Mohammad Talebi

Review of recent advances in the preparation of organic polymer monoliths for liquid chromatography of large molecules.

In recent years the use of monolithic polymers in separation science has greatly increased due to the advantages these materials present over particle-based stationary phases, such as their relative ease of preparation and good permeability. For these reasons, these materials present high potential as stationary phases for the separation and purification of large molecules such as proteins, peptides, nucleic acids and cells. An example of this is the wide range of commercial available polymer-based monolithic columns now present in the market. This review summarizes recent developments in the synthesis of monolithic polymers for separation science, such as the incorporation of nanostructures in the polymeric scaffold as well as the preparation of hybrid structures. The different methods used in the surface functionalization of monolithic columns are also reviewed. Finally, we critically discuss the recent applications of this column technology in the separation of large molecules under different chromatographic mode.

Method development and validation for optimised separation of salicylic, acetyl salicylic and ascorbic acid in pharmaceutical formulations by hydrophilic interaction chromatography and response surface methodology

This paper introduces a design of experiments (DOE) approach for method optimisation in hydrophilic interaction chromatography (HILIC). An optimisation strategy for the separation of acetylsalicylic acid, its major impurity salicylic acid and ascorbic acid in pharmaceutical formulations by HILIC is presented, with the aid of response surface methodology (RSM) and Derringers desirability function. A Box-Behnken experimental design was used to build the mathematical models and then to choose the significant parameters for the optimisation by simultaneously taking both resolution and retention time as the responses. The refined model had a satisfactory coefficient (R²>0.92, n=27). The four independent variables studied simultaneously were: acetonitrile content of the mobile phase, pH and concentration of buffer and column temperature each at three levels. Of these, the concentration of buffer and its cross-product with pH had a significant, positive influence on all studied responses. For the test compounds, the best separation conditions were: acetonitrile/22 mM ammonium acetate, pH 4.4 (82:18, v/v) as the mobile phase and column temperature of 28°C. The methodology also captured the interaction between variables which enabled exploration of the retention mechanism involved. It would be inferred that the retention is governed by a compromise between hydrophilic partitioning and ionic interaction. The optimised method was further validated according to the ICH guidelines with respect to linearity and range, precision, accuracy, specificity and sensitivity. The robustness of the method was also determined and confirmed by overlying counter plots of responses which were derived from the experimental design utilised for method optimisation.

Charge heterogeneity profiling of monoclonal antibodies using low ionic strength ion-exchange chromatography and well-controlled pH gradients on monolithic columns

In this work, the suitability of employing shallow pH gradients generated using single component buffer systems as eluents through cation-exchange (CEX) monolithic columns is demonstrated for the high-resolution separation of monoclonal antibody (mAb) charge variants in three different biopharmaceuticals. A useful selection of small molecule buffer species is described that can be used within very narrow pH ranges (typically 1 pH unit) defined by their buffer capacity for producing controlled and smooth pH profiles when used together with porous polymer monoliths. Using very low ionic strength eluents also enabled direct coupling with electrospray ionisation mass spectrometry. The results obtained by the developed pH gradient approach for the separation of closely related antibody species appear to be consistent with those obtained by imaged capillary isoelectric focusing (iCE) in terms of both resolution and separation profile. Both determinants of resolution, i.e., peak compression and peak separation contribute to the gains in resolution, evidently through the Donnan potential effect, which is increased by decreasing the eluent concentration, and also through the way electrostatic charges are distributed on the protein surface. Retention mechanisms based on the trends observed in retention of proteins at pH values higher than the electrophoretic pI are also discussed using applicable theories. Employing monolithic ion-exchangers is shown to enable fast method development, short analysis time, and high sample throughput owing to the accelerated mass transport of the monolithic media. The possibility of short analysis time, typically less than 15 min, and high sample throughput is extremely useful in the assessment of charge-based changes to the mAb products, such as during manufacturing or storage.

Development and validation of a HPLC method for the determination of buprenorphine hydrochloride, naloxone hydrochloride and noroxymorphone in a tablet formulation

A simple isocratic reversed-phase high-performance liquid chromatographic method (RP-HPLC) was developed for the simultaneous determination of buprenorphine hydrochloride, naloxone hydrochloride dihydrate and its major impurity, noroxymorphone, in pharmaceutical tablets. The chromatographic separation was achieved with 10 mmol L(-1) potassium phosphate buffer adjusted to pH 6.0 with orthophosphoric acid and acetonitrile (17:83, v/v) as mobile phase, a C-18 column, Perfectsil Target ODS3 (150 mm x 4.6mm i.d., 5 microm) kept at 35 degrees C and UV detection at 210 nm. The compounds were eluted isocratically at a flow rate of 1.0 mL min(-1). The average retention times for naloxone, noroxymorphone and buprenorphine were 2.4, 3.8 and 8.1 min, respectively. The method was validated according to the ICH guidelines. The validation characteristics included accuracy, precision, linearity, range, specificity, limit of quantitation and robustness. The calibration curves were linear (r>0.996) over the concentration range 0.22-220 microg mL(-1) for buprenorphine hydrochloride and 0.1-100 microg mL(-1) for naloxone hydrochloride dihydrate and noroxymorphone. The recoveries for all three compounds were above 96%. No spectral or chromatographic interferences from the tablet excipients were found. This method is rapid and simple, does not require any sample preparation and is suitable for routine quality control analyses.

