Optimization of a glycoengineered Pichia pastoris cultivation process for commercial antibody production

Glycoengineering enabled the production of proteins with human N-linked glycans by Pichia pastoris. This study used a glycoengineered P. pastoris strain which is capable of producing humanized glycoprotein with terminal galactose for monoclonal antibody production. A design of experiments approach was used to optimize the process parameters. Followed by further optimization of the specific methanol feed rate, induction duration, and the initial induction biomass, the resulting process yielded up to 1.6 g/L of monoclonal antibody. This process was also scaled-up to 1,200-L scale, and the process profiles, productivity, and product quality were comparable with 30-L scale. The successful scale-up demonstrated that this glycoengineered P. pastoris fermentation process is a robust and commercially viable process.     

透析培养

本讨论了有效利用透析技术从发酵液中及时转移低分子杂质混合物,从而获得高密度发酵细胞的方法,章从反应系统、工艺策略、膜相关性能、应用我、生产性放大等方面说明了利用透析技术以达到高浓度细胞发酵的有效性和可靠性。透析技术不仅克服了微孔过滤和超滤中存在的膜孔堵塞弊端,而且如果应用“营养分离”补策略,还可以防止营养物质的损失而使培养基被高效利用,在实验条件下,透析培养的潜力通过两种反应模型进行演示：内置     

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 knowledge; 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 that is compliant with current regulations. This review provides an overview of the state-of-the art technology in key aspects of cell culture, e.g., engineering 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.     

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     

S-腺苷甲硫氨酸的研究进展

S-腺苷甲硫氨酸(SAM)是甲硫氨酸和三磷酸腺苷相结合的代谢物,广泛存在于动植物和微生物体内,参与40多种生化反应,主要作为三种代谢途径(转甲基、转硫基、转氨丙基)的前体,临床上被广泛用于治疗肝病、抑郁症、关节炎等。SAM的制备方法主要有化学合成法、酶促合成法、发酵法三种。化学合成的SAM是消旋体,需进行光学拆分,且存在产率低、原料L-高半胱氨酸价格昂贵和环境污染等问题。酶促合成法合成的SAM纯度高,但原料ATP成本太高。发酵法已成为目前生产SAM最常用的方法,欧洲利用发酵法生产SAM已实现了产业化,但国内的起步较晚,目前还处于实验室研究阶段。因此,应加强发酵法生产SAM的产业化关键技术研究。     

Scale-up fermentation of recombinant <Emphasis Type="Italic">Candida rugosa</Emphasis> lipase expressed in <Emphasis Type="Italic">Pichia pastoris</Emphasis> using the GAP promoter

The high-cell-density fermentation of Candida rugosa lipase in the constitutive Pichia pastoris expression system was scaled up from 5 to 800 l in series by optimizing the fermentation conditions at both lab scale and pilot scale. The exponential feeding combined with pH-stat strategy succeeded in small scale studies, while a two-stage fermentation strategy, which shifted at 48 h by fine tuning the culture temperature and pH, was assessed effective in pilot-scale fermentation. The two-stage strategy made an excellent balance between the expression of heterogeneous protein and the growth of host cells, controlling the fermentation at a relatively low cell growth rate for the constitutive yeast expression system to accumulate high-level product. A stable lipase activity of approximately 14,000 IU ml⁻¹ and a cell wet weight of ca. 500 g l⁻¹ at the 800-l scale were obtained. The efficient and convenient techniques suggested in this study might facilitate further scale-up for industrial lipase production.     

