Use of computational fluid dynamics as a tool for establishing process design space for mixing in a bioreactor

Validation of a CFD model for cell culture bioreactors at large scale and its application in scale-up

Among all the operating parameters that control the cell culture environment inside bioreactors, appropriate mixing and aeration are crucial to ensure sufficient oxygen supply, homogeneous mixing, and CO2 stripping. A model-based manufacturing facility fit approach was applied to define agitation and bottom air flow rates during the process scale-up from laboratory to manufacturing, of which computational fluid dynamics (CFD) was the core modeling tool. The realizable k-ε turbulent dispersed Eulerian gas-liquid flow model was established and validated using experimental values for the volumetric oxygen transfer coefficient (kLa). Model validation defined the process operating parameter ranges for application of the model, identified mixing issues (e.g., impeller flooding, dissolved oxygen gradients, etc.) and the impact of antifoam on kLa. Using the CFD simulation results as inputs to the models for oxygen demand, gas entrance velocity, and CO2 stripping aided in the design of the agitation and bottom air flow rates needed to meet cellular oxygen demand, control CO2 levels, mitigate risks for cell damage due to shear, foaming, as well as fire hazards due to high O2 levels in the bioreactor gas outlet. The recommended operating conditions led to the completion of five manufacturing runs with a 100% success rate. This model-based approach achieved a seamless scale-up and reduced the required number of at-scale development batches, resulting in cost and time savings of a cell culture commercialization process.

Analyzing of hydrodynamic stress and mass transfer requirements of a fermentation process carried out in a coaxial bioreactor: a scale-up study

Fluid hydrodynamic stress has a deterministic effect on the morphology of filamentous fungi. Although the coaxial mixer has been recognized as a suitable gas dispersion system for minimizing inhomogeneities within a bioreactor, its performance for achieving enhanced oxygen transfer while operating at a reduced shear environment has not been investigated yet, specifically upon scale-up. Therefore, the influence of the impeller type, aeration rate, and central impeller retrofitting on the efficacy of an abiotic coaxial system containing a shear-thinning fluid was examined. The aim was to assess the hydrodynamic parameters, including stress, mass transfer, bubble size, and gas hold-up, upon conducting a scale-up study. The investigation was conducted through dynamic gassing-in, tomography, and computational fluid dynamics combined with population balance methods. It was observed that the coaxial bioreactor performance was strongly influenced by the agitator type. In addition, coaxial bioreactors are scalable in terms of shear environment and oxygen transfer rate.

Shear stress as a driver of degradation for protein-based therapeutics: More accomplice than culprit

Protein degradation is a major concern for protein-based therapeutics. It may alter the biological activity of the product and raise the potential for undesirable effects on the patients. Among the numerous drivers of protein degradation, shear stress has been the focus around which much work has revolved since the 1970s. In the pharmaceutical realm, the product is often processed through several unit operations, which include mixing, pumping, filtration, filling, and atomization. Nonetheless, the drug might be exposed to significant shear stresses, which might cooperatively contribute to product degradation, together with interfacial stress. This review presents fundamentals of shear stress about protein structure, followed by an overview of the drivers of product degradation. The impact of shear stress on protein stability in different unit operations is then presented, and recommendations for limiting the adverse effects on the biopharmaceutical formulations are outlined. Finally, several devices used to explore the effects of shear stress are discussed.

Modeling multiphase fluid flow, mass transfer, and chemical reactions in bioreactors using large-eddy simulation

We present a transient large eddy simulation (LES) modeling approach for simulating the interlinked physics describing free surface hydrodynamics, multiphase mixing, reaction kinetics, and mass transport in bioreactor systems. Presented case-studies include non-reacting and reacting bioreactor systems, modeled through the inclusion of uniform reaction rates and more complex biochemical reactions described using Contois type kinetics. It is shown that the presence of reactions can result in a non-uniform spatially varying species concentration field, the magnitude and extent of which is directly related to the reaction rates and the underlying variations in the local volumetric mass transfer coefficient.