Performance comparison of partial least squares-related variable selection methods for quantitative structure retention relationships modelling of retention times in reversed-phase liquid chromatography

The relative performance of six multivariate data analysis methods derived from or combined with partial least squares (PLS) has been compared in the context of quantitative structure-retention relationships (QSRR). These methods include, GA (genetic algorithm)-PLS, Monte Carlo uninformative variable elimination (MC-UVE), competitive adaptive reweighted sampling (CARS), iteratively retaining informative variables (IRIV), variable iterative space shrinkage approach (VISSA) and PLS with automated backward selection of predictors (autoPLS). A set of 825 molecular descriptors was computed for 86 suspected sports doping compounds and used for predicting their gradient retention times in reversed-phase liquid chromatography (RPLC). The correlation between molecular descriptors selected by each technique and the retention time was established using the PLS method. All models derived from a selected subset of descriptors outperformed the reference PLS model derived from all descriptors, with very small demands of computational time and effort. A performance comparison indicated great diversity of these methods in selecting the most relevant molecular descriptors, ranging from 28 for CARS to 263 for MC-UVE. While VISSA provided the lowest degree of over-fitting for the training set, CARS demonstrated the best compromise between the prediction accuracy and the number of selected descriptors, with the prediction error of as low as 46s for the external test set. Only ten descriptors were found to be common for all models, with the characteristics of these descriptors being representative of the retention mechanism in RPLC.

Towards a chromatographic similarity index to establish localized quantitative structure-retention models for retention prediction: Use of retention factor ratio

Quantitative Structure-Retention Relationships (QSRR) have the potential to speed up the screening phase of chromatographic method development as the initial exploratory experiments are replaced by prediction of analyte retention based solely on the structure of the molecule. The present study offers further proof-of-concept of localized QSRR modelling, in which the retention of any given compound is predicted using only the most chromatographically similar compounds in the available dataset. To this end, each compound in the dataset was sequentially removed from the database and individually utilized as a test analyte. In this study, we propose the retention factor k as the most relevant chromatographic similarity measure and compare it with the Tanimoto index, the most popular similarity measure based on chemical structure. Prediction error was reduced by up to 8 fold when QSRR was based only on chromatographically similar compounds rather than using the entire dataset. The study therefore shows that the design of a practically useful structural similarity index should select the same compounds in the dataset as does the k-similarity filter in order to establish accurate predictive localized QSRR models. While low average prediction errors (Mean Absolute Error (MAE)<0.5min) and slopes of the regression lines through the origin close to 1.00 were obtained using k-similarity searching, the use of the structural Tanimoto similarity index, considered as the gold standard in Quantitative Structure-Activity Relationships (QSAR) studies, generally resulted in much higher prediction errors (MAE>1min) and significant deviations from the reference slope of 1.0. The Tanomoto similarity index therefore appears to have limited general utility in QSRR studies. Future studies therefore aim at designing a more appropriate chromatographic similarity index that can then be applied for unknown compounds (that is, compounds which have not been tested previously on the chromatographic system used, but for which the chemical structures are known).

Prediction of retention in hydrophilic interaction liquid chromatography using solute molecular descriptors based on chemical structures

Quantitative structure-retention relationship (QSRR) models are developed to predict the retention times of analytes on five hydrophilic interaction liquid chromatography (HILIC) stationary phases (bare silica, amine, amide, diol and zwitterionic), with a view to selecting the most suitable stationary phase(s) for the separation of these analytes. The study was conducted using six β-adrenergic agonists as target analytes. Molecular descriptors were calculated based only on chemical structures optimized using density functional theory. A genetic algorithm (GA) was then used to select the most relevant molecular descriptors and these were used to build a retention model for each stationary phase using partial least squares (PLS) regression. This model was then used to predict the retention of the test set of target analytes. This process created an optimized descriptor set which enhanced the reliability of the developed QSRR models. Finally, the QSRR models developed in the work were utilized to provide some insight into the separation mechanisms operating in the HILIC mode. Three performance criteria - mean absolute error (MAE), root mean square error of prediction scaled to retention time (RMSEP), and the number of selected descriptors, were used to evaluate the developed models when applied to an external test set of six β-adrenergic agonists and showed highly predictive abilities. MAE values ranged from 13 to 25s on four of the stationary phases, with a somewhat higher error (50s) being observed for the zwitterionic phase. RMSEP values of 4.88-11.12% were recorded. Validation was performed through Y-randomization and chemical domain applicability, from which it was evident that the developed optimized GA-PLS models were robust. The high levels of accuracy, reliability and applicability of the models were to a large extent due to the optimization of the GA descriptor set and the presence of relevant structural and geometric molecular descriptors, together with descriptors based on important physicochemical properties, which establish a strong connection between retention time and meaningful chemical properties. The present strategy, while it is a pilot study, holds great promise for broader screening of HILIC stationary phases for desired separation, as well as for acquisition of information about molecular mechanisms of separation under chromatographic conditions.