大数据-模型混合驱动下生物过程优化与放大的新机遇与挑战

当前,生物制造技术和产业是世界关注的热点。然而,生物过程优化与放大过程中普遍面临以下几个难题,包括:过程检测手段缺乏,难以满足关键指标参数的监控;细胞代谢认知匮乏,无法理性实现过程最优化调控;反应器环境差异大,导致逐级放大效率低下。文中针对以上亟待解决的关键问题,通过案例分析介绍发酵过程实时检测-动态调控-理性放大全链条关键技术创新。在未来,生物过程设计将以集成细胞生理学(时空多尺度细胞代谢模型)和流体动力学(CFD模型)的全生命周期模型为指导,推进计算机辅助设计与开发,加速生物过程实现大规模智能化生产,开启绿色生物制造新时代。     

Application of high‐throughput mini‐bioreactor system for systematic scale‐down modeling,process characterization,and control strategy development

High‐throughput systems and processes have typically been targeted for process development and optimization in the bioprocessing industry. For process characterization, bench scale bioreactors have been the system of choice. Due to the need for performing different process conditions for multiple process parameters, the process characterization studies typically span several months and are considered time and resource intensive. In this study, we have shown the application of a high‐throughput mini‐bioreactor system viz. the Advanced Microscale Bioreactor (ambr15^TM), to perform process characterization in less than a month and develop an input control strategy. As a pre‐requisite to process characterization, a scale‐down model was first developed in the ambr system (15 mL) using statistical multivariate analysis techniques that showed comparability with both manufacturing scale (15,000 L) and bench scale (5 L). Volumetric sparge rates were matched between ambr and manufacturing scale, and the ambr process matched the pCO₂ profiles as well as several other process and product quality parameters. The scale‐down model was used to perform the process characterization DoE study and product quality results were generated. Upon comparison with DoE data from the bench scale bioreactors, similar effects of process parameters on process yield and product quality were identified between the two systems. We used the ambr data for setting action limits for the critical controlled parameters (CCPs), which were comparable to those from bench scale bioreactor data. In other words, the current work shows that the ambr15^TM system is capable of replacing the bench scale bioreactor system for routine process development and process characterization. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1623–1632, 2015     

Approach to designing rotating drum bioreactors for solid-state fermentation on the basis of dimensionless design factors

The development of large-scale solid-state fermentation (SSF) processes is hampered by the lack of simple tools for the design of SSF bioreactors. The use of semifundamental mathematical models to design and operate SSF bioreactors can be complex. In this work, dimensionless design factors are used to predict the effects of scale and of operational variables on the performance of rotating drum bioreactors. The dimensionless design factor (DDF) is a ratio of the rate of heat generation to the rate of heat removal at the time of peak heat production. It can be used to predict maximum temperatures reached within the substrate bed for given operational variables. Alternatively, given the maximum temperature that can be tolerated during the fermentation, it can be used to explore the combinations of operating variables that prevent that temperature from being exceeded. Comparison of the predictions of the DDF approach with literature data for operation of rotating drums suggests that the DDF is a useful tool. The DDF approach was used to explore the consequences of three scale-up strategies on the required air flow rates and maximum temperatures achieved in the substrate bed as the bioreactor size was increased on the basis of geometric similarity. The first of these strategies was to maintain the superficial flow rate of the process air through the drum constant. The second was to maintain the ratio of volumes of air per volume of bioreactor constant. The third strategy was to adjust the air flow rate with increase in scale in such a manner as to maintain constant the maximum temperature attained in the substrate bed during the fermentation.     

Structured kinetic model to represent the utilization of multiple substrates in complex media during rifamycin B fermentation

Industrial fermentations typically use media that are balanced with multiple substitutable substrates including complex carbon and nitrogen source. Yet, much of the modeling effort to date has mainly focused on defined media. Here, we present a structured model that accounts for growth and product formation kinetics of rifamycin B fermentation in a multi-substrate complex medium. The phenomenological model considers the organism to be an optimal strategist with an in-built mechanism that regulates the sequential and simultaneous uptake of the substrate combinations. This regulatory process is modeled by assuming that the uptake of a substrate depends on the level of a key enzyme or a set of enzymes, which may be inducible. Further, the fraction of flux through a given metabolic branch is estimated using a simple multi-variable constrained optimization. The model has the typical form of Monod equation with terms incorporating multiple limiting substrates and substrate inhibition. Several batch runs were set up with varying initial substrate concentrations to estimate the kinetic parameters for the rifamycin overproducer strain Amycolatopsis mediterranei S699. Glucose and ammonium sulfate (AMS) demonstrated significant substrate inhibition toward growth as well as product formation. The model correctly predicts the experimentally observed regulated simultaneous uptake of the substitutable substrate combinations under different fermentation conditions. The modeling results may have applications in the optimization and control of rifamycin B fermentation while the modeling strategy presented here would be applicable to other industrially important fermentations.     

