Selective high throughput protein quantification based on UV absorption spectra

The application of high throughput experimentation (HTE) in protein purification process development has created an analytical bottleneck. Recently, a new label‐free and non‐invasive methodology for analyzing multicomponent protein mixtures by means of spectral measurements was presented. Analytics based on the methodology was shown to increase analytical throughput for selective protein quantification significantly, however this was only demonstrated for one particular protein combination. In this work, the possibilities and limitations of the analytical method are investigated further. Principal component analysis (PCA) was performed on a broad range of absorption spectra to investigate their common characteristics and differences. The PCA was used both for cluster analysis and to define a measure for spectral similarity. For binary protein combinations, the calibration precision was shown to decrease exponentially with the defined spectral similarity factor. Knowledge of this correlation can be used to determine a priori whether a calibration will be successful or not. Calibration robustness was investigated by applying the analytics to liquid chromatography performed in HTE mode. Further it was shown, that a spectral difference of 0.6% was sufficient to sucessfully preform a spectral based calibration of two IgG1 monoclonals. Biotechnol. Bioeng. 2013; 110: 448–460. © 2012 Wiley Periodicals, Inc.     

Strategic assay deployment as a method for countering analytical bottlenecks in high throughput process development: Case studies in ion exchange chromatography

High throughput approaches to facilitate the development of chromatographic separations have now been adopted widely in the biopharmaceutical industry, but issues of how to reduce the associated analytical burden remain. For example, acquiring experimental data by high level factorial designs in 96 well plates can place a considerable strain upon assay capabilities, generating a bottleneck that limits significantly the speed of process characterization. This article proposes an approach designed to counter this challenge; Strategic Assay Deployment (SAD). In SAD, a set of available analytical methods is investigated to determine which set of techniques is the most appropriate to use and how best to deploy these to reduce the consumption of analytical resources while still enabling accurate and complete process characterization. The approach is demonstrated by investigating how salt concentration and pH affect the binding of green fluorescent protein from Escherichia coli homogenate to an anion exchange resin presented in a 96‐well filter plate format. Compared with the deployment of routinely used analytical methods alone, the application of SAD reduced both the total assay time and total assay material consumption by at least 40% and 5%, respectively. SAD has significant utility in accelerating bioprocess development activities. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012     

Application of simplex‐based experimental optimization to challenging bioprocess development problems: Case studies in downstream processing

The identification of feasible operating conditions during the early stages of bioprocess development is implemented frequently through High Throughput (HT) studies. These typically employ techniques based on regression analysis, such as Design of Experiments. In this work, an alternative approach, based on a previously developed variant of the Simplex algorithm, is compared to the conventional regression‐based method for three experimental systems involving polishing chromatography and protein refolding. This Simplex algorithm variant was found to be more effective in identifying superior operating conditions, and in fact it reached the global optimum in most cases involving multiple optima. By contrast, the regression‐based method often failed to reach the global optimum, and in many cases reached poor operating conditions. The Simplex‐based method is further shown to be robust in dealing with noisy experimental data, and requires fewer experiments than regression‐based methods to reach favorable operating conditions. The Simplex‐variant also lends itself to the use of HT analytical methods, when they are available, which can assist in avoiding analytical bottlenecks. It is suggested that this Simplex‐variant is ideally suited to rapid optimization in early‐phase process development. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:404–419, 2016     

Nonlinear state estimation as tool for online monitoring and adaptive feed in high throughput cultivations

Robotic facilities that can perform advanced cultivations (e.g., fed-batch or continuous) in high throughput have drastically increased the speed and reliability of the bioprocess development pipeline. Still, developing reliable analytical technologies, that can cope with the throughput of the cultivation system, has proven to be very challenging. On the one hand, the analytical accuracy suffers from the low sampling volumes, and on the other hand, the number of samples that must be treated rapidly is very large. These issues have been a major limitation for the implementation of feedback control methods in miniaturized bioreactor systems, where observations of the process states are typically obtained after the experiment has finished. In this work, we implement a Sigma-Point Kalman Filter in a high throughput platform with 24 parallel experiments at the mL-scale to demonstrate its viability and added value in high throughput experiments. The filter exploits the information generated by the ammonia-based pH control to enable the continuous estimation of the biomass concentration, a critical state to monitor the specific rates of production and consumption in the process. The objective in the selected case study is to ensure that the selected specific substrate consumption rate is tightly controlled throughout the complete Escherichia coli cultivations for recombinant production of an antibody fragment.     