Investigation of the Role of Impeller Structural Parameters on Liquid-Liquid Mixing Characteristics in Stirred Tanks

Liquid-liquid mixings in stirred tanks are commonly found in many industries. In this study, we performed computational fluid dynamics (CFD) modeling and simulation to investigate the liquid-liquid mixing behavior. Furthermore, the population balance model (PBM) was used to characterize the droplet size distribution. The PBM model parameters were calibrated using the experimental data of droplet sizes at different agitation speeds. Additionally, we employed the steady-state Sauter mean droplet size to validate the developed CFD-PBM coupled model at different dispersion phase holdups. Then, the validated CFD-PBM coupled model was employed to evaluate the role of impeller structural parameters on the liquid-liquid mixing efficiency based on a user-defined mixing index. It was found that the position of impellers significantly affects the mixing efficiency, and an increase in stirring speed and the number of impellers improved the mixing efficiency.

Analysis of hollow wall effect on the fluid dynamics in the orbitally shaken bioreactors

Orbitally shaking bioreactors (OSRs) have recently been increasingly applied in the biopharmaceutical industry because they can provide a suitable environment for mammalian cell growth and protein expression. Fluid dynamics information is crucial for analyzing or optimizing of different types of bioreactors. Considering that the structure has an important influence on the fluid dynamics in a bioreactor, it necessary to design or optimize its structure by the computational fluid dynamics (CFD) approach. The aim of this study is to optimize the wall structure of a hollow cylinder OSR proposed in our previous work. Based on previous research, the influences of the hollow wall of the OSR on fluid dynamics and the volumetric mass transfer coefficient ([Formula: see text]) were analysed by the established CFD model. The results showed that the mixing performance of OSR could be improved by decreasing the installation height of the hollow wall. An installation height of 30 mm was found to be most favourable for mixing. The reliability of the CFD model was verified by comparing the liquid wave height and liquid wave shape between the simulation and experiment. The shear stress in the hollow cylinder OSR was proven gentle for mammalian cell cultivation.

Numerical and Experimental Investigation of the Hydrodynamics in the Single-Use Bioreactor Mobius® CellReady 3 L

Two-way Euler-Lagrange simulations are performed to characterize the hydrodynamics in the single-use bioreactor Mobius^® CellReady 3 L. The hydrodynamics in stirred tank bioreactors are frequently modeled with the Euler–Euler approach, which cannot capture the trajectories of single bubbles. The present study employs the two-way coupled Euler–Lagrange approach, which accounts for the individual bubble trajectories through Langrangian equations and considers their impact on the Eulerian liquid phase equations. Hydrodynamic process characteristics that are relevant for cell cultivation including the oxygen mass transfer coefficient, the mixing time, and the hydrodynamic stress are evaluated for different working volumes, sparger types, impeller speeds, and sparging rates. A microporous sparger and an open pipe sparger are considered where bubbles of different sizes are generated, which has a pronounced impact on the bubble dispersion and the volumetric oxygen mass transfer coefficient. It is found that only the microporous sparger provides sufficiently high oxygen transfer to support typical suspended mammalian cell lines. The simulated mixing time and the volumetric oxygen mass transfer coefficient are successfully validated with experimental results. Due to the small reactor size, mixing times are below 25 s across all tested conditions. For the highest sparging rate of 100 mL min−1, the mixing time is found to be two seconds shorter than for a sparging rate of 50 mL min−1, which again, is 0.1 s longer than for a sparging rate of 10 mL min−1 at the same impeller speed of 100 rpm and the working volume of 1.7 L. The hydrodynamic stress in this bioreactor is found to be below critical levels for all investigated impeller speeds of up to 150 rpm, where the maximum levels are found in the region where the bubbles pass behind the impeller blades.

