Systematic interpolation method predicts protein chromatographic elution from batch isotherm data without a detailed mechanistic isotherm model

Predicting protein elution for overloaded ion exchange columns requires models capable of describing protein binding over broad ranges of protein and salt concentrations. Although approximate mechanistic models are available, they do not always have the accuracy needed for precise predictions. The aim of this work is to develop a method to predict protein chromatographic behavior from batch isotherm data without relying on a mechanistic model. The method uses a systematic empirical interpolation (EI) scheme coupled with a lumped kinetic model with rate parameters determined from HETP measurements for non‐binding conditions, to numerically predict the column behavior. For two experimental systems considered in this work, predictions based on the EI scheme are in excellent agreement with experimental elution profiles under highly overloaded conditions without using any adjustable parameters. A qualitative study of the sensitivity of predicting protein elution profiles to the precision, granularity, and extent of the batch adsorption data shows that the EI scheme is relatively insensitive to the properties of the dataset used, requiring only that the experimental ranges of protein and salt concentrations overlap those under which the protein actually elutes from the column and possess a ±10% measurement precision.     

Improved process analytical technology for protein a chromatography using predictive principal component analysis tools

Protein A chromatography is widely employed for the capture and purification of antibodies and Fc‐fusion proteins. Due to the high cost of protein A resins, there is a significant economic driving force for using these chromatographic materials for a large number of cycles. The maintenance of column performance over the resin lifetime is also a significant concern in large‐scale manufacturing. In this work, several statistical methods are employed to develop a novel principal component analysis (PCA)‐based tool for predicting protein A chromatographic column performance over time. A method is developed to carry out detection of column integrity failures before their occurrence without the need for a separate integrity test. In addition, analysis of various transitions in the chromatograms was also employed to develop PCA‐based models to predict both subtle and general trends in real‐time protein A column yield decay. The developed approach has significant potential for facilitating timely and improved decisions in large‐scale chromatographic operations in line with the process analytical technology (PAT) guidance from the Food and Drug Administration (FDA). Biotechnol. Bioeng. 2011; 108:59–68. © 2010 Wiley Periodicals, Inc.     

Large scale demonstration of a process analytical technology application in bioprocessing: Use of on‐line high performance liquid chromatography for making real time pooling decisions for process chromatography

Process Analytical Technology (PAT) has been gaining a lot of momentum in the biopharmaceutical community because of the potential for continuous real time quality assurance resulting in improved operational control and compliance. In previous publications, we have demonstrated feasibility of applications involving use of high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) for real‐time pooling of process chromatography column. In this article we follow a similar approach to perform lab studies and create a model for a chromatography step of a different modality (hydrophobic interaction chromatography). It is seen that the predictions of the model compare well to actual experimental data, demonstrating the usefulness of the approach across the different modes of chromatography. Also, use of online HPLC when the step is scaled up to pilot scale (a 2294 fold scale‐up from a 3.4 mL column in the lab to a 7.8 L column in the pilot plant) and eventually to manufacturing scale (a 45930 fold scale‐up from a 3.4 mL column in the lab to a 158 L column in the manufacturing plant) is examined. Overall, the results confirm that for the application under consideration, online‐HPLC offers a feasible approach for analysis that can facilitate real‐time decisions for column pooling based on product quality attributes. The observations demonstrate that the proposed analytical scheme allows us to meet two of the key goals that have been outlined for PAT, i.e., “variability is managed by the process” and “product quality attributes can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental, and other conditions”. The application presented here can be extended to other modes of process chromatography and/or HPLC analysis. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Ultra scale‐down approach to correct dispersive and retentive effects in small‐scale columns when predicting larger scale elution profiles

