study comprised 5, C18-modified ultra-high performance liquid chromatography (UHPLC) columns in total, in some cases with surprising results. We identified several equivalences between the Design Spaces (DSs) of markedly different columns. Conversely, there were cases where, despite the predicted similarities in column data, the modeled DSs demonstrated clear differences between the selected stationary phases.

Computer-assisted multifactorial method development for the streamlined separation and analysis of multicomponent mixtures in (Bio)pharmaceutical settings

The (bio)pharmaceutical industry is rapidly moving towards complex drug modalities that require a commensurate level of analytical enabling technologies that can be deployed at a fast pace. Unsystematic method development and unnecessary manual intervention remain a major barrier towards a more efficient deployment of meaningful analytical assay across emerging modalities. Digitalization and automation are key to streamline method development and enable rapid assay deployment. This review discusses the use of computer-assisted multifactorial chromatographic method development strategies for fast-paced downstream characterization and purification of biopharmaceuticals. Various chromatographic techniques such as reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), ion exchange chromatography (IEX), hydrophobic interaction chromatography (HIC), and supercritical fluid chromatography (SFC) are addressed and critically reviewed. The most significant parameters for retention mechanism modelling, as well as mapping the separation landscape for optimal chromatographic selectivity and resolution are also discussed. Furthermore, several computer-assisted approaches for optimization and development of chromatographic methods of therapeutics, including linear, nonlinear, and multifactorial modelling are outlined. Finally, the potential of the chromatographic modelling and computer-assisted optimization strategies are also illustrated, highlighting substantial productivity improvements, and cost savings while accelerating method development, deployment and transfer processes for therapeutic analysis in industrial settings.

Development and validation of stability indicating UPLC methods for related substances and assay analyses of ricobendazole hydrochloride

Ricobendazole hydrochloride is an active ingredient of a veterinary antiparasitic drug. The aim of this study was to investigate the degradation of ricobendazole hydrochloride under stress and stability testing conditions, for which we developed and validated the first stability indicating, specific, precise, accurate, and robust assay and related substances UPLC methods. The Acquity UPLC BEH C18 column was used for the related substances and assay analyses of ricobendazole hydrochloride, and the analyses were performed at 25 °C sample and 30 °C column temperatures with a 2 µL injection volume. In both methods, a mixture of water and methanol (60:40, v/v) was used as the diluent, mobile phase A was a phosphate buffer (50 mM potassium dihydrogen phosphate solution, pH 3.2 ± 0.05, adjusted with 10% o-phosphoric acid), and mobile phase B was a mixture of mobile phase A and acetonitrile (50:50, v/v). For the analysis of related substances, a gradient elution system was used at a flow rate of 0.4 mL/min for 35 min with a detection wavelength of 220 nm, while for the assay analysis; a gradient elution system was used at a flow rate of 0.3 mL/min for 15 min with a detection wavelength of 290 nm. The calibration curves showed excellent linearity with high R-squared (R2) values for each compound, ricobendazole (0.9998, 0.249 - 3.740 µg/mL), ricobendazole amine (0.9998, 0.255 - 3.819 µg/mL), albendazole (0.9998, 0.255 - 7.646 µg/mL), and albendazole sulfone (1.0000, 0.251 - 15.090 µg/mL) indicating a strong correlation between the concentrations of the compounds and their respective peak areas in the UPLC analysis. The method showed excellent accuracy with relative standard deviation values of less than 2.5%. The stress and photostability studies showed that ricobendazole hydrochloride was insensitive to daylight and UV radiation and showed significant degradation at elevated temperature (85 °C, 9 days) and under all hydrolysis and oxidation conditions. The major impurity was ricobendazole amine under thermal and hydrolysis conditions, while albendazole sulfone was the major oxidative impurity.

The Applicability of Chromatographic Retention Modeling on Chiral Stationary Phases in Reverse-Phase Mode: A Case Study for Ezetimibe and Its Impurities

Mechanistic modeling is useful for predicting and modulating selectivity even in early chromatographic method development. This approach is also in accordance with current analytical quality using design principles and is highly welcomed by the authorities. The aim of this study was to investigate the separation behavior of two different types of chiral stationary phases (CSPs) for the separation of ezetimibe and its related substances using the mechanistic retention modeling approach offered by the Drylab software (version 4.5) package. Based on the obtained results, both CSPs presented with chemoselectivity towards the impurities of ezetimibe. The cyclodextrin-based CSP displayed a higher separation capacity and was able to separate seven related substances from the active pharmaceutical ingredient, while the cellulose-based column enabled the baseline resolution of six impurities from ezetimibe. Generally, the accuracy of predicted retention times was lower for the polysaccharide CSP, which could indicate the presence of additional secondary interactions between the analytes and the CSP. It was also demonstrated that the combination of mechanistic modeling and an experimental design approach can be applied to method development on CSPs in reverse-phase mode. The applicability of the methods was tested on spiked artificial placebo samples, while intraday and long-term (2 years) method repeatability was also challenged through comparing the obtained retention times and resolution values. The results indicated the excellent robustness of the selected setpoints. Overall, our findings indicate that the chiral columns could offer orthogonal selectivity to traditional reverse-phase columns for the separation of structurally similar compounds.