Parametric numerical study and optimization of mass transfer and bubble size distribution in a gas-liquid stirred tank bioreactor equipped with Rushton turbine using computational fluid dynamics

Designing and optimizing a bioreactor can be an especially challenging process. Computational modelling is an effective tool to investigate the effects of various operating parameters on bioreactor performance and identify the optimum ones. In this work, a computational fluid dynamics-population balance model (CFD-PBM) was developed to elucidate the effect of different geometrical and operating parameters on the hydrodynamics and mass transfer coefficient of a batch stirred tank bioreactor. The validated model was projected to predict the effect of different parameters including the gas flow rate, the impeller off-bottom clearance, the number of agitator blades, and rotational speed of the impeller on the velocity profiles, air volume fraction, bubble size distribution, and the local gas mass transfer coefficient (K l a) in the bioreactor. Air bubble breakup and coalescence phenomena were considered in all simulations. Factorial experimental design approach was employed to statistically investigate the impacts of the aforementioned operating and geometrical parameters on K l a and bubble size distribution in the bioreactor in order to determine the most significant parameters. This can give an essential insight into the most impactful factors when it comes to designing and scaling up a bioreactor.

Towards in silico Process Modeling for Vaccines

Chemical, manufacturing, and control development timelines occupy a significant part of vaccine end-to-end development. In the on-going race for accelerating timelines, in silico process development constitutes a viable strategy that can be achieved through an artificial intelligence (AI)-driven or a mechanistically oriented approach. In this opinion, we focus on the mechanistic option and report on the modeling competencies required to achieve it. By inspecting the most frequent vaccine process units, we identify fluid mechanics, thermodynamics and transport phenomena, intracellular modeling, hybrid modeling and data science, and model-based design of experiments as the pillars for vaccine development. In addition, we craft a generic pathway for accommodating the modeling competencies into an in silico process development strategy.

High-Throughput Process Development: I-Process Chromatography

Chromatographic separation serves as "a workhorse" for downstream process development and plays a key role in the removal of product-related, host-cell-related, and process-related impurities. Complex and poorly characterized raw materials and feed material, low feed concentration, product instability, and poor mechanistic understanding of the processes are some of the critical challenges that are faced during the development of a chromatographic step. Traditional process development is performed as a trial-and-error-based evaluation and often leads to a suboptimal process. A high-throughput process development (HTPD) platform involves the integration of miniaturization, automation, and parallelization and provides a systematic approach for time- and resource-efficient chromatographic process development. Creation of such platforms requires the integration of mechanistic knowledge of the process with various statistical tools for data analysis. The relevance of such a platform is high in view of the constraints with respect to time and resources that the biopharma industry faces today.This protocol describes the steps involved in performing the HTPD of chromatography steps. It describes the operation of a commercially available device (PreDictor™ plates from GE Healthcare). This device is available in 96-well format with 2 or 6 μL well size. We also discuss the challenges that one faces when performing such experiments as well as possible solutions to alleviate them. Besides describing the operation of the device, the protocol also presents an approach for statistical analysis of the data that are gathered from such a platform. A case study involving the use of the protocol for examining ion exchange chromatography of the Granulocyte Colony Stimulating Factor (GCSF), a therapeutic product, is briefly discussed. This is intended to demonstrate the usefulness of this protocol in generating data that are representative of the data obtained at the traditional lab scale. The agreement in the data is indeed very significant (regression coefficient 0.93). We think that this protocol will be of significant value to those involved in performing the high-throughput process development of the chromatography process.

