Chromatography focus on


Chromatography Modelling in High Performance Liquid Chromatography Method Development


by Imre Molnár, Hans-Jürgen Rieger, Institute for Applied Chromatography, Berlin, Germany Róbert Kormány, Egis Pharmaceutical, Budapest, Hungary


This article discusses the development of chromatography modelling of the last 30 years from the first software package for calculating resolution and capacity factors to the visual modelling of chromatograms for testing peak movements with altering elution conditions.


Different approaches are discussed, such as retention modelling based on measurements, others based on molecular structure or on statistical considerations. The state-of-the-art will be demonstrated with a few applications of industrial importance.


Introduction


Computer supported chromatography method development [1,2,3] started around 1985 as IBM released the so called IBM PC, the first ’Personal Computer‘. The members of the project were Lloyd Snyder, John Dolan, Tom Jupille, founders of LCResources on the US West Coast and myself, who, after returning from Csaba Horváth’s Lab at Yale University founded the Institute for Applied Chromatography, located in Berlin-Kreuzberg on the 1st October 1981. The 4 of us decided to use the new technology of IBM-computers to write a program for HPLC method development. Jack Kirkland, a pioneer of HPLC at DuPont measured different properties on 1000 columns, and with Lloyd Snyder calculated the influence of the pore structure and ligand length in order to model band spreading. This was the beginning of ’DryLab‘, a name which Lloyd Snyder suggested for the software.


In 1988, the first iteration of the DryLab software was developed and allowed the modelling of band spreading, during optimisation of isocratic %B in DryLab I (I=isocratic) [4]. In 1989 modelling of gradient elution DryLab G (G=gradient) was developed [5]. First chromatograms for visualisation were plotted with *-characters. A few months later we were able to plot chromatograms for every change in experimental conditions. In the following years the software was further improved to isocratic multiparameter software, called ’DryLab Imp‘, where the user could model changes in pH, temperature, ionic strength, ternary eluent composition and ion-pair-chromatography. Gradient elution was more difficult to model with other factors, therefore the so called 2-dimensional modelling with gradient time (tG) and temperature (T) the (“tG-T-model”) was developed. At the same time a number of other factors, like column length, ID, particle size (dp), flow rate, dwell volume, gradient %Bstart and %Bend, and up to 10 gradient steps could be calculated. With these features DryLab was already in the 1990’s a multifactorial chromatography modelling software. The major feature of these models was their simplicity and visuality [6].


A very informative book on computer assisted method development was published in 1990 by Glajch and Snyder with 42 contributions to the theory and praxis of HPLC modelling [1] illustrating the work of leaders of the chromatographic scientific community working on separation predictions.


Some years later Sergej Galushko started his project, which he first named ’ChromDream’ which was later renamed ’ChromSword‘. The software allowed the prediction of retention time based on a compounds molecular structure which is important for those working in drug design [7,8]. To run the experiments he later introduced ’AutoChromSword‘ software which collected runs overnight in an automated fashion.


Other companies also introduced similar software packages. Agilent developed ICOS (intelligent computer optimization software) [9]. In France ’Osiris‘ was developed by the group of Heinisch, Rocca and Tschapla [10]. In Canada Mike McBrian introduced an optimisation software for chromatography with ACDLabs (Advanced Chromatography Development) [11]. During this time programs like ’Diamond’ and ’PESOS’ came and went. Around 2005 the company S-Matrix introduced “Fusion”, software which controlled Waters instruments to generate experiments and evaluate them according to statistical principles. This list is not complete and there were other software packages developed during this time, but these are beyond the scope of this article.


Theory of RPC Modelling


Retention phenomena of reversed-phase chromatography (RPC) are described in many ways by different authors. The philosophy used in DryLab is described in the ’Solvophobic Theory‘ of Csaba Horváth, which was developed in the years 1975-1977 at Yale [12]. The fundamental concept of this theory is that retention in RPC is enforced by water, as the retarding component of the eluent. The uptake (dissolution) of nonpolar molecules in the water structure requires large amounts of energy.


The retention factor k (also called the ’capacity factor‘) is proportional to the energy needed in this process. In the case of dibenzanthracene on a C8-phase, we find the following values for the capacity factor:


k in water k in acetonitrile


kw = 4000 kAN = 1


Horváth and his team found that the only possible explanation for this extremely wide scale of retention times is the change in the surface tension of water altered by the addition of acetonitrile (AN) or methanol (MeOH). The strong lipophobicity of water can easily and continuously be reduced in this way, which is what occurs in gradient elution. Thus a typical approach to method development in RPC is to initially run a scouting gradient on a C18 column, which will typically resolves more than 95% of all compound peaks present in the sample.


Gradient elution typically starts with water or water-rich eluents. Upon injecting the sample into such a mobile phase (eluent), the water mixes with the hydrophobic sample components and forces them onto the surface of the C8 or C18 column packings. The capacity factors of organic molecules in water (Kw) are 103-106 times higher than in acetonitrile or methanol. By increasing the amount of the organic eluent, the retention force from water will become weaker, the surface tension of the eluent is reduced from 72 dyn/cm in water to approximately 22 dyn/cm at room temperature with a reduction in retention time occurring at the same time. This process has tremendous capabilities for separating complex mixtures in a highly reproducible manner for simultaneous qualitative and quantitative analysis.


In gradient elution, we can calculate the retention precisely for every component. Based on only two gradient runs, we can further calculate isocratic conditions and see how the k-values are reduced with increasing %B (percent organic) in the mobile phase.


The amazing ease of Reversed-Phase gradient elution is exhibited in the continuous reduction of the retention force of water by the increasing amount of the organic eluent (MeOH or AN). Fine differences in accessible solvophobic molecular surface areas, consisting of C-C, C-H and other nonpolar atomic bonds, combined with steps in the gradient, are sufficient to achieve reasonably good separations with almost any mixture in life science applications.


Modelling of Reversed-Phase separations is based on the measurement of both the retention time and the peak area [13,14]. The calculation of sample positions in the corresponding chromatograms in a Design of Experiments (DoE) enables the chromatographer to look at a small number of experiments in a virtual mode and generate a fast overview of separation choices. However by running a DoE, e.g. a tG-T model with 4 runs, we must realise that each chromatogram will look different. This however is the purpose of the exercise, as we want to learn how peaks move, so we can establish a model and can derive solutions for separation problems.


Experimental conditions


Column selection should be done carefully. We have a great number of RP-columns on the market. Snyder, Dolan, Carr, Engelhardt, Euerby, Tanaka and Petersson among others published excellent papers on column selectivity [15, 16] including more than 500 columns and demonstrated how to select the best columns for a separation. We used a YMC C18 120Å column, 150 x 4.6 mm, 5 µm (Waters, Milford, MA, USA) with a synthetic sample mixture developed for column testing at a flow rate of 2.0 mL/min. A Shimadzu Prominence (Shimadzu Europe, Duisburg, Germany) LC with dwell volume Vd: 0.4 mL and UV detection at 254 nm was used throughout the work. Modelling software was DryLab®


4, v.4.0.10.15. (Molnar-Institute,


Berlin, Germany). Eluent A was 0.025 M phosphate buffer at pH 2.8. Eluent B1 was acetonitrile (AN) Eluent B2 was methanol (MeOH) and a 50:50-mix of B1:B2. Gradient times were 20 and 60 min from 5 to 95% (B1+B2) at T1: 30 and T2: 60°C.


INTERNATIONAL LABMATE - APRIL 2013


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68