Application of multivariate analysis toward biotech processes: case study of a cell-culture unit operation

This paper examines the feasibility of using multivariate data analysis (MVDA) for supporting some of the key activities that are required for successful manufacturing of biopharmaceutical products. These activities include scale-up, process comparability, process characterization, and fault diagnosis. Multivariate data analysis and modeling were performed using representative data from small-scale (2 L) and large-scale (2000 L) batches of a cell-culture process. Several input parameters (pCO2, pO2, glucose, pH, lactate, ammonium ions) and output parameters (purity, viable cell density, viability, osmolality) were evaluated in this analysis. Score plots, loadings plots, and VIP plots were utilized for assessing scale-up and comparability of the cell-culture process. Batch control charts were found to be useful for fault diagnosis during routine manufacturing. Finally, observations made from reviewing VIP plots were found to be in agreement with conclusions from process characterization studies demonstrating the effectiveness of MVDA as a tool for extracting process knowledge.     

Application of near‐infrared (NIR) spectroscopy for screening of raw materials used in the cell culture medium for the production of a recombinant therapeutic protein

Control of raw materials based on an understanding of their impact on product attributes has been identified as a key aspect of developing a control strategy in the Quality by Design (QbD) paradigm. This article presents a case study involving use of a combined approach of Near‐infrared (NIR) spectroscopy and Multivariate Data Analysis (MVDA) for screening of lots of basal medium powders based on their impact on process performance and product attributes. These lots had identical composition as per the supplier and were manufactured at different scales using an identical process. The NIR/MVDA analysis, combined with further investigation at the supplier site, concluded that grouping of medium components during the milling and blending process varied with the scale of production and media type. As a result, uniformity of blending, impurity levels, chemical compatibility, and/or heat sensitivity during the milling process for batches of large‐scale media powder were deemed to be the source of variation as detected by NIR spectra. This variability in the raw materials was enough to cause unacceptably large variability in the performance of the cell culture step and impact the attributes of the resulting product. A combined NIR/MVDA approach made it possible to finger print the raw materials and distinguish between good and poor performing media lots. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Guidance for performing multivariate data analysis of bioprocessing data: Pitfalls and recommendations

Biotech unit operations are often characterized by a large number of inputs (operational parameters) and outputs (performance parameters) along with complex correlations among them. A typical biotech process starts with the vial of the cell bank, ends with the final product, and has anywhere from 15 to 30 such unit operations in series. Besides the above‐mentioned operational parameters, raw material attributes can also impact process performance and product quality as well as interact among each other. Multivariate data analysis (MVDA) offers an effective approach to gather process understanding from such complex datasets. Review of literature suggests that the use of MVDA is rapidly increasing, fuelled by the gradual acceptance of quality by design (QbD) and process analytical technology (PAT) among the regulators and the biotech industry. Implementation of QbD and PAT requires enhanced process and product understanding. In this article, we first discuss the most critical issues that a practitioner needs to be aware of while performing MVDA of bioprocessing data. Next, we present a step by step procedure for performing such analysis. Industrial case studies are used to elucidate the various underlying concepts. With the increasing usage of MVDA, we hope that this article would be a useful resource for present and future practitioners of MVDA. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:967–973, 2014     

Development of a scale down cell culture model using multivariate analysis as a qualification tool

In characterizing a cell culture process to support regulatory activities such as process validation and Quality by Design, developing a representative scale down model for design space definition is of great importance. The manufacturing bioreactor should ideally reproduce bench scale performance with respect to all measurable parameters. However, due to intrinsic geometric differences between scales, process performance at manufacturing scale often varies from bench scale performance, typically exhibiting differences in parameters such as cell growth, protein productivity, and/or dissolved carbon dioxide concentration. Here, we describe a case study in which a bench scale cell culture process model is developed to mimic historical manufacturing scale performance for a late stage CHO‐based monoclonal antibody program. Using multivariate analysis (MVA) as primary data analysis tool in addition to traditional univariate analysis techniques to identify gaps between scales, process adjustments were implemented at bench scale resulting in an improved scale down cell culture process model. Finally we propose an approach for small scale model qualification including three main aspects: MVA, comparison of key physiological rates, and comparison of product quality attributes. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:152–160, 2014     