Ultra scale‐down approaches represent valuable methods for chromatography development work in the biopharmaceutical sector, but for them to be of value, scale‐down mimics must predict large‐scale process performance accurately. For example, one application of a scale‐down model involves using it to predict large‐scale elution profiles correctly with respect to the size of a product peak and its position in a chromatogram relative to contaminants. Predicting large‐scale profiles from data generated by small laboratory columns is complicated, however, by differences in dispersion and retention volumes between the two scales of operation. Correcting for these effects would improve the accuracy of the scale‐down models when predicting outputs such as eluate volumes at larger scale and thus enable the efficient design and operation of subsequent steps. This paper describes a novel ultra scale‐down approach which uses empirical correlations derived from conductivity changes during operation of laboratory and pilot columns to correct chromatographic profiles for the differences in dispersion and retention. The methodology was tested by using 1 mL column data to predict elution profiles of a chimeric monoclonal antibody obtained from Protein A chromatography columns at 3 mL laboratory‐ and 18.3 L pilot‐scale. The predictions were then verified experimentally. Results showed that the empirical corrections enabled accurate estimations of the characteristics of larger‐scale elution profiles. These data then provide the justification to adjust small‐scale conditions to achieve an eluate volume and product concentration which is consistent with that obtained at large‐scale and which can then be used for subsequent ultra scale‐down operations. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Systematic interpolation method predicts protein chromatographic elution with salt gradients,pH gradients and combined salt/pH gradients

A methodology is presented to predict protein elution behavior from an ion exchange column using both individual or combined pH and salt gradients based on high‐throughput batch isotherm data. The buffer compositions are first optimized to generate linear pH gradients from pH 5.5 to 7 with defined concentrations of sodium chloride. Next, high‐throughput batch isotherm data are collected for a monoclonal antibody on the cation exchange resin POROS XS over a range of protein concentrations, salt concentrations, and solution pH. Finally, a previously developed empirical interpolation (EI) method is extended to describe protein binding as a function of the protein and salt concentration and solution pH without using an explicit isotherm model. The interpolated isotherm data are then used with a lumped kinetic model to predict the protein elution behavior. Experimental results obtained for laboratory scale columns show excellent agreement with the predicted elution curves for both individual or combined pH and salt gradients at protein loads up to 45 mg/mL of column. Numerical studies show that the model predictions are robust as long as the isotherm data cover the range of mobile phase compositions where the protein actually elutes from the column.     

The Collection and Elution of Radioactive Fatty Acid Methyl Esters During Quantitative Gas-Liquid Chromatography

Abstract

An improved procedure is described for the collection and elution of low levels of radioactive fatty acid methyl esters separated by gas-liquid chromatography. A gas chromatographic effluent splitter was employed to partition fatty acid methyl ester samples in the column effluent, Condensation of a portion of the eluted fatty acids was accomplished in borosilicate glass tubing collectors maintained at ?70°C, Quantitation of nanomolar levels of fatty acid methyl esters was accomplished by calibrating the gas chromatographic flame ionization detectors with the splitters opened or closed. The elution of condensed radioactive fatty acid methyl esters from the glass collectors was complete when benzene followed by a toluene based scintillation fluid were employed as solvents. The method described may be applicable to the analysis of cis-trans isomers of unsaturated fatty acids.     

Structural quality of unrefined models in protein docking

Structural characterization of protein‐protein interactions is essential for understanding life processes at the molecular level. However, only a fraction of protein interactions have experimentally resolved structures. Thus, reliable computational methods for structural modeling of protein interactions (protein docking) are important for generating such structures and understanding the principles of protein recognition. Template‐based docking techniques that utilize structural similarity between target protein‐protein interaction and cocrystallized protein‐protein complexes (templates) are gaining popularity due to generally higher reliability than that of the template‐free docking. However, the template‐based approach lacks explicit penalties for intermolecular penetration, as opposed to the typical free docking where such penalty is inherent due to the shape complementarity paradigm. Thus, template‐based docking models are commonly assumed to require special treatment to remove large structural penetrations. In this study, we compared clashes in the template‐based and free docking of the same proteins, with crystallographically determined and modeled structures. The results show that for the less accurate protein models, free docking produces fewer clashes than the template‐based approach. However, contrary to the common expectation, in acceptable and better quality docking models of unbound crystallographically determined proteins, the clashes in the template‐based docking are comparable to those in the free docking, due to the overall higher quality of the template‐based docking predictions. This suggests that the free docking refinement protocols can in principle be applied to the template‐based docking predictions as well. Proteins 2016; 85:39–45. © 2016 Wiley Periodicals, Inc.     