High-Throughput Process Development: II-Membrane Chromatography

Membrane chromatography is gradually emerging as an alternative to conventional column chromatography. It alleviates some of the major disadvantages associated with the latter, including high-pressure drop across the column bed and dependence on intraparticle diffusion for the transport of solute molecules to their binding sites within the pores of separation media. In the last decade, it has emerged as a method of choice for final polishing of biopharmaceuticals, in particular, monoclonal antibody products. The relevance of such a platform is high in view of the constraints with respect to time and resources that the biopharma industry faces today.This protocol describes the steps involved in performing HTPD of a membrane chromatography step. It describes the operation of a commercially available device (AcroPrep™ Advance filter plate with Mustang S membrane from Pall Corporation). This device is available in 96-well format with a 7 μL membrane in each well. We will discuss the challenges that one faces when performing such experiments as well as possible solutions to alleviate them. Besides describing the operation of the device, the protocol also presents an approach for statistical analysis of the data that are gathered from such a platform. A case study involving the use of the protocol for examining ion-exchange chromatography of the Granulocyte Colony Stimulating Factor (GCSF), a therapeutic product, is briefly discussed. This is intended to demonstrate the usefulness of this protocol in generating data that are representative of the data obtained at the traditional lab scale. The agreement in the data is indeed very significant (regression coefficient 0.9866). We think that this protocol will be of significant value to those involved in performing high-throughput process development of membrane chromatography.

Beyond heuristics: CFD-based novel multiparameter scale-up for geometrically disparate bioreactors demonstrated at industrial 2kL-10kL scales

The timely delivery of the most up-to-date medicines and drug products is essential for patients throughout the world. Successful scaling of the bioreactors used within the biopharmaceutical industry plays a large part in the quality and time to market of these products. Scale and topology differences between vessels add a large degree of complication and uncertainty within the scaling process. Currently, this approach is primarily achieved through extensive experimentation and facile empirical correlations, which can be costly and time consuming while providing limited information. The work undertaken in the current study demonstrates a more robust and complete approach using computational fluid dynamics (CFD) to provide potent multiparameter scalability, which only requires geometric and material properties before a comprehensive and detailed solution can be generated. The CFD model output parameters that can be applied in the scale-up include mass transfer rates, mixing times, shear rates, gas hold-up values, and bubble residence times. The authors examined three bioreactors with variable geometries and were able to validate them based on single-phase and multiphase experiments. Furthermore, leveraging the resulting CFD output information enabled the authors to successfully scale-up from a known 2kL to a novel and disparate 5kL single-use bioreactor in the first attempted cell culture. This multiparameter scaling approach promises to ultimately lead to a reduction in the time to market providing patients with earlier access to the most groundbreaking medicines.

Using CFD simulations and statistical analysis to correlate oxygen mass transfer coefficient to both geometrical parameters and operating conditions in a stirred-tank bioreactor

Optimization of a bioreactor design can be an especially challenging process. For instance, testing different bioreactor vessel geometries and different impeller and sparger types, locations, and dimensions can lead to an exceedingly large number of configurations and necessary experiments. Computational fluid dynamics (CFD), therefore, has been widely used to model multiphase flow in stirred-tank bioreactors to minimize the number of optimization experiments. In this study, a multiphase CFD model with population balance equations are used to model gas-liquid mixing, as well as gas bubble distribution, in a 50 L single-use bioreactor vessel. The vessel is the larger chamber in an early prototype of a multichamber bioreactor for mammalian cell culture. The model results are validated with oxygen mass transfer coefficient (k_L a) measurements within the prototype. The validated model is projected to predict the effect of using ring or pipe spargers of different sizes and the effect of varying the impeller diameter on k_L a. The simulations show that ring spargers result in a superior k_L a compared to pipe spargers, with an optimum sparger-to-impeller diameter ratio of 0.8. In addition, larger impellers are shown to improve k_L a. A correlation of k_L a is presented as a function of both the reactor geometry (i.e., sparger-to-impeller diameter ratio and impeller-to-vessel diameter ratio) and operating conditions (i.e., Reynolds number and gas flow rate). The resulting correlation can be used to predict k_L a in a bioreactor and to optimize its design, geometry, and operating conditions.