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody–peptide fusion

Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody–peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high‐throughput (HT) micro‐bioreactor system (Ambr^TM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on‐line and off‐line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale‐up. Biotechnol. Bioeng. 2017;114: 2222–2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Multivariate data analysis on historical IPV production data for better process understanding and future improvements

Historical manufacturing data can potentially harbor a wealth of information for process optimization and enhancement of efficiency and robustness. To extract useful data multivariate data analysis (MVDA) using projection methods is often applied. In this contribution, the results obtained from applying MVDA on data from inactivated polio vaccine (IPV) production runs are described. Data from over 50 batches at two different production scales (700‐L and 1,500‐L) were available. The explorative analysis performed on single unit operations indicated consistent manufacturing. Known outliers (e.g., rejected batches) were identified using principal component analysis (PCA). The source of operational variation was pinpointed to variation of input such as media. Other relevant process parameters were in control and, using this manufacturing data, could not be correlated to product quality attributes. The gained knowledge of the IPV production process, not only from the MVDA, but also from digitalizing the available historical data, has proven to be useful for troubleshooting, understanding limitations of available data and seeing the opportunity for improvements. Biotechnol. Bioeng. 2010;107: 96–104. © 2010 Wiley Periodicals, Inc.     

Fermentanomics: Relating quality attributes of a monoclonal antibody to cell culture process variables and raw materials using multivariate data analysis

Fermentanomics is an emerging field of research and involves understanding the underlying controlled process variables and their effect on process yield and product quality. Although major advancements have occurred in process analytics over the past two decades, accurate real‐time measurement of significant quality attributes for a biotech product during production culture is still not feasible. Researchers have used an amalgam of process models and analytical measurements for monitoring and process control during production. This article focuses on using multivariate data analysis as a tool for monitoring the internal bioreactor dynamics, the metabolic state of the cell, and interactions among them during culture. Quality attributes of the monoclonal antibody product that were monitored include glycosylation profile of the final product along with process attributes, such as viable cell density and level of antibody expression. These were related to process variables, raw materials components of the chemically defined hybridoma media, concentration of metabolites formed during the course of the culture, aeration‐related parameters, and supplemented raw materials such as glucose, methionine, threonine, tryptophan, and tyrosine. This article demonstrates the utility of multivariate data analysis for correlating the product quality attributes (especially glycosylation) to process variables and raw materials (especially amino acid supplements in cell culture media). The proposed approach can be applied for process optimization to increase product expression, improve consistency of product quality, and target the desired quality attribute profile. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1586–1599, 2015     

Multivariate PAT solutions for biopharmaceutical cultivation: current progress and limitations

Increasingly elaborate and voluminous datasets are generated by the (bio)pharmaceutical industry and are a major challenge for application of PAT and QbD principles. Multivariate data analysis (MVDA) is required to delineate relevant process information from large multi-factorial and multi-collinear datasets. Here the key role of MVDA for industrial (bio)process data is discussed, with a focus on progress and limitations of MVDA as a PAT solution for biopharmaceutical cultivation processes. MVDA based models were proven useful and should be routinely implemented for bioprocesses. It is concluded that although the highest level of PAT with process control within its design space in real-time during manufacturing is not reached yet, MVDA will be central to reach this ultimate objective for cell cultivations.     

