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

Ferencz, Elek; Kelemen, Éva-Katalin; Obreja, Mona; Sipos, Eszter; Vida, Sára; Urkon, Melinda; Szabó, Zoltán‐István

doi:10.1016/j.jpba.2021.114203

Cited by 14 publications

(8 citation statements)

References 22 publications

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“…Consequently, adjustments to the calculations might be necessary to account for these aspects and improve accuracy. Nevertheless, the average error is acceptable and is comparable to ranges reported for RP-LC separations using the same model [7,10]. Noteworthy is that the elution order between prediction and verification was consistent, which is of higher priority for method optimizations.…”

Section: Input Runs Wp I Wp Ii Wp Iii Wp Iv Wp Vsupporting

confidence: 73%

“…The combination of three chromatographic factors is well-approved in the DryLab software. While in RP-LC, the combination of pH, tG, and T is commonly used [7,10,11], this set is not applicable in SFC due to the absence of a measurable pH. Thus, the terC/tG/T model is considered a suitable alternative model for SFC.…”

Section: Feasibility Experiment: Application To Diverse Peptidesmentioning

confidence: 99%

“…A modified LSSM [4] is used in recent software versions, such as the DryLab software [6], with the actual mathematical equations being proprietary information. Nowadays, the preparation of 3D models through simultaneous variation of three chromatographic parameters, such as pH or ternary composition (terC) in combination with gradient time (tG) and column temperature (T), is well established [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Retention modeling of therapeutic peptides in sub‐/supercritical fluid chromatography

Neumann,

Schmidtsdorff,

Schmidt

et al. 2024

Separation Science Plus

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Chromatographic modeling software packages are valuable tools during method optimization steps. These are well established for reversed‐phase applications utilizing retention time (RT) prediction to optimize separations and receive robust methods, which is of high interest for the analysis of pharmaceuticals. In contrast to liquid chromatography, the knowledge of RT prediction in supercritical fluid chromatography is limited to a manageable number of studies.This study uses the software DryLab to predict the RTs of the peptides bacitracin (Bac), colistin, tyrothricin (Tyro), and insulin analogs. Gradient time, column temperature, and the ternary composition (terC) of carbon dioxide, methanol (MeOH), and acetonitrile (ACN) in the gradient elution are varied in a feasibility approach using a neutral (Viridis BEH) and an amino‐derivatized aromatic (Torus 2‐PIC) stationary phase. In the second part, chromatographic optimization is performed in silico through gradient adjustments to optimize the separation of the fingerprint of Bac. The final gradient method utilizes a Viridis BEH column (100 × 3.0 mm, 1.7 μm), carbon dioxide, and a modifier consisting of ACN/MeOH/water/methanesulfonic acid (60:40:2:0.1, v:v:v:v). In addition, changes in the retention order of Tyro compounds with the proportion of the terC in combination with a Torus Diol column are investigated.

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Section: Input Runs Wp I Wp Ii Wp Iii Wp Iv Wp Vsupporting

confidence: 73%

Section: Feasibility Experiment: Application To Diverse Peptidesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Retention modeling of therapeutic peptides in sub‐/supercritical fluid chromatography

Neumann,

Schmidtsdorff,

Schmidt

et al. 2024

Separation Science Plus

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“…The independent variables, which included the mobile phase's pH (X2) and composition (X1), were examined for their impact on the dependent variable. Table 1 shows the independent factors used in the experiment [10]. The experimental design was developed for the separation process, the independent variables were the type of column used, the flow rate of the mobile phase, and the system's temperature.…”

Section: Optimization Of Analytical Conditionsmentioning

confidence: 99%

RP-HPLC method development and validation of Albendazole and its impurity

Saini,

Singh,

Vyas

et al. 2024

BIO Web Conf.

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Oxibendazole is a type of benzimidazole that is commonly used as an antiparasitic medication for both humans and animals. However, it is also a significant impurity found in albendazole, and it is crucial to follow the ICH Q3B criteria when analysing oxibendazole impurities. Therefore, it is recommended to use a simple, fast, sensitive, and precise RP-HPLC approach to identify oxibendazole impurities in bulk and pharmaceutical formulations of albendazole.To separate the oxibendazole impurity, acetonitrile and 10 nM potassium phosphate were used as a mobile phase. Orthophosphoric acid was used to accurately adjust the pH of the mobile phase to 2.03, ensuring optimal conditions. A nucleosil C18 column (250 x 4.6 mm, 5 µm) was used for the separation process, and it effectively provided the necessary separation. The gradient elution was set at a wavelength of 235 nm and a flow rate of 1 mL/min. The analytical technique was successfully designed and validated. The AQbD technique was used to optimize the analytical conditions for the suggested methodology, and the Design Expert 13® trial version was used for the central composite design optimization of analytical conditions. The procedure's linearity was verified using a regression coefficient of 0.999 within a working range of 0.5 to 3 μg/ml. Accuracy research showed results of 99.94–100.10% at 50, 100, and 150% levels of the working concentration. The oxibendazole impurity's average retention time was found to be 6.40 minutes, with a relative standard deviation of less than 2%, indicating high accuracy. The limits of detection (LOD) and quantification (LOQ) were found to be 0.073 and 0.091 μg/ml, respectively. Following the ICH Q2(R1) criteria, other validation criteria, such as robustness, were also evaluated. In conclusion, the proposed approach is suitable for analysing albendazole and oxibendazole in bulk and pharmaceutical formulations, making it ideal for detecting oxibendazole impurities.

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“…They generally offer good performances but they are limited to predicting the retention of compounds that have already been analyzed, therefore they do not completely resolve the issue of the experimental work for new unknown compounds. Several pieces of software enable the performing of these optimizations, among which DryLab™ (Molnar Institute, Berlin, Germany) is possibly the most well-known [ 13 , 14 ]. The development of a method for a new sample of known composition that has never been analyzed before generally requires models using a different approach known as quantitative structure–retention relationship (QSRR) models [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

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

Laethem

Kumari

Boulanger³

et al. 2022

Molecules

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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.

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

Cited by 14 publications

References 22 publications

Retention modeling of therapeutic peptides in sub‐/supercritical fluid chromatography

Retention modeling of therapeutic peptides in sub‐/supercritical fluid chromatography

RP-HPLC method development and validation of Albendazole and its impurity

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

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