High‐throughput ion exchange purification of positively charged recombinant protein in the presence of negatively charged dextran sulfate

Product quality analyses are critical for developing cell line and bioprocess producing therapeutic proteins with desired critical product quality attributes. To facilitate these analyses, a high‐throughput small‐scale protein purification (SSP) is required to quickly purify many samples in parallel. Here we develop an SSP using ion exchange resins to purify a positively charged recombinant growth factor P1 in the presence of negatively charged dextran sulfate supplemented to improve the cell culture performance. The major challenge in this work is that the strong ionic interaction between P1 and dextran sulfate disrupts interaction between P1 and chromatography resins. To solve this problem, we develop a two‐step SSP using Q Sepharose Fast Flow (QFF) and SP Sepharose XL (SPXL) resins to purify P1. The overall yield of this two‐step SSP is 78%. Moreover, the SSP does not affect the critical product quality attributes. The SSP was critical for developing the cell line and process producing P1. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:516–520, 2014     

Process analytics 4.0: A paradigm shift in rapid analytics for biologics development

Analytical testing of product quality attributes and process parameters during the biologics development (Process analytics) has been challenging due to the rapid growth of biomolecules with complex modalities to support unmet therapeutic needs. Thus, the expansion of the process analytics tool box for rapid analytics with the deployment of cutting-edge technologies and cyber-physical systems is a necessity. We introduce the term, Process Analytics 4.0; which entails not only technology aspects such as process analytical technology (PAT), assay automation, and high-throughput analytics, but also cyber-physical systems that enable data management, visualization, augmented reality, and internet of things (IoT) infrastructure for real time analytics in process development environment. This review is exclusively focused on dissecting high-level features of PAT, automation, and data management with some insights into the business aspects of implementing during process analytical testing in biologics process development. Significant technological and business advantages can be gained with the implementation of digitalization, automation, and real time testing. A systematic development and employment of PAT in process development workflows enable real time analytics for better process understanding, agility, and sustainability. Robotics and liquid handling workstations allow rapid assay and sample preparation automation to facilitate high-throughput testing of attributes and molecular properties which are otherwise challenging to monitor with PAT tools due to technological and business constraints. Cyber-physical systems for data management, visualization, and repository must be established as part of Process Analytics 4.0 framework. Furthermore, we review some of the challenges in implementing these technologies based on our expertise in process analytics for biopharmaceutical drug substance development.     

Simplex‐based optimization of numerical and categorical inputs in early bioprocess development: Case studies in HT chromatography

Bioprocess development studies often involve the investigation of numerical and categorical inputs via the adoption of Design of Experiments (DoE) techniques. An attractive alternative is the deployment of a grid compatible Simplex variant which has been shown to yield optima rapidly and consistently. In this work, the method is combined with dummy variables and it is deployed in three case studies wherein spaces are comprised of both categorical and numerical inputs, a situation intractable by traditional Simplex methods. The first study employs in silico data and lays out the dummy variable methodology. The latter two employ experimental data from chromatography based studies performed with the filter‐plate and miniature column High Throughput (HT) techniques. The solute of interest in the former case study was a monoclonal antibody whereas the latter dealt with the separation of a binary system of model proteins. The implemented approach prevented the stranding of the Simplex method at local optima, due to the arbitrary handling of the categorical inputs, and allowed for the concurrent optimization of numerical and categorical, multilevel and/or dichotomous, inputs. The deployment of the Simplex method, combined with dummy variables, was therefore entirely successful in identifying and characterizing global optima in all three case studies. The Simplex‐based method was further shown to be of equivalent efficiency to a DoE‐based approach, represented here by D‐Optimal designs. Such an approach failed, however, to both capture trends and identify optima, and led to poor operating conditions. It is suggested that the Simplex‐variant is suited to development activities involving numerical and categorical inputs in early bioprocess development.     