Real-time monitoring of quality attributes by in-line Fourier transform infrared spectroscopic sensors at ultrafiltration and diafiltration of bioprocess

Technologies capable of monitoring product quality attributes and process parameters in real time are becoming popular due to the endorsement of regulatory agencies and also to support the agile development of biotherapeutic pipelines. The utility of vibrational spectroscopic techniques such as Fourier transform mid-infrared (Mid-IR) and multivariate data analysis (MVDA) models allows the prediction of multiple critical attributes simultaneously in real time. This study reports the use of Mid-IR and MVDA model sensors for monitoring of multiple attributes (excipients and protein concentrations) in real time (measurement frequency of every 40 s) at ultrafiltration and diafiltration (UF/DF) unit operation of biologics manufacturing. The platform features integration of fiber optic Mid-IR probe sensors to UF/DF set up at the bulk solution and through a flow cell at the retentate line followed by automated Mid-IR data piping into a process monitoring software platform with pre-loaded partial least square regression (PLS) chemometric models. Data visualization infrastructure is also built-in to the platform so that upon automated PLS prediction of excipients and protein concentrations, the results were projected in a graphical or numerical format in real time. The Mid-IR predicted concentrations of excipients and protein show excellent correlation with the offline measurements by traditional analytical methods. Absolute percent difference values between Mid-IR predicted results and offline reference assay results were ≤5% across all the excipients and the protein of interest; which shows a great promise as a reliable process analytical technology tool.     

Exploring the linkage between cell culture process parameters and downstream processing utilizing a plackett‐burman design for a model monoclonal antibody

Linkage of upstream cell culture with downstream processing and purification is an aspect of Quality by Design crucial for efficient and consistent production of high quality biopharmaceutical proteins. In a previous Plackett‐Burman screening study of parallel bioreactor cultures we evaluated main effects of 11 process variables, such as agitation, sparge rate, feeding regimens, dissolved oxygen set point, inoculation density, supplement addition, temperature, and pH shifts. In this follow‐up study, we observed linkages between cell culture process parameters and downstream capture chromatography performance and subsequent antibody attributes. In depth analysis of the capture chromatography purification of harvested cell culture fluid yielded significant effects of upstream process parameters on host cell protein abundance and behavior. A variety of methods were used to characterize the antibody both after purification and buffer formulation. This analysis provided insight in to the significant impacts of upstream process parameters on aggregate formation, impurities, and protein structure. This report highlights the utility of linkage studies in identifying how changes in upstream parameters can impact downstream critical quality attributes. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:163–170, 2017     

Effect of process change from perfusion to fed-batch on product comparability for biosimilar monoclonal antibody

A fed-batch process for the production of biosimilar monoclonal antibody was developed. Since the brand product is produced by perfusion process, the impact of process change from perfusion to fed-batch on product quality and cell performance was evaluated. Perfusion culture was performed at 0.47–1.00 (v/v/d) perfusion rate by spin-filter method with 15–17 μm mesh. Culture parameters such as pH (6.8–7.2), dissolved oxygen (40–70% air saturation), temperature (37 °C) and agitation speed (250 rpm) were applied in both culture modes. In terms of cell performance, volumetric productivity increased 3.7 times while process performance increased 7.5 times in fed-batch culture due to 10 times higher scalability. Considering the glycosylation pattern and charge variants, no significant changes in product quality were observed upon process change, although intact IgG level slightly decreased in fed-batch mode. The change of production media showed more effect on glycosylation patterns than the operation in different culture modes. Furthermore, there were no differences in biological activity, including TNFα, FcγRIIIa, and C1q-binding affinity. Through a scale-up study from 3 L to 12,500 L, it was confirmed that cell performance and product quality could be maintained. In conclusion, product quality of the fed-batch process was comparable to that of the reference product.     

Modulation of high mannose levels in N-linked glycosylation through cell culture process conditions to increase antibody-dependent cell-mediated cytotoxicity activity for an antibody biosimilar