Rapid method development in hydrophilic interaction liquid chromatography for pharmaceutical analysis using a combination of quantitative structure-retention relationships and design of experiments

A design-of-experiment (DoE) model was developed, able to describe the retention times of a mixture of pharmaceutical compounds in hydrophilic interaction liquid chromatography (HILIC) under all possible combinations of acetonitrile content, salt concentration, and mobile-phase pH with R2 > 0.95. Further, a quantitative structure-retention relationship (QSRR) model was developed to predict retention times for new analytes, based only on their chemical structures, with a root-mean-square error of prediction (RMSEP) as low as 0.81%. A compound classification based on the concept of similarity was applied prior to QSRR modeling. Finally, we utilized a combined QSRR-DoE approach to propose an optimal design space in a quality-by-design (QbD) workflow to facilitate the HILIC method development. The mathematical QSRR-DoE model was shown to be highly predictive when applied to an independent test set of unseen compounds in unseen conditions with a RMSEP value of 5.83%. The QSRR-DoE computed retention time of pharmaceutical test analytes and subsequently calculated separation selectivity was used to optimize the chromatographic conditions for efficient separation of targets. A Monte Carlo simulation was performed to evaluate the risk of uncertainty in the models prediction, and to define the design space where the desired quality criterion was met. Experimental realization of peak selectivity between targets under the selected optimal working conditions confirmed the theoretical predictions. These results demonstrate how discovery of optimal conditions for the separation of new analytes can be accelerated by the use of appropriate theoretical tools.

3D printed titanium micro-bore columns containing polymer monoliths for reversed-phase liquid chromatography.

The potential of 3D selective laser melting (SLM) technology to produce compact, temperature and pressure stable titanium alloy chromatographic columns is explored. A micro bore channel (0.9 mm I.D. × 600 mm long) was produced within a 5 × 30 × 30 mm titanium alloy (Ti-6Al-4V) cuboid, in form of a double handed spiral. A poly(butyl methacrylate-co-ethyleneglycoldimethacrylate) (BuMA-co-EDMA) monolithic stationary phase was thermally polymerised within the channel for application in reversed-phase high-performance liquid chromatography. The prepared monolithic column was applied to the liquid chromatographic separation of intact proteins and peptides. Peak capacities of 69-76 (for 6-8 proteins respectively) were observed during isothermal separation of proteins at 44 °C which were further increased to 73-77 using a thermal step gradient with programmed temperature from 60 °C to 35 °C using an in-house built direct-contact heater/cooler platform based upon matching sized Peltier thermoelectric modules. Rapid temperature gradients were possible due to direct-contact between the planar metal column and the Peltier module, and the high thermal conductivity of the titanium column as compared to a similar stainless steel printed column. The separation of peptides released from a digestion of E.coli was also achieved in less than 35 min with ca. 40 distinguishable peaks at 210 nm.

Semiautomated pH gradient ion-exchange chromatography of monoclonal antibody charge variants

A new approach using a chromatography system equipped with isocratic pumps and an electrolytic eluent generator (EG) is introduced, replacing external pH gradient delivery using conventional gradient systems, in which bottled buffers with preadjusted pH are mixed using a gradient pump. The EG is capable of generating high purity base or acid required for online preparation of the buffer at the point of use, utilizing deionized water as the only carrier stream. Typically, the buffer was generated from online titration of a reagent composed of low molecular weight amines. The reagent was delivered isocratically into a static mixing tee, where it was titrated to the required pH with electrolytically generated base or acid. The required pH gradient was thus conveniently generated by electrically controlling the concentration of titrant. Also, since the pH was adjusted at the point of use, this approach offered enhanced throughput in terms of eluent preparation time and labor, and with a more reproducible pH profile. The performance of the system was demonstrated by running pH gradients ranging from pH 8.2 to 10.9 on a polymer monolith cation-exchange column for high throughput profiling of charge heterogeneity of intact, basic therapeutic monoclonal antibodies. A high degree of flexibility in modulating the key parameters of the pH gradient, including the buffer concentration, the pH gradient slope and the operating pH range was demonstrated. This enabled fine-tuning of the separation conditions for each individual antibody in order to enhance the chromatographic resolution.