Optimization of microbial cell disruption using pressurized CO2 for improving lipid recovery from wet biomass

Microbial cell disruption using pressurized gases (e.g., CO₂) is a promising approach to improve the lipid recovery from wet oleaginous microorganisms by eliminating the energy-intensive drying required for conventional methods. In this study, we perform cell disruption of Rhodotorula glutinis using pressurized CH₄, N₂, and Ar where we find the efficacy of these gases on cell viability is minimal. Since CO₂ is found to be the only viable gas for microbial cell disruption among these four gases, we use a combination of Box-Behnken design and response surface methodology (RSM) to find the optimal cell disruption by tuning different parameters such as pressure (P), temperature (T), exposure time (t), and agitation (a). From RSM, we find 6 log reduction of viable cells at optimized conditions, which corresponds to more than 99% cell death at P = 4000 kPa, T = 296.5 K, t = 360 min, and a = 325 rpm. Furthermore, from the scanning electron microscope (SEM), we find a complete morphological change in the cell structure when treated with pressurized CO₂ compared to the untreated cells. Finally, we find that up to 85% of total lipid can be recovered using optimized pressurized CO₂ from wet biomass compared to the untreated wet cells where up to 73% lipid can be recovered.

Analyzing the suitability of a baffled orbitally shaken bioreactor for cells cultivation using the computational fluid dynamics approach

Orbitally shaken bioreactors (OSRs) is one of important bioreactors for mammalian cells cultivation in suspension, especially for the screening of valuable microorganisms and in basic bioprocess development experiments. However, the suitability of OSRs for cells culture in large scale is still under development. In this article, a new kind of OSRs with baffle structure was proposed and a three-dimensional CFD model was established to analyze the influence of baffle structure on the flow field. Lower installation height of baffles was found suitable for improving the mixing efficiency. Compared to the unbaffled OSR, the baffled OSR could enhance the level of oxygen transfer largely but the oxygen transfer rate was independent on the baffle installation height. Moreover, as the baffle installation height increased, the energy transferred for liquid motion was decreased. Finally, the shear stress of the baffled OSRs proposed was gentle for mammalian cells growth. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2746, 2019.

Characterizing the fluid dynamics in the flow fields of cylindrical orbitally shaken bioreactors with different geometry sizes

Orbitally shaken bioreactors (OSRs) are commonly used for the cultivation of mammalian cells in suspension. To aid the geometry designing and optimizing of OSRs, we conducted a three-dimensional computational fluid dynamics (CFD) simulation to characterize the flow fields in a 10 L cylindrical OSR with different vessel diameters. The liquid wave shape captured by a camera experimentally validated the CFD models established for the cylindrical OSR. The geometry size effect on volumetric mass transfer coefficient (k_La) and hydromechanical stress was analyzed by varying the ratio of vessel diameter (d) to liquid height at static (h _L), d/h _L. The highest value of k_La about 30 h^-1 was observed in the cylindrical vessel with the d/h _L of 6.35. Moreover, the magnitudes of shear stress and energy dissipation rate in all the vessels tested were below their minimum values causing cells damage separately, which indicated that the hydromechanical-stress environment in OSRs is suitable for cells cultivation in suspension. Finally, the CFD results suggested that the d/h _L higher than 8.80 should not be adopted for the 10 L cylindrical OSR at the shaking speed of 180 rpm because the "out of phase" state probably will happen there.

Transforming nanomedicine manufacturing toward Quality by Design and microfluidics