The regulatory approval of a biosimilar product is contingent on the favorable comparability of its safety and efficacy to that of the innovator product. As such, it is important to match the critical quality attributes of the biosimilar product to that of the innovator product. The N-glycosylation profile of a monoclonal antibody (mAb) can influence effector function activities such as antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-dependent cytotoxicity. In this study, we describe efforts to modulate the high-mannose (HM) levels of a biosimilar mAb produced in a Chinese hamster ovary cell fed-batch process. Because the HM level of the mAb was observed to impact ADCC activity, it was desirable to match it to the innovator mAb's levels. Several cell culture process related factors known to modulate the HM content of N-glycosylation were investigated, including osmolality, ammonium chloride (NH₄Cl) addition, glutamine concentration, monensin addition, and the addition of alternate sugars and amino sugars to the feed medium. The process conditions evaluated varied in impact on HM levels, process performance and product quality. One condition, the addition of alternate sugars and amino sugars to feed medium, was identified as the preferred method for increasing HM levels with minimal disruptions to process performance or other product quality attributes. Interestingly, a secondary interaction between sugar and amino sugar supplemented feeds and osmolality was observed during process scale-up. These studies demonstrate sugar and amino sugar concentrations and osmolality are critical variables to evaluate to match HM content in biosimilar and their innovator mAbs.     

Interaction of cell culture process parameters for modulating mAb afucosylation

The extent of afucosylation, which refers to the absence of core fucose on Fc glycans, can correlate positively with the antibody-dependent cellular cytotoxicity (ADCC) activity of a monoclonal antibody (mAb). Therefore, it is important to maintain consistent afucosylation during cell culture process scale-up in bioreactors for a mAb with ADCC activity. However, there is currently a lack of understanding about the impact of partial pressure of carbon dioxide (pCO₂)—a parameter that can vary with bioreactor scale—on afucosylation. Using a small-scale (3 L) bioreactor model that can modulate pCO ₂ levels through modified configurations and gassing strategies, we identified three cell culture process parameters that influence afucosylation of a mAb produced by a recombinant Chinese Hamster Ovary (CHO) cell line: pCO ₂, media hold duration (at 37°C), and manganese. These three-independent parameters demonstrated a synergistic effect on mAb afucosylation; increase in pCO ₂, media hold duration, and manganese consistently increased afucosylation. Our investigations into the underlying mechanisms through proteomic analysis indicated that the synergistic interactions downregulated pathways related to guanosine diphosphate-fucose synthesis and fucosylation, and upregulated manganese transport into the CHO cells. These new findings highlight the importance of considering potential differences in culture environment and operations across bioreactor scales, and understanding the impact of their interactions on product quality.     

Towards robust cell culture processes — Unraveling the impact of media preparation by spectroscopic online monitoring

Biopharmaceutical manufacturing processes can be affected by variability in cell culture media, e.g. caused by raw material impurities. Although efforts have been made in industry and academia to characterize cell culture media and raw materials with advanced analytics, the process of industrial cell culture media preparation itself has not been reported so far. Within this publication, we first compare mid‐infrared and two‐dimensional fluorescence spectroscopy with respect to their suitability as online monitoring tools during cell culture media preparation, followed by a thorough assessment of the impact of preparation parameters on media quality. Through the application of spectroscopic methods, we can show that media variability and its corresponding root cause can be detected online during the preparation process. This methodology is a powerful tool to avoid batch failure and is a valuable technology for media troubleshooting activities. Moreover, in a design of experiments approach, including additional liquid chromatography–mass spectrometry analytics, it is shown that variable preparation parameters such as temperature, power input and preparation time can have a strong impact on the physico‐chemical composition of the media. The effect on cell culture process performance and product quality in subsequent fed‐batch processes was also investigated. The presented results reveal the need for online spectroscopic methods during the preparation process and show that media variability can already be introduced by variation in media preparation parameters, with a potential impact on scale‐up to a commercial manufacturing process.     

Application of quality by design principles to the development and technology transfer of a major process improvement for the manufacture of a recombinant protein

