Alexander T. Hanke

Purifying biopharmaceuticals: knowledge-based chromatographic process development

The purification of biopharmaceuticals is commonly considered the bottleneck of the manufacturing process. Increasing product diversity, along with growing regulatory and economic constraints raise the need to adopt new rational, systematic, and generally applicable process development strategies. Liquid chromatography is the key step in most purification processes and a well-understood unit operation, yet this understanding is still rarely effectively utilized during process development. Knowledge of the composition of the mixture, the molecular properties of the solutes and how they interact with the resins are required to rationalise the design choices. Here, we provide an overview of the advances in the determination and measurement of these properties and interactions, and outline their use throughout the different stages of downstream process development.

Analytical characterization of complex, biotechnological feedstocks by pH gradient ion exchange chromatography for purification process development.

The accelerating growth of the market for proteins and the growing interest in new, more complex molecules are bringing new challenges to the downstream process development of these proteins. This results in a demand for faster, more cost efficient, and highly understood downstream processes. Screening procedures based on high-throughput methods are widely applied nowadays to develop purification processes for proteins. However, screening highly complex biotechnological feedstocks, such as complete cell lysates containing target proteins often expressed with a low titre, is still very challenging. In this work we demonstrate a multidimensional, analytical screening approach based on pH gradient ion exchange chromatography (IEC), gel electrophoresis and protein identification via mass spectrometry to rationally characterize a biotechnological feedstock for the purpose of purification process development. With this very simple characterization strategy a two-step purification based on consecutive IEC operations was rapidly laid out for the purification of a diagnostic protein from a cell lysate reaching a purity of ∼80%. The target protein was recombinantly produced using an insect cell expression system.

Mapping of Enzyme Kinetics on a Microfluidic Device

A microfluidic platform or “microfluidic mapper” is demonstrated, which in a single experiment performs 36 parallel biochemical reactions with 36 different combinations of two reagents in stepwise concentration gradients. The volume used in each individual reaction was 36 nl. With the microfluidic mapper, we obtained a 3D enzyme reaction plot of horseradish peroxidase (HRP) with Amplex Red (AR) and hydrogen peroxide (H2O2), for concentration ranges of 11.7 μM to 100.0 μM and 11.1 μM to 66.7 μM for AR and H2O2, respectively. This system and methodology could be used as a fast analytical tool to evaluate various chemical and biochemical reactions especially where two or more reagents interact with each other. The generation of dual concentration gradients in the present format has many advantages such as parallelization of reactions in a nanoliter-scale volume and the real-time monitoring of processes leading to quick concentration gradients. The microfluidic mapper could be applied to various problems in analytical chemistry such as revealing of binding kinetics, and optimization of reaction kinetics.

Prediction of protein retention times in hydrophobic interaction chromatography by robust statistical characterization of their atomic‐level surface properties

The correlation between the dimensionless retention times (DRT) of proteins in hydrophobic interaction chromatography (HIC) and their surface properties were investigated. A ternary atomic‐level hydrophobicity scale was used to calculate the distribution of local average hydrophobicity across the proteins surfaces. These distributions were characterized by robust descriptive statistics to reduce their sensitivity to small changes in the three‐dimensional structure. The applicability of these statistics for the prediction of protein retention behaviour was looked into. A linear combination of robust statistics describing the central tendency, heterogeneity and frequency of highly hydrophobic clusters was found to have a good predictive capability (R2 = 0.78), when combined a factor to account for protein size differences. The achieved error of prediction was 35% lower than for a similar model based on a description of the protein surface on an amino acid level. This indicates that a robust and mathematically simple model based on an atomic description of the protein surface can be used for the prediction of the retention behaviour of conformationally stable globular proteins with a well determined 3D structure in HIC.