Estimating chromatographic enantioselectivity (α) from gradient enantioselective chromatography data

Calculation of chromatographic enantioselectivity (α) is critically important in enantioselective chromatographic method development studies. The fact that α can only be calculated from isocratic elution conditions, whereas gradient elution conditions are predominantly used in method development screening, presents some problems for the use of α as a scoring indicator for automated, intelligent enantioselective chromatography method development systems. In this study, an empirical algorithm was developed to estimate α at isocratic conditions based upon information collected from a gradient elution. The algorithm was validated for SFC applications and has been shown to accurately predict enantioselectivity for a wide variety of racemic test analytes eluted on different chiral column and mobile phase conditions. Chirality, 2011. © 2010 Wiley‐Liss, Inc.     

Assessment of cisplatin reactivity with peptides and proteins using reverse-phase high-performance liquid chromatography and flameless atomic absorption spectroscopy

Methodology based on gradient elution reverse-phase high-performance liquid chromatography has been developed to permit monitoring of reactions of cisplatin, a noble metal-containing antineoplastic agent, with peptides, polypeptides, and proteins. Such reactions have been implicated in biotransformation of eisplatin. Specificity is provided by both the chromatographic column and the use of on-line uv and off-line atomic absorption spectroscopic detectors placed in series postcolumn. chromatographic conditions were optimized to maximize resolution of nitrogenous components. In some cases, however, resolution of platinum-containing components and those devoid of metal was not possible. This chromatographic overlap could be deconvoluted by sequentially monitoring the eluant with a uv detector (responsive to all proteinaceous material) and on atomic absorption spectrophotometer (specific for platinum detection). This technique has been applied to a kinetic investigation of cisplatin reactivity toward Met-enkephalin.     

Caprylic acid‐induced impurity precipitation from protein A capture column elution pool to enable a two‐chromatography‐step process for monoclonal antibody purification

This article presents the use of caprylic acid (CA) to precipitate impurities from the protein A capture column elution pool for the purification of monoclonal antibodies (mAbs) with the objective of developing a two chromatography step antibody purification process. A CA‐induced impurity precipitation in the protein A column elution pool was evaluated as an alternative method to polishing chromatography techniques for use in the purification of mAbs. Parameters including pH, CA concentrations, mixing time, mAb concentrations, buffer systems, and incubation temperatures were evaluated on their impacts on the impurity removal, high‐molecular weight (HMW) formation and precipitation step yield. Both pH and CA concentration, but not mAb concentrations and buffer systems, are key parameters that can affect host–cell proteins (HCPs) clearance, HMW species, and yield. CA precipitation removes HCPs and some HMW species to the acceptable levels under the optimal conditions. The CA precipitation process is robust at 15–25°C. For all five mAbs tested in this study, the optimal CA concentration range is 0.5–1.0%, while the pH range is from 5.0 to 6.0. A purification process using two chromatography steps (protein A capture column and ion exchange polishing column) in combination with CA‐based impurity precipitation step can be used as a robust downstream process for mAb molecules with a broad range of isoelectric points. Residual CA can be effectively removed by the subsequent polishing cation exchange chromatography. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1515–1525, 2015     

Adaptation to high throughput batch chromatography enhances multivariate screening

High throughput process development offers unique approaches to explore complex process design spaces with relatively low material consumption. Batch chromatography is one technique that can be used to screen chromatographic conditions in a 96‐well plate. Typical batch chromatography workflows examine variations in buffer conditions or comparison of multiple resins in a given process, as opposed to the assessment of protein loading conditions in combination with other factors. A modification to the batch chromatography paradigm is described here where experimental planning, programming, and a staggered loading approach increase the multivariate space that can be explored with a liquid handling system. The iterative batch chromatography (IBC) approach is described, which treats every well in a 96‐well plate as an individual experiment, wherein protein loading conditions can be varied alongside other factors such as wash and elution buffer conditions. As all of these factors are explored in the same experiment, the interactions between them are characterized and the number of follow‐up confirmatory experiments is reduced. This in turn improves statistical power and throughput. Two examples of the IBC method are shown and the impact of the load conditions are assessed in combination with the other factors explored.     