This study describes the application of quality by design (QbD) principles to the development and implementation of a major manufacturing process improvement for a commercially distributed therapeutic protein produced in Chinese hamster ovary cell culture. The intent of this article is to focus on QbD concepts, and provide guidance and understanding on how the various components combine together to deliver a robust process in keeping with the principles of QbD. A fed-batch production culture and a virus inactivation step are described as representative examples of upstream and downstream unit operations that were characterized. A systematic approach incorporating QbD principles was applied to both unit operations, involving risk assessment of potential process failure points, small-scale model qualification, design and execution of experiments, definition of operating parameter ranges and process validation acceptance criteria followed by manufacturing-scale implementation and process validation. Statistical experimental designs were applied to the execution of process characterization studies evaluating the impact of operating parameters on product quality attributes and process performance parameters. Data from process characterization experiments were used to define the proven acceptable range and classification of operating parameters for each unit operation. Analysis of variance and Monte Carlo simulation methods were used to assess the appropriateness of process design spaces. Successful implementation and validation of the process in the manufacturing facility and the subsequent manufacture of hundreds of batches of this therapeutic protein verifies the approaches taken as a suitable model for the development, scale-up and operation of any biopharmaceutical manufacturing process.     

Quantification of power consumption and oxygen transfer characteristics of a stirred miniature bioreactor for predictive fermentation scale-up

Miniature parallel bioreactors are becoming increasingly important as tools to facilitate rapid bioprocess design. Once the most promising strain and culture conditions have been identified a suitable scale-up basis needs to be established in order that the cell growth rates and product yields achieved in small scale optimization studies are maintained at larger scales. Recently we have reported on the design of a miniature stirred bioreactor system capable of parallel operation [Gill et al. (2008); Biochem Eng J 39:164-176]. In order to enable the predictive scale-up of miniature bioreactor results the current study describes a more detailed investigation of the bioreactor mixing and oxygen mass transfer characteristics and the creation of predictive engineering correlations useful for scale-up studies. A Power number of 3.5 for the miniature turbine impeller was first established based on experimental ungassed power consumption measurements. The variation of the measured gassed to ungassed power ratio, P(g)/P(ug), was then shown to be adequately predicted by existing correlations proposed by Cui et al. [Cui et al. (1996); Chem Eng Sci 51:2631-2636] and Mockel et al. [Mockel et al. (1990); Acta Biotechnol 10:215-224]. A correlation relating the measured oxygen mass transfer coefficient, k(L)a, to the gassed power per unit volume and superficial gas velocity was also established for the miniature bioreactor. Based on these correlations a series of scale-up studies at matched k(L)a (0.06-0.11 s(-1)) and P(g)/V (657-2,960 W m(-3)) were performed for the batch growth of Escherichia coli TOP10 pQR239 using glycerol as a carbon source. Constant k(L)a was shown to be the most reliable basis for predictive scale-up of miniature bioreactor results to conventional laboratory scale. This gave good agreement in both cell growth and oxygen utilization kinetics over the range of k(L)a values investigated. The work described here thus gives further insight into the performance of the miniature bioreactor design and will aid its use as a tool for rapid fermentation process development.     

Protein aggregation and mitigation strategy in low pH viral inactivation for monoclonal antibody purification

ABSTRACT

Significant amounts of soluble product aggregates were observed during low-pH viral inactivation (VI) scale-up for an IgG4 monoclonal antibody (mAb IgG4-N1), while small-scale experiments in the same condition showed negligible aggregation. Poor mixing and product exposure to low pH were identified as the root cause. To gain a mechanistic understanding of the problem, protein aggregation properties were studied by varying critical parameters including pH, hold time and protein concentration. Comprehensive biophysical characterization of product monomers and aggregates was performed using fluorescence-size-exclusion chromatography, differential scanning fluorimetry, fluorescence spectroscopy, and dynamic light scattering. Results showed IgG4-N1 partially unfolds at about pH 3.3 where the product molecules still exist largely as monomers owing to strong inter-molecular repulsions and favorable colloidal stability. In the subsequent neutralization step, however, the conformationally changed monomers are prone to aggregation due to weaker inter-molecular repulsions following the pH transition from 3.3 to 5.5. Surface charge calculations using homology modeling suggested that intra-molecular repulsions, especially between CH2 domains, may contribute to the IgG4-N1 unfolding at ≤ pH 3.3. Computational fluid dynamics (CFD) modeling was employed to simulate the conditions of pH titration to reduce the risk of aggregate formation. The low-pH zones during acid addition were characterized using CFD modeling and correlated to the condition causing severe product aggregation. The CFD tool integrated with the mAb solution properties was used to optimize the VI operating parameters for successful scale-up demonstration. Our research revealed the governing aggregation mechanism for IgG4-N1 under acidic conditions by linking its molecular properties and various process-related parameters to macroscopic aggregation phenomena. This study also provides useful insights into the cause and mitigation of low-pH-induced IgG4 aggregation in downstream VI operation.     