Fourier transform assisted deconvolution of skewed peaks in complex multi-dimensional chromatograms

Lower order peak moments of individual peaks in heavily fused peak clusters can be determined by fitting peak models to the experimental data. The success of such an approach depends on two main aspects: the generation of meaningful initial estimates on the number and position of the peaks, and the choice of a suitable peak model. For the detection of meaningful peaks in multi-dimensional chromatograms, a fast data scanning algorithm was combined with prior resolution enhancement through the reduction of column and system broadening effects with the help of two-dimensional fast Fourier transforms. To capture the shape of skewed peaks in multi-dimensional chromatograms a formalism for the accurate calculation of exponentially modified Gaussian peaks, one of the most popular models for skewed peaks, was extended for direct fitting of two-dimensional data. The method is demonstrated to successfully identify and deconvolute peaks hidden in strongly fused peak clusters. Incorporation of automatic analysis and reporting of the statistics of the fitted peak parameters and calculated properties allows to easily identify in which regions of the chromatograms additional resolution is required for robust quantification.

3D-liquid chromatography as a complex mixture characterization tool for knowledge-based downstream process development.

Knowledge‐based development of chromatographic separation processes requires efficient techniques to determine the physicochemical properties of the product and the impurities to be removed. These characterization techniques are usually divided into approaches that determine molecular properties, such as charge, hydrophobicity and size, or molecular interactions with auxiliary materials, commonly in the form of adsorption isotherms. In this study we demonstrate the application of a three‐dimensional liquid chromatography approach to a clarified cell homogenate containing a therapeutic enzyme. Each separation dimension determines a molecular property relevant to the chromatographic behavior of each component. Matching of the peaks across the different separation dimensions and against a high‐resolution reference chromatogram allows to assign the determined parameters to pseudo‐components, allowing to determine the most promising technique for the removal of each impurity. More detailed process design using mechanistic models requires isotherm parameters. For this purpose, the second dimension consists of multiple linear gradient separations on columns in a high‐throughput screening compatible format, that allow regression of isotherm parameters with an average standard error of 8%.

A microfluidic chip with a staircase pH gradient generator, a packed column and a fraction collector for chromatofocusing of proteins

A microfluidic device for pH gradient chromatofocusing is presented, which performs creation of a micro‐column, pH gradient generation, and fraction collection in a single device. Using a sieve micro‐valve, anion exchange particles were packed into a microchannel in order to realize a solid‐phase absorption column. To fractionate proteins according to their isoelectric points, elution buffer solutions with a stepwise pH gradient were prepared in 16 parallel mixing reactors and flowed through the micro‐column, wherein a protein mixture was previously loaded. The volume of the column is only 20 nL, hence it allows extremely low sample consumption and fast analysis compared with a conventional system. We demonstrated separation of two proteins, albumin–fluorescein isothiocyanate conjugate (FITC‐BSA) and R‐Phycoerythrin (R‐PE), by using a microcolumn of commercial charged polymeric particles (Source 15Q). The microfluidic device can be used as a rapid diagnostic tool to analyse crude mixtures of proteins or nucleic acids and determine adsorption/desorption characteristics of various biochemical products, which can be helpful for scientific fundamental understanding as well as instrumental in various industrial applications, especially in early stage screening and process development.

Chromatographic parameter determination for complex biological feedstocks

The application of mechanistic models for chromatography requires accurate model parameters. Especially for complex feedstocks such as a clarified cell harvest, this can still be an obstacle limiting the use of mechanistic models. Another commonly encountered obstacle is a limited amount of sample material and time to determine all needed parameters. Therefore, this study aimed at implementing an approach on a robotic liquid handling system that starts directly with a complex feedstock containing a monoclonal antibody. The approach was tested by comparing independent experimental data sets with predictions generated by the mechanistic model using all parameters determined in this study. An excellent agreement between prediction and experimental data was found verifying the approach. Thus, it can be concluded that RoboColumns with a bed volume of 200 μL can well be used to determine isotherm parameters for predictions of larger scale columns. Overall, this approach offers a new way to determine crucial model input parameters for mechanistic modelling of chromatography for complex biological feedstocks.