Nanopharmaceuticals aim at translating the unique features of nano-scale materials into therapeutic products and consequently their development relies critically on the progression in manufacturing technology to allow scalable processes complying with process economy and quality assurance. The relatively high failure rate in translational nanopharmaceutical research and development, with respect to new products on the market, is at least partly due to immature bottom-up manufacturing development and resulting sub-optimal control of quality attributes in nanopharmaceuticals. Recently, quality-oriented manufacturing of pharmaceuticals has undergone an unprecedented change toward process and product development interaction. In this context, Quality by Design (QbD) aims to integrate product and process development resulting in an increased number of product applications to regulatory agencies and stronger proprietary defense strategies of process-based products. Although QbD can be applied to essentially any production approach, microfluidic production offers particular opportunities for QbD-based manufacturing of nanopharmaceuticals. Microfluidics provides unique design flexibility, process control and parameter predictability, and also offers ample opportunities for modular production setups, allowing process feedback for continuously operating production and process control. The present review aims at outlining emerging opportunities in the synergistic implementation of QbD strategies and microfluidic production in contemporary development and manufacturing of nanopharmaceuticals. In doing so, aspects of design and development, but also technology management, are reviewed, as is the strategic role of these tools for aligning nanopharmaceutical innovation, development, and advanced industrialization in the broader pharmaceutical field.

Application of CFD in Bioprocessing: Separation of mammalian cells using disc stack centrifuge during production of biotherapeutics

Centrifugation continues to be one of the most commonly used unit operations for achieving efficient harvest of the product from the mammalian cell culture broth during production of therapeutic monoclonal antibodies (mAbs). Since the mammalian cells are known to be shear sensitive, optimal performance of the centrifuge requires a balance between productivity and shear. In this study, Computational Fluid Dynamics (CFD) has been successfully used as a tool to facilitate efficient optimization. Multiphase Eulerian-Eulerian model coupled with Gidaspow drag model along with Eulerian-Eulerian k-ε mixture turbulence model have been used to quantify the complex hydrodynamics of the centrifuge and thus evaluate the turbulent stresses generated by the centrifugal forces. An empirical model has been developed by statistical analysis of experimentally observed cell lysis data as a function of turbulent stresses. An operating window that offers the optimal balance between high productivity, high separation efficiency, and low cell damage has been identified by use of CFD modeling.

Characterizing the fluid dynamics of the inverted frustoconical shaking bioreactor

The authors conducted a three-dimensional computational fluid dynamics (CFD) simulation to calculate the flow field in the inverted frustoconical shaking bioreactor with 5 L working volume (IFSB-5L). The CFD models were established for the IFSB-5L at different operating conditions (different shaking speeds and filling volumes) and validated by comparison of the liquid height distribution in the agitated IFSB-5L. The "out of phase" operating conditions were characterized by analyzing the flow field in the IFSB-5L at different filling volumes and shaking speeds. The values of volumetric power consumption (P/V_L ) and volumetric mass transfer coefficient (k_L a) were determined from simulated and experimental results, respectively. Finally, the operating condition effect on P/V_L and k_L a was investigated. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:478-485, 2018.

Population Balance Modeling: Current Status and Future Prospects

Population balance modeling is undergoing phenomenal growth in its applications, and this growth is accompanied by multifarious reviews. This review aims to fortify the model's fundamental base, as well as point to a variety of new applications, including modeling of crystal morphology, cell growth and differentiation, gene regulatory processes, and transfer of drug resistance. This is accomplished by presenting the many faces of population balance equations that arise in the foregoing applications.

High-throughput process development: I. Process chromatography

Chromatographic separation serves as "a workhorse" for downstream process development and plays a key role in removal of product-related, host cell-related, and process-related impurities. Complex and poorly characterized raw materials and feed material, low feed concentration, product instability, and poor mechanistic understanding of the processes are some of the critical challenges that are faced during development of a chromatographic step. Traditional process development is performed as trial-and-error-based evaluation and often leads to a suboptimal process. High-throughput process development (HTPD) platform involves an integration of miniaturization, automation, and parallelization and provides a systematic approach for time- and resource-efficient chromatography process development. Creation of such platforms requires integration of mechanistic knowledge of the process with various statistical tools for data analysis. The relevance of such a platform is high in view of the constraints with respect to time and resources that the biopharma industry faces today. This protocol describes the steps involved in performing HTPD of process chromatography step. It described operation of a commercially available device (PreDictor™ plates from GE Healthcare). This device is available in 96-well format with 2 or 6 μL well size. We also discuss the challenges that one faces when performing such experiments as well as possible solutions to alleviate them. Besides describing the operation of the device, the protocol also presents an approach for statistical analysis of the data that is gathered from such a platform. A case study involving use of the protocol for examining ion-exchange chromatography of granulocyte colony-stimulating factor (GCSF), a therapeutic product, is briefly discussed. This is intended to demonstrate the usefulness of this protocol in generating data that is representative of the data obtained at the traditional lab scale. The agreement in the data is indeed very significant (regression coefficient 0.93). We think that this protocol will be of significant value to those involved in performing high-throughput process development of process chromatography.