Immobilized metal affinity chromatography in open-loop simulated moving bed technology: Purification of a heat stable histidine tagged β-glucosidase

Open-loop simulated moving bed (SMB) has been used for immobilized metal affinity chromatographic (IMAC) purification of his-tagged β-glucosidase expressed in E. coli. A simplified approach based on an optimized single column protocol is used to design the open-loop SMB. A set of columns in the SMB represent one step in the chromatographic cycle i.e. there will be one set each of columns for load, wash, elution etc within the SMB. Only the wash and elution are operated with columns in sequence. The β-glucosidase was purified to almost single band purity with a purification factor of 15 and a recovery of 91%. SMB-performance showed reduced buffer consumption, higher purification fold, a better yield and higher productivity.     

THE CONTRIBUTION OF MATERNAL EFFECTS TO SELECTION RESPONSE: AN EMPIRICAL TEST OF COMPETING MODELS

Maternal effects can dramatically influence the evolutionary process, in some cases facilitating and in others hindering adaptive evolution. Maternal effects have been incorporated into quantitative genetic models using two theoretical frameworks: the variance‐components approach, which partitions variance into direct and maternal components, and the trait‐based approach, which assumes that maternal effects are mediated by specific maternal traits. Here, we demonstrate parallels between these models and test their ability to predict evolutionary change. First, we show that the two approaches predict equivalent responses to selection in the absence of maternal effects mediated by traits that are themselves maternally influenced. We also introduce a correction factor that may be applied when such cascading maternal effects are present. Second, we use several maternal effect models, as well as the standard breeder's equation, to predict evolution in response to artificial selection on flowering time in American bellflower, Campanulastrum americanum. Models that included maternal effects made much more accurate predictions of selection response than the breeder's equation. Maternal effect models differed somewhat in their fit, with a version of the trait‐based model providing the best fit. We recommend fitting such trait‐based models when possible and appropriate to make the most accurate evolutionary predictions.     

Optimization of affinity and ion-exchange chromatographic processes for the purification of proteins

This study documents several alternative approaches for the optimization of the ion-exchange and affinity chromatographic purification of proteins. In these approaches, the chromatographic process has been treated as a four-stage (adsorption, washing, elution, and regeneration) operation. Central to these investigations has been the elaboration of practical iterative procedures based on the use of theoretical models describing each of these stages. Predictions derived from these models have then been evaluated in terms of experimental data obtained using batch adsorption measurements in finite bath configurations and frontal breakthrough measurements with packed beds of different dimensions, containing nonporous and porous adsorbents of different selectivities and capacities for proteins. Commencing with the kinetic and distribution parameters derived from batch equilibrium measurements, the effect of the initial concentration of the target protein, the solid-liquid volume ratio, the superficial velocity and the column dimensions on the pressure drop, production rate, concentration profile, column utilization, and yield have been determined with packed beds. The potential of these iterative approaches to simplify the determination of key mass transfer and interaction parameters required for scale-up and economic optimization of chromatographic purifications of proteins has been examined using ion exchange, immobilized metal ion affinity, and triazine dye pseudo-affinity adsorbents of different selectivity and adsorption capacities. (c) 1996 John Wiley & Sons, Inc.     

High-performance liquid chromatography of proteins on deformed nonporous agarose beads. Affinity chromatography of dehydrogenases based on cibacron blue-derivatized agarose

Nonporous agarose beads, prepared by shrinkage and cross-linking in organic solvents, were derivatized with Cibacron Blue F3G-A. A compressed bed of these beads was used for purification of dehydrogenases (glucose-6-phosphate dehydrogenase, lactate dehydrogenase and alcohol dehydrogenase). The chromatographic conditions for the purification of glucose-6-phosphate dehydrogenase were optimized by varying the pH of the buffer; the concentrations of eluting agents, i.e. NADP (specific elution) and sodium chloride (nonspecific elution); flow rate; residence time of the protein on the column bed; and protein load. Specific elution with NADP (2 mM in 0.025 M Tris-HCl, pH 8.0) gave the highest recovery (140%) and highest purification factor (200-fold) of the enzyme. The ability of the compressed bed of nonporous agarose beads to tolerate high flow rates was essential, since the recovery of the enzyme activity increased with an increase in flow rate.     