Cell culture processes for monoclonal antibody production

Animal cell culture technology has advanced significantly over the last few decades and is now generally considered a reliable, robust and relatively mature technology. A range of biotherapeutics are currently synthesized using cell culture methods in large scale manufacturing facilities that produce products for both commercial use and clinical studies. The robust implementation of this technology requires optimization of a number of variables, including (1) cell lines capable of synthesizing the required molecules at high productivities that ensure low operating cost; (2) culture media and bioreactor culture conditions that achieve both the requisite productivity and meet product quality specifications; (3) appropriate on-line and off-line sensors capable of providing information that enhances process control; and (4) good understanding of culture performance at different scales to ensure smooth scale-up. Successful implementation also requires appropriate strategies for process development, scale-up and process characterization and validation that enable robust operation and ensure compliance with current regulations. This review provides an overview of the state-of-the art technology in key aspects of cell culture, e.g., generation of highly productive cell lines and optimization of cell culture process conditions. We also summarize the current thinking on appropriate process development strategies and process advances that might affect process development.Key words: monoclonal antibody, expression systems, cell line engineering, cell culture process development, optimization scale-up and technology transfer, process advances     

Accelerating patient access to novel biologics using stable pool‐derived product for non‐clinical studies and single clone‐derived product for clinical studies

Cell cloning and subsequent process development activities are on the critical path directly impacting the timeline for advancement of next generation therapies to patients with unmet medical needs. The use of stable cell pools for early stage material generation and process development activities is an enabling technology to reduce timelines. To successfully use stable pools during development, it is important that bioprocess performance and requisite product quality attributes be comparable to those observed from clonally derived cell lines. To better understand the relationship between pool and clone derived cell lines, we compared data across recent first in human (FIH) programs at Amgen including both mAb and Fc‐fusion modalities. We compared expression and phenotypic stability, bioprocess performance, and product quality attributes between material derived from stable pools and clonally derived cells. Overall, our results indicated the feasibility of matching bioprocess performance and product quality attributes between stable pools and subsequently derived clones. These findings support the use of stable pools to accelerate the advancement of novel biologics to the clinic. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1476–1482, 2017     

Development toward rapid and efficient screening for high performance hydrolysate lots in a recombinant monoclonal antibody manufacturing process

Plant‐derived hydrolysates are widely used in mammalian cell culture media to increase yields of recombinant proteins and monoclonal antibodies (mAbs). However, these chemically varied and undefined raw materials can have negative impact on yield and/or product quality in large‐scale cell culture processes. Traditional methods that rely on fractionation of hydrolysates yielded little success in improving hydrolysate quality. We took a holistic approach to develop an efficient and reliable method to screen intact soy hydrolysate lots for commercial recombinant mAb manufacturing. Combined high‐resolution ¹H nuclear magnetic resonance (NMR) spectroscopy and partial least squares (PLS) analysis led to a prediction model between product titer and NMR fingerprinting of soy hydrolysate with cross‐validated correlation coefficient R² of 0.87 and root‐mean‐squared‐error of cross‐validation RMSECV% of 11.2%. This approach screens for high performance hydrolysate lots, therefore ensuring process consistency and product quality in the mAb manufacturing process. Furthermore, PLS analysis was successful in discerning multiple markers (DL‐lactate, soy saccharides, citrate and succinate) among hydrolysate components that positively and negatively correlate with titer. Interestingly, these markers correlate to the metabolic characteristics of some strains of taxonomically diverse lactic acid bacteria (LAB). Thus our findings indicate that LAB strains may exist during hydrolysate manufacturing steps and their biochemical activities may attribute to the titer enhancement effect of soy hydrolysates. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 28: 1061–1068, 2012