Optimization of batch fermentor sterilization

This article presents a calculation procedure useful for the optimization and scale up of batch sterilization cycles in large-scale fermentors. This technique determines the sterilization temperature and hold-time necessary to minimize nutrient damage in a specific fermentor. The method can also be used for "scaledown" experiments to eliminate sterilization conditions as a scale up parameter. A method for the systematic evaluation of different sterilization conditions on product yield is also presented. This procedure is useful in determining if scale up of sterilization conditions is important for a given process. The validity of the techniques presented are supported by data showing significant yield improvements in a 1.2 x 10(5) L antibiotic fermentation.     

Scale-up of Escherichia coli growth and recombinant protein expression conditions from microwell to laboratory and pilot scale based on matched k(L)a

Fermentation optimization experiments are ideally performed at small scale to reduce time, cost and resource requirements. Currently microwell plates (MWPs) are under investigation for this purpose as the format is ideally suited to automated high-throughput experimentation. In order to translate an optimized small-scale fermentation process to laboratory and pilot scale stirred-tank reactors (STRs) it is necessary to characterize key engineering parameters at both scales given the differences in geometry and the mechanisms of aeration and agitation. In this study oxygen mass transfer coefficients are determined in three MWP formats and in 7.5 L and 75 L STRs. k(L)a values were determined in cell-free media using the dynamic gassing-out technique over a range of agitation conditions. Previously optimized culture conditions at the MWP scale were then scaled up to the larger STR scales on the basis of matched k(L)a values. The accurate reproduction of MWP (3 mL) E. coli BL21 (DE3) culture kinetics at the two larger scales was shown in terms of cell growth, protein expression, and substrate utilization for k(L)a values that provided effective mixing and gas-liquid distribution at each scale. This work suggests that k(L)a provides a useful initial scale-up criterion for MWP culture conditions which enabled a 15,000-fold scale translation in this particular case. This work complements our earlier studies on the application of DoE techniques to MWP fermentation optimization and in so doing provides a generic framework for the generation of large quantities of soluble protein in a rapid and cost-effective manner.     

Dialysis cultures

Dialysis techniques are discussed as a means for effective removal of low-molecular-mass components from fermentation broth to reach high cell density. Reactor systems and process strategies, the relevant properties of membranes and examples for high-density fermentation with dialysis, and problems related to scale-up are addressed. The dialysis technique has turned out to be very efficient and reliable for obtaining high cell densities. As in dialysis processes the membranes are not perfused, membrane clogging is not a problem as it is for micro- and ultrafiltration. By applying a “nutrient-split” feeding strategy, the loss of nutrients can be avoided and the medium is used very efficiently. The potential of dialysis cultures is demonstrated on the laboratory scale in a membrane dialysis reactor with an integrated membrane and in reactor systems with an external dialysis loop. In dialysis cultures with different microorganisms (Staphylococci, Escherichia coli, extremophilic microorganisms, Lactobacilli) the cell densities achieved were up to 30 times higher than those of other fermentation methods. The technique enables high cell densities to be attained without time-consuming medium optimization. For animal cell cultures the concept of a fixed bed coupled with dialysis proved to be very effective. Received: 24 March 1998 / Received revision: 18 June 1998 / Accepted: 19 June 1998     

Scale-up engineering in animal cell technology: Part II

In the first part of this article we defined what is meant by scale-up. We also introduced the idea that engineers, in seeking to scale up bioprocesses, look at parameters that limit that process. If the parameters are independent of scale or reactor configuration they may enable the calculation of engineering data to predict behavior at large scales. In this exercise, dimensional analysis is one of the engineer's most important tools.In Part II, we will examine the application of the approach outlined in Part I to the analysis of scale-up in situations where shear or mass transfer may be limiting factors, situations which are particularly likely to arise in animal cell culture.     

