Multifactor model for the optimization of selectivity in reversed-phase chromatography

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.

Chromatographic separations of aromatic carboxylic acids

The purpose of this review is to present methods of chromatographic analysis of aromatic carboxylic acids. The separation, identification and quantitative analysis of aromatic carboxylic acids are necessary because of their importance as non-steroid antiphlogistic drugs, semi-products of biosynthesis of aromatic amino-acids in plants (phenolic acids), metabolites of numerous toxic substances, drugs and catecholamines. HPLC separation of ionic samples tends to be more complicated than separation of non-ionic compounds. The review describes the dependence of the retention of ionic solutes on pH and solvent composition as well as on the ionic strength of a mobile phase. The application of the ion-suppressing RP-HPLC method using organic modifiers (aqueous buffer solutions) as eluents in aromatic carboxylic acid analysis is also presented. In more difficult cases of analysis the addition of an ion-pairing reagent, such as the quaternary alkylammonium ion, is necessary to obtain satisfactory separations. Hypotheses of ion-pair formation in reversed-phase systems as well as the influence of various agents on the separation of ionic solutes in IP-RP systems are explained. Examples of the application of ion-pair liquid chromatography to the analysis of aromatic carboxylic acids have also been reviewed. The principles and application of ion-exchange chromatography to the purification, isolation and less frequently, to chromatographic analysis are discussed. Polar adsorbents and polar bonded stationary phases are also widely used in carboxylic acid separation in normal-phase systems, mainly by TLC, often coupled with densitometry. The review also shows examples of separation of chiral benzoic acids and their derivatives in LC systems. The possibilities of application of gas chromatography preceded by derivatisation or pyrolysis of acidic compounds and applications of GC-MS and Py-GC-MS coupled methods in identification and quantitation of aromatic carboxylic acids is also reviewed.

Optimization of selectivity in high-performance liquid chromatography using desirability functions and mixture designs according to PRISMA

A computer program for the mobile phase optimization of high-performance liquid chromatography (HPLC) is described. The desirability function technique combined to the prisma mixture design was employed to enhance the quality of HPLC separations. The use of statistical models to predict the behaviour of retention times (tR) and band broadening at the different eluent compositions obtained by prisma was examined for dansyl amides and coumarins. The study showed that the dependence between the eluent composition and tR values of dansyl amides and coumarins can be expressed using quadratic regression models with a high degree of accuracy. Band broadening given by means of the band width at half-height (wh) was described by a linear regression model. Both models were used in calculating and predicting the resolution (Rs) in various solvent combinations. The desirability function converted the calculated (Rs) value into the desirability value (D), and the overall optimum was then defined by means of the overall desirability. The optimal eluent mixtures for the separation of compounds were easily read from the contour plot inside the horizontal plane of the prisma model. A good separation was achieved using the optimized solvent combination. Depending on the aims of the optimal separation, the program allows either optimization of critical pairs or achieving the overall optimum giving a reasonable separation for as many compounds as possible.

Half-fraction and full factorial designs versus central composite design for retention modelling in reversed-phase ion-pair liquid chromatography

In a previous paper (J. O. De Beer, C. V. Vandenbroucke and D. L. Massart, J. Pharm. Biomed. Anal., 12, (1994) 1379-1396) liquid chromatographic (LC) retention modelling of the cough-syrup compounds methyl para-hydroxybenzoate (MPHB) and propyl para-hydroxybenzoate (PPHB), phenylephrine hydrochloride (PE) and chlorphenamine maleate (CPM) was studied using a face-centred central composite design. It is examined whether smaller half-fractional and full factorial designs with fewer experiments tend to reliably predict retention times of the latter compounds as well. Simplified regression modelling, however, neglecting more first-order and interactive effects and disregarding pure second-order effects, has to be set up. These smaller designs finally satisfy the prediction of the retention of MPHB, PPHB and PE also. Retention prediction of CPM is much less accurate. CPM has a pKa value of 4.0, which is encompassed by the examined mobile phase pH limits 3.0 and 5.0. Since the largest retention shifts occur near the pKa value, retention prediction in this area becomes more complex. CPM retention modelling from a full factorial design is useful if the mobile phase pH is fixed at 5.0 for methanol as well as for acetonitrile as organic modifers. The full factorial design, applied with acetonitrile as organic modifer, enables the selection of suitable LC parameter combinations for fast and complete separation of the four compounds in cough-syrup analysis.