Verification of energy dissipation rate scalability in pilot and production scale bioreactors using computational fluid dynamics

Suspension mammalian cell cultures in aerated stirred tank bioreactors are widely used in the production of monoclonal antibodies. Given that production scale cell culture operations are typically performed in very large bioreactors (≥ 10,000 L), bioreactor scale-down and scale-up become crucial in the development of robust cell-culture processes. For successful scale-up and scale-down of cell culture operations, it is important to understand the scale-dependence of the distribution of the energy dissipation rates in a bioreactor. Computational fluid dynamics (CFD) simulations can provide an additional layer of depth to bioreactor scalability analysis. In this communication, we use CFD analyses of five bioreactor configurations to evaluate energy dissipation rates and Kolmogorov length scale distributions at various scales. The results show that hydrodynamic scalability is achievable as long as major design features (# of baffles, impellers) remain consistent across the scales. Finally, in all configurations, the mean Kolmogorov length scale is substantially higher than the average cell size, indicating that catastrophic cell damage due to mechanical agitation is highly unlikely at all scales.

High-throughput process development: II. Membrane chromatography

Membrane chromatography is gradually emerging as an alternative to conventional column chromatography. It alleviates some of the major disadvantages associated with the latter including high pressure drop across the column bed and dependence on intra-particle diffusion for the transport of solute molecules to their binding sites within the pores of separation media. In the last decade, it has emerged as a method of choice for final polishing of biopharmaceuticals, in particular monoclonal antibody products. The relevance of such a platform is high in view of the constraints with respect to time and resources that the biopharma industry faces today. This protocol describes the steps involved in performing HTPD of a membrane chromatography step. It describes operation of a commercially available device (AcroPrep™ Advance filter plate with Mustang S membrane from Pall Corporation). This device is available in 96-well format with 7 μL membrane in each well. We discuss the challenges that one faces when performing such experiments as well as possible solutions to alleviate them. Besides describing the operation of the device, the protocol also presents an approach for statistical analysis of the data that is gathered from such a platform. A case study involving use of the protocol for examining ion exchange chromatography of Granulocyte Colony Stimulating Factor (GCSF), a therapeutic product, is briefly discussed. This is intended to demonstrate the usefulness of this protocol in generating data that is representative of the data obtained at the traditional lab scale. The agreement in the data is indeed very significant (regression coefficient 0.99). We think that this protocol will be of significant value to those involved in performing high-throughput process development of membrane chromatography.

Design of experiments applications in bioprocessing: concepts and approach

Most biotechnology unit operations are complex in nature with numerous process variables, feed material attributes, and raw material attributes that can have significant impact on the performance of the process. Design of experiments (DOE)-based approach offers a solution to this conundrum and allows for an efficient estimation of the main effects and the interactions with minimal number of experiments. Numerous publications illustrate application of DOE towards development of different bioprocessing unit operations. However, a systematic approach for evaluation of the different DOE designs and for choosing the optimal design for a given application has not been published yet. Through this work we have compared the I-optimal and D-optimal designs to the commonly used central composite and Box-Behnken designs for bioprocess applications. A systematic methodology is proposed for construction of the model and for precise prediction of the responses for the three case studies involving some of the commonly used unit operations in downstream processing. Use of Akaike information criterion for model selection has been examined and found to be suitable for the applications under consideration.