The goal of this study was to evaluate the accuracy of simulated robustness testing using commercial mod- elling software (DryLab) and state-of-the-art stationary phases. For this purpose, a mixture of amlodipine and its seven related impurities was analyzed on short narrow bore columns (50 × 2.1 mm, packed with sub-2  m particles) providing short analysis times. The performance of commercial modelling software for robustness testing was systematically compared to experimental measurements and DoE based pre- dictions. We have demonstrated that the reliability of predictions was good, since the predicted retention times and resolutions were in good agreement with the experimental ones at the edges of the design space. In average, the retention time relative errors were <1.0%, while the predicted critical resolution errors were comprised between 6.9 and 17.2%. Because the simulated robustness testing requires signif- icantly less experimental work than the DoE based predictions, we think that robustness could now be investigated in the early stage of method development.

Moreover, the column interchangeability, which is also an important part of robustness testing, was investigated considering five different C8 and C18 columns packed with sub-2  m particles. Again, thanks to modelling software, we proved that the separation was feasible on all columns within the same analysis time (less than 4 min), by proper adjustments of variables.

In this contribution, the possibility to automatically transfer RPLC methods between different column dimensions and instruments was evaluated using commercial modelling software. The method transfer reliability was tested with loratadine and its 7 related pharmacopeial impurities. In this study, state- of-the-art columns packed with superficially porous particles of 5, 2.6, 1.7 and 1.3 µm particles were exclusively employed. A fast baseline separation of loratadine and related impurities (Rs,min = 2.49) was achieved under the best analytical conditions (i.e. column of 50 mm × 2.1 mm, 1.3 µm, 10–90% ACN in 5 min, T = 40 ◦ C, pH = 3, F = 0.5 ml/min). This optimal method was successfully tested on columns packed with other particle sizes, namely 1.7 and 2.6 µm, to reduce pressure drop. The selectivities and retentions remained identical, while the peak widths were logically wider, leading to a reduction of peak capacity from 203 to 181 and 159 on the 1.3, 1.7 and 2.6 µm particles, respectively. On the minimum, the reso- lution was equal to 1.54 on the 50 mm × 2.1 mm, 2.6 µm stationary phase. Next to this, the method was transferred to columns of different lengths, inner diameters and particle sizes (100 mm × 3 mm, 2.6 m or 150 mm × 4.6 mm, 5 µm). These columns were used on other LC instruments possessing larger dwell volumes. The modelling software employed for developing the original method was able to calculate the new gradient conditions to be used. The accuracy of prediction was excellent, as the average retention time errors between predicted and observed chromatograms were −0.11% and 0.45% when transferring the method to 100 mm × 3 mm and 150 mm × 4.6 mm columns, respectively. This work proves the use- fulness and validity of HPLC modelling software for transferring methods between different instruments, column dimensions and/or flow rates. 
 

Highlights:

• Innovative QbD-based approach for robustness testing of a compendial HPLC method.
• A Design Space was constructed to study the robustness in silico.
• Required peak resolution of 2.0 could not be reached in all experiments.
• After adjusting the gradient time the requirements were fulfilled.
• A separate “Eluent Design Space” study was performed.

This study describes the development of liquid chromatographic methods for the simultaneous separation of some of the most popular local anesthetics in pharmaceutical preparations and medical praxis (benzocaine, bupivacaine, chloroprocaine lidocaine, oxybuprocaine, prilocaine, procaine, propipocaine and tetracaine) based on a systematic approach using experimental design methodology in which one or more factors are changed at the same time. The strategy employs a chromatography modeling software for the simultaneous optimization of critical chromatographic parameters, which are gradient time tG, temperature T and the ternary composition of the organic eluent B.

DryLab is one of the most established software for chromatography modeling, which allows for modeling of chromatographic separations based on input data from two or more experimental runs. The use of DryLab for HPLC modeling to facilitate methods development was well documented in the last 27 years. In this time a continuous development occurred to the software which enabled it to cope more with the ongoing technological progress. On the other hand, a number of published studies exist that deal with the use of DryLab in different chromatographic modes and wide application ranges. DryLab is applied to solve different analytical problems in pharmaceutical analysis, which deal mostly with the separation of active pharmaceutical ingredients (APIs) in the presence of their impurities and/or their degradation products. In the field of phytochemical analysis many applications on complex plant extracts are also available. Moreover, DryLab has been successfully applied to optimize the separation of different groups of environmental pollutants, peptides and proteins and metabolites.

Highlights:

• Implementation of organic solvent gradients in micellar liquid chromatography, MLC.
• Screening of β-blockers in urine samples with direct injection in gradient MLC.
• 1-Propanol gradients allows the elution of β-blockers of diverse polarity.
• Gradient elution starting with pure micellar solution benefits direct injection.
• Optimisation of organic solvent gradients in MLC can be performed with DryLab®.