Drilling into "Quality by Design" Approach for Analytical Methods

The need for consistency in analytical method development reinforces the dependence of pharmaceutical product development and manufacturing on robust analytical data. The Analytical Quality by Design (AQbD), akin to the product Quality by Design (QbD) endows a high degree of confidence to the method quality developed. AQbD involves the definition of the analytical target profile as starting point, followed by the identification of critical method variables and critical analytical attributes, supported on risk assessment and design of experiment tools for the establishment of a method operable design region and control strategy of the method. This systematic approach moves away from reactive troubleshooting to proactive failure reduction. The objective of this review is to highlight the elements of the AQbD framework and provide an overview of their implementation status in various analytical methods used in the pharmaceutical field. These methodologies include but are not limited to, high-performance liquid chromatography, UV-Vis spectrophotometry, capillary electrophoresis, supercritical fluid chromatography, and high-performance thin-layer chromatography. Finally, a critical appraisal is provided to highlight how regulators have encouraged AQbD principles application to boost the prevention of method failures and a better understanding of the method operable design region (MODR) and control strategy, ultimately resulting in cost-effectiveness and regulatory flexibility.

User-Driven Strategy for In Silico Screening of Reversed-Phase Liquid Chromatography Conditions for Known Pharmaceutical-Related Small Molecules

In the pharmaceutical field, and more precisely in quality control laboratories, robust liquid chromatographic methods are needed to separate and analyze mixtures of compounds. The development of such chromatographic methods for new mixtures can result in a long and tedious process even while using the design of experiments methodology. However, developments could be accelerated with the help of in silico screening. In this work, the usefulness of a strategy combining response surface methodology (RSM) followed by multicriteria decision analysis (MCDA) applied to predictions from a quantitative structure-retention relationship (QSRR) model is demonstrated. The developed strategy shows that selecting equations for the retention time prediction models based on the pKa of the compound allows flexibility in the models. The MCDA developed is shown to help to make decisions on different criteria while being robust to the user's decision on the weights for each criterion. This strategy is proposed for the screening phase of the method lifecycle. The strategy offers the possibility to the user to select chromatographic conditions based on multiple criteria without being too sensitive to the importance given to them. The conditions with the highest desirability are defined as the starting point for further optimization steps.

Analytical quality by design-compliant retention modeling for exploring column interchangeabilities in separating ezetimibe and its related substances

There are several potential advantages of using experimental design-based retention modeling for chromatographic method development. Most importantly, through the model-delivered systematic understanding (Design Spaces), users can benefit from increased method consistency, flexibility and robustness that can efficiently be achieved at lesser amount of development time. As a result, modeling tools have always been great supplementary assets and welcomed by both the pharmaceutical industry and the regulatory authorities. Most recently published chapters of ICH however - Q2(R2) and Q14 (both currently drafts) - evidence a further paradigm shift, specifying the elements of model-based development strategies in the so-called "enhanced approach". The main aim of this study was to investigate the impact of stationary phase chemistries on chromatographic method performance in the application example of ezetimibe and its related substances. A commercial modeling software package (DryLab®) was used to outline three-dimensional experimental design frameworks and acquire model Design Spaces (DSs) of 9 tested columns. This was done by performing 12 input calibration experiments per column, systematically changing critical method parameters (CMPs) as variables such as the gradient time (tG), temperature (T) and the ternary composition (tC) of the mobile phase. The constructed models allowed studying retention behaviors of selected analytes within each separation systems. In the first part of our work, we performed single optimizations for all nine stationary phases with substantially different surface modifications based on their highest achievable critical resolution values. For these optimum points in silico robustness testing was performed, clearly showing a change of CMPs, depending on the column, and specified optimum setpoint. In the second part of our work, we simultaneously compared the three-dimensional virtual separation models to identify all method parameter combinations that could provide at least baseline separation (R_{s, crit.}>1.50). These overlapping areas between the models described a common method operational design region (MODR) where columns were considered completely interchangeable - in terms of their baseline resolving capability - regardless of their exact physicochemical properties. A final optimized, column-independent working point within the common MODR was selected for verification. Indeed, experimental chromatograms showed excellent agreement with the model; all columns in the common condition were able to yield critical resolution values higher than 2.0, only their retentivity (elution window of peaks) was found different in some cases. Our results underline that a profound understanding of the separation process is of utmost importance andthat in some cases, adequate selectivity is achievable on various stationary phases.