Microwell engineering characterization for mammalian cell culture process development

Experimentation in shaken microplate formats offers a potential platform technology for the rapid evaluation and optimization of cell culture conditions. Provided that cell growth and antibody production kinetics are comparable to those found in currently used shake flask systems then the microwell approach offers the possibility to obtain early process design data more cost effectively and with reduced material requirements. This work describes a detailed engineering characterization of liquid mixing and gas–liquid mass transfer in microwell systems and their impact on suspension cell cultures. For growth of murine hybridoma cells producing IgG1, 24‐well plates have been characterized in terms of energy dissipation (P/V) (via Computational Fluid Dynamics, CFD), fluid flow, mixing and oxygen transfer rate as a function of shaking frequency and liquid fill volume. Predicted k_La values varied between 1.3 and 29 h^?1; liquid‐phase mixing time, quantified using iodine decolorization experiments, varied from 1.7 s to 3.5 h; while the predicted P/V ranged from 5 to 35 W m^?3. CFD simulations of the shear rate predicted hydrodynamic forces will not be detrimental to cells. For hybridoma cultures however, high shaking speeds (>250 rpm) were shown to have a negative impact on cell growth, while a combination of low shaking speed and high well fill volume (120 rpm, 2,000 µL) resulted in oxygen limited conditions. Based on these findings a first engineering comparison of cell culture kinetics in microwell and shake flask formats was made at matched average energy dissipation rates. Cell growth kinetics and antibody titer were found to be similar in 24‐well microtiter plates and 250 mL shake flasks. Overall this work has demonstrated that cell culture performed in shaken microwell plates can provide data that is both reproducible and comparable to currently used shake flask systems while offering at least a 30‐fold decrease in scale of operation and material requirements. Linked with automation this provides a route towards the high throughput evaluation of robust cell lines under realistic suspension culture conditions. Biotechnol. Bioeng. 2010; 105: 260–275. © 2009 Wiley Periodicals, Inc.     

Product and contaminant measurement in bioprocess development by SELDI‐MS

Bioprocesses for therapeutic protein production typically require significant resources to be invested in their development. Underlying these efforts are analytical methods, which must be fit for the purpose of monitoring product and contaminants in the process. It is highly desirable, especially in early‐phase development when material and established analytical methods are limiting, to be able to determine what happens to the product and impurities at each process step with small sample volumes in a rapid and readily performed manner. This study evaluates the utility of surface‐enhanced laser desorption ionization mass spectroscopy (SELDI‐MS), known for its rapid analysis and minimal sample volumes, as an analytical process development tool. In‐process samples from an E. coli process for apolipoprotein A‐IM (ApoA‐IM) manufacture were used along with traditional analytical methods such as HPLC to check the SELDI‐MS results. ApoA‐IM is a naturally occurring variant of ApoA‐I that appears to confer protection against cardiovascular disease to those that carry the mutated gene. The results show that, unlike many other analytical methods, SELDI‐MS can handle early process samples that contain complex mixtures of biological molecules with limited sample pretreatment and thereby provide meaningful process‐relevant information. At present, this technique seems most suited to early‐phase development particularly when methods for traditional analytical approaches are still being established. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

High throughput monoclonal antibody generation by immunizing multiple antigens

Recognizing proteins via the production of highly specific monoclonal antibodies (mAbs) is crucial to identifying proteins for proteomic research. However, traditional mAb generation is time-consuming with low efficiency. In this study, we assessed the high throughput method of producing mAbs by immunizing mice with multiple antigens in order to obtain hybridomas against these multiple antigens in one cell fusion. We selected eight proteins that play important roles in human physiological or pathological processes. These proteins were mixed and simultaneously administered to one mouse. We observed the immunizing period for 10 d, and determined the effect of liquid medium and semi-solid medium in hybridoma generation. As a result, all eight immunogens induced antibodies in the immunized mouse in one cell fusion, we obtained hybridomas specific to all eight proteins by enzyme-linked immuno sorbent assay (ELISA) screening, hybridomas against five out of eight showed specific positive in Western-blotting assays. This indicates that we generated mAbs specific to eight proteins in one cell fusion, greatly increasing the efficiency of mAb generation. Furthermore, we observed that hybridomas selected from the liquid medium and semi-solid medium showed different reactivity to antigens. Our study established high-throughput and time-saving methods for production of mAbs. These results provide alternative approaches for increasing the efficacy of mAb generation.     

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.     