High-Performance Liquid Chromatography of Proteins on Deformed Nonporous Agarose Beads. Affinity Chromatography of Dehydrogenases Based on Cibacron Blue-Derivatized Agarose

Nonporous agarose beads, prepared by shrinkage and cross-linking in organic solvents, were derivatized with Cibacron Blue F3G-A. A compressed bed of these beads was used for purification of dehydrogenases (glucose-6-phosphate dehydrogenase, lactate dehydrogenase and alcohol dehydrogenase). The chromatographic conditions for the purification of glucose-6-phosphate dehydrogenase were optimized by varying the pH of the buffer; the concentrations of eluting agents, i.e. NADP (specific elution) and sodium chloride (nonspecific elution); flow rate; residence time of the protein on the column bed; and protein load. Specific elution with NADP (2 mM in 0.025 M Tris-HCl, pH 8.0) gave the highest recovery (140%) and highest purification factor (200-fold) of the enzyme. The ability of the compressed bed of nonporous agarose beads to tolerate high flow rates was essential, since the recovery of the enzyme activity increased with an increase in flow rate.     

Model-based monitoring of industrial reversed phase chromatography to predict insulin variants

Downstream processing in the manufacturing biopharmaceutical industry is a multistep process separating the desired product from process- and product-related impurities. However, removing product-related impurities, such as product variants, without compromising the product yield or prolonging the process time due to extensive quality control analytics, remains a major challenge. Here, we show how mechanistic model-based monitoring, based on analytical quality control data, can predict product variants by modeling their chromatographic separation during product polishing with reversed phase chromatography. The system was described by a kinetic dispersive model with a modified Langmuir isotherm. Solely quality control analytical data on product and product variant concentrations were used to calibrate the model. This model-based monitoring approach was developed for an insulin purification process. Industrial materials were used in the separation of insulin and two insulin variants, one eluting at the product peak front and one eluting at the product peak tail. The model, fitted to analytical data, used one component to simulate each protein, or two components when a peak displayed a shoulder. This monitoring approach allowed the prediction of the elution patterns of insulin and both insulin variants. The results indicate the potential of using model-based monitoring in downstream polishing at industrial scale to take pooling decisions.     

Species–habitat associations and demographic rates of forest trees

Niche‐driven effects on demographic processes generated in response to habitat heterogeneity partly shape local distributions of species. Thus, tree distributions are commonly studied in relation to habitat conditions to understand how niche differentiation contributes to species coexistence in forest communities. Many such studies implicitly assume that local abundance reflects habitat suitability, and that abundance is relatively stable over time. We compared models based on abundance with those based on demographic performance for making inferences about habitat association for 287 tree species from three large dynamic plots located in tropical, subtropical and temperate forests. The correlation between the predictions of the abundance‐based models and the demography‐based models varied widely, with correlation coefficients ranging nearly from ?1 to 1.This suggests that the two types of models capture different information about species–habitat associations. Demography‐based models evaluate habitat quality by focusing on population processes and thus should be preferred for understanding responses of tree species to habitat conditions, especially when habitat conditions are changing and species–habitat interactions cannot be considered to be at equilibrium.     

Applicability of Chromatographic Co‐Elution for Antibiotic Target Identification

Identification of the molecular target is a crucial step in evaluating novel antibiotics. To support target identification, a label‐free method based on chromatographic co‐elution has previously been developed. Target identification by chromatographic coelution (TICC) exploits the alteration of the elution profile of target‐bound drug versus free drug in ion exchange (IEX) chromatography to identify potential target proteins from elution fractions. The applicability of TICC for antibiotic research is investigated by evaluating which proteins, that is, putative targets, can be monitored in Bacillus subtilis. Coelution of components of known protein complexes provides a read‐out for how well the native state of proteins is conserved during chromatography. Rifampicin, which targets RNA polymerase, is used in a proof‐of‐concept study.