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Adaption of Retention Models to Allow Optimisation of Peptide and Protein Separations


Patrik Petersson,1 Jette Munch,1 Melvin R Euerby,2 1. Novo Nordisk A/S, Måløv, Denmark.


2. Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK. 3. Advanced Chemistry Development (ACD/Labs), Toronto, Canada.


Andrey Vazhentsev,3 Michael McBrien,3 Sanjivanjit K. Bhal,3 and Karim Kassam3


While the current percentage of biopharmaceutical drugs approved and used as human medicine is small compared with small molecule drugs, EvaluatePharma® finds that ‘the percentage of sales from biotechnology products (bioengineered vaccines & biologics), within the world’s top 100, is set to increase from 39% in 2012 to 51% in 2018. In the broader market, sales from biotechnology products are expected to account for 25% of the world pharmaceutical market by 2018, versus the current share of 21% in 2012 [1]. Growing interest in biopharmaceuticals has led to proteins and peptides becoming analytes of increasing importance in the analytical laboratory.


The most commonly used analytical technique for the analysis of protein and peptide purity is reversed phase chromatography (RPC) in combination with UV detection and/or mass spectrometry. As the molecular weight of the protein increases, the selectivity of the RPC separation decreases. Consequently it becomes necessary to introduce complementary separation techniques, e.g., ion exchange chromatography (IEC) for larger proteins.


Retention modelling has been successfully used for the method development and optimisation of analytical scale separations of small molecules for 30 years [2-4] and several commercial software packages are available, for example DryLab, ACD/LC Simulator, ChromSword, and Osiris.


A common method development strategy involves a screening of columns and mobile phases that are known to generate large differences in selectivity. The most promising combination of column and mobile phase is then selected and a limited number of experiments conducted in order to build retention models. Subsequently, these models are applied to find an optimal temperature and gradient shape in silico and to assess method robustness.


An important advantage with retention modelling based on theoretical rather than statistical models (i.e., polynomial models based on factorial designs often referred to as DoE), is that a significantly smaller number of experiments are required to fit the models and, in addition, more advanced


predictions can be made. For example, it is possible to predict the appearance of an entire chromatogram rather than simply a numerical value which describes the quality of the separation.


When defining a method development strategy for peptides and proteins involving retention modelling of RPC and IEC it was, however, realised that existing commercial software programs were not capable of producing accurate predictions for peptides and proteins.


A literature search revealed that relevant models had been published that account for protein retention as a function of solvent strength [2-4] as well as temperature in various types of chromatography [5-8]. It appears, however, that these had not been implemented into commercial retention modelling software programs at the time this study was conducted in 2011.


As a collaborative effort, the authors set out to adapt and validate a commercially available software program (ACD/LC Simulator [9]) to accurately model retention and peak width of proteins and peptides in analytical scale reversed phase and ion exchange chromatography.


1.1. Solvent Strength Retention Models


As described by Snyder [1] the following isocratic relationships are required in order to account for isocratic retention of peptides and proteins:


ln k = a + b x (1) where k is the isocratic retention factor,


a and b are system and analyte specific constants and x the fraction of the strong solvent. Eqn. 1 is valid for reversed phase chromatography (RPC) and hydrophobic interaction chromatography (HIC). Often it is extended with a 2nd


for non-linearity. ln k = a + b x + c x2


(2)


In order to account for ion exchange chromatography (IEC) and hydrophilic interaction chromatography (HILIC) the following equation is needed.


ln k = d + e ln x (3)


where d and e are system and analyte specific constants and x the fraction of the strong solvent.


Peptides and proteins respond more strongly to changes in solvent strength than small molecules. The response increases with increasing molecular weight [10]. In order to develop selective and robust methods it is therefore commonplace to employ very shallow and long gradients. The development of such gradients without retention modelling is an iterative and time consuming task.


Based on the isocratic models described above it is possible to derive equations that account for retention during linear gradients [2-4]. Segmented gradients that are commonly used do, however, require numerical solutions where a large number of isocratic segments are combined to account for retention.


order term to account


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