High throughput chromatography and analytics can inform viral clearance capabilities during downstream process development for biologics

High throughput process development (HTPD) using liquid handling robotics and RoboColumns is an established methodology in downstream process development to screen chromatography resins and optimize process designs to meet target product profiles. However, HTPD is not yet widely available for use in viral clearance capability of the resin due to a variety of constraints. In the present study, a BSL-1-compatible, non-infectious MVM model, MVM-VLP, was tested for viral clearance assessment with various resin and membrane chromatography operations in a HTPD mode. To detect the MVM-VLP in the high throughput experiments, an electrochemiluminescence immunoassay (ECLIA) assay was developed with up to 5 logs of dynamic range. Storage time suitability of MVM-VLP solutions in various buffer matrices, in the presence or absence of a glycoprotein vaccine candidate, were assessed. Then, MVM-VLP and a test article monoclonal antibody (mAb) were used in a HTPD design that included commercially available ion exchange media chemistries, elucidating a wide variety of viral clearance ability at different operating conditions. The methodologies described herein have the potential to be a part of the process design stage in biologics manufacturing process development, which in turn can reduce risk associated with viral clearance validation studies.     

Protein engineering of Acidovorax facilis 72W nitrilase for bioprocess development

Hydroxycarboxylic acid monomers can be used to prepare industrially important polymers. Enzymatic production of such hydroxycarboxylic acids is often preferred to chemical production since the reactions are run at ambient temperature, do not require strongly acidic or basic reaction conditions, and produce the desired product with high selectivity at high conversion. However, native enzymes often do not perform desired reactions with the efficiency required for commercial applications. Protein engineering was used to significantly increase the specific activity of nitrilase from Acidovorax facilis 72W for the conversion of 3-hydroxyvaleronitrile to 3-hydroxyvaleric acid. Overexpression of engineered nitrilase enzymes in Escherichia coli, combined with immobilization of whole cells in alginate beads that can be recycled many times has facilitated the development of a commercially viable bioprocess for production of 3-hydroxyvaleric acid.     

Using high throughput screening to define virus clearance by chromatography resins

High throughput screening (HTS) of chromatography resins can accelerate downstream process development by rapidly providing information on product and impurity partitioning over a wide range of experimental conditions. In addition to the removal of typical product and process‐related impurities, chromatography steps are also used to remove potential adventitious viral contaminants and non‐infectious retrovirus‐like particles expressed by rodent cell lines used for production. This article evaluates the feasibility of using HTS in a 96‐well batch‐binding format to study removal of the model retrovirus xenotropic murine leukemia virus (xMuLV) from product streams. Two resins were examined: the anion exchange resin Q Sepharose Fast Flow? (QSFF) and Capto adhere?, a mixed mode resin. QSFF batch‐binding HTS data was generated using two mAbs at various pHs, NaCl concentrations, and levels of impurities. Comparison of HTS data to that generated using the column format showed good agreement with respect to virus retentation at different pHs, NaCl concentrations and impurity levels. Results indicate that NaCl concentration and impurity level, but not pH, are key parameters that can impact xMuLV binding to both resins. Binding of xMuLV to Capto adhere appeared to tolerate higher levels of NaCl and impurity than QSFF, and showed some product‐specific impact on binding that was not observed with QSFF. Overall, the results demonstrate that the 96‐well batch‐binding HTS technique can be an effective tool for rapidly defining conditions for robust virus clearance on chromatographic resins. Biotechnol. Bioeng. 2013; 110: 1984–1994. © 2013 Wiley Periodicals, Inc.     

A high throughput mechanical screening device for cartilage tissue engineering

Articular cartilage enables efficient and near-frictionless load transmission, but suffers from poor inherent healing capacity. As such, cartilage tissue engineering strategies have focused on mimicking both compositional and mechanical properties of native tissue in order to provide effective repair materials for the treatment of damaged or degenerated joint surfaces. However, given the large number design parameters available (e.g. cell sources, scaffold designs, and growth factors), it is difficult to conduct combinatorial experiments of engineered cartilage. This is particularly exacerbated when mechanical properties are a primary outcome, given the long time required for testing of individual samples. High throughput screening is utilized widely in the pharmaceutical industry to rapidly and cost-effectively assess the effects of thousands of compounds for therapeutic discovery. Here we adapted this approach to develop a high throughput mechanical screening (HTMS) system capable of measuring the mechanical properties of up to 48 materials simultaneously. The HTMS device was validated by testing various biomaterials and engineered cartilage constructs and by comparing the HTMS results to those derived from conventional single sample compression tests. Further evaluation showed that the HTMS system was capable of distinguishing and identifying ‘hits’, or factors that influence the degree of tissue maturation. Future iterations of this device will focus on reducing data variability, increasing force sensitivity and range, as well as scaling-up to even larger (96-well) formats. This HTMS device provides a novel tool for cartilage tissue engineering, freeing experimental design from the limitations of mechanical testing throughput.