Scaling-up of a batch whey fermentation by Kluyveromyces fragilis

Summary A whey fermentation by Kluyveromyces fragilis was scaled-up to a 1000-dm³ stirred fermentor, by varying the stirrer speed, the air-flow rate and the initial concentration of lactose. Its evolution was simulated by applying the same unstructured model (consisting of a microbial specific growth rate of pseudo-first order with respect to the COD concentration and constant biomass yield per unit COD removed) set up in previous experiments using 8- to 80-dm³ fermentors. Despite the great scale-up ratios, very different operating conditions, and geometric dissimilarity, a series of empirical regressions previously developed allowed approximate, but acceptable prediction of the stoichiometric and kinetic coefficients of the above mathematical model, thus confirming the capability of this model to provide a reliable basis for further scale-up of this fermentation process to a production scale.     

Application of Modeling to Scale-up Dissolution in Pharmaceutical Manufacturing

Liquid mixing scale-up in pharmaceutical industry has often been based on empirical approach in spite of tremendous understanding of liquid mixing scale-up in engineering fields. In this work, we attempt to provide a model-based approach to scale-up dissolution process from a 2 l lab-scale vessel to a 4,000 l scale vessel used in manufacturing. Propylparaben was used as a model compound to verify the model predictions for operating conditions at commercial scale that would result in similar dissolution profile as observed in lab scale. Geometric similarity was maintained between both of the scales to ensure similar mixing characteristics. We utilized computational fluid dynamics (CFD) to ensure that the operating conditions at laboratory and commercial scale will result in similar power per unit volume (P/V). Utilizing this simple scale-up criterion of similar P/V across different scales, results obtained indicate fairly good reproducibility of the dissolution profiles between the two scales. Utilization of concepts of design of experiments enabled summarizing scale-up results in statistically meaningful parameters, for example −90% dissolution in lab scale at a given time under certain operating conditions will result in 75–88% at commercial scale with 95% confidence interval when P/V is maintained constant across the two scales. In this work, we have successfully demonstrated that scale-up of solid dissolution can be done using a systematic process of lab-scale experiments followed by simple CFD modeling to predict commercial-scale experimental conditions.     

Fed-batch bioreactor process scale-up from 3-L to 2,500-L scale for monoclonal antibody production from cell culture

This case study focuses on the scale-up of a Sp2/0 mouse myeloma cell line based fed-batch bioreactor process, from the initial 3-L bench scale to the 2,500-L scale. A stepwise scale-up strategy that involved several intermediate steps in increasing the bioreactor volume was adopted to minimize the risks associated with scale-up processes. Careful selection of several available mixing models from literature, and appropriately applying the calculated results to our settings, resulted in successful scale-up of agitation speed for the large bioreactors. Consideration was also given to scale-up of the nutrient feeding, inoculation, and the set-points of operational parameters such as temperature, pH, dissolved oxygen, dissolved carbon dioxide, and aeration in an integrated manner. It has been demonstrated through the qualitative and the quantitative side-by-side comparison of bioreactor performance as well as through a panel of biochemical characterization tests that the comparability of the process and the product was well controlled and maintained during the process scale-up. The 2,500-L process is currently in use for the routine clinical production of Epratuzumab in support of two global Phase III clinical trials in patients with lupus. Today, the 2,500 L, fed-batch production process for Epratuzumab has met all scheduled batch releases, and the quality of the antibody is consistent and reproducible, meeting all specifications, thus confirming the robustness of the 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.     

Application of multivariate data analysis for identification and successful resolution of a root cause for a bioprocessing application

Multivariate Data Analysis (MVDA) can be used for supporting key activities required for successful bioprocessing. These activities include process characterization, process scale-up, process monitoring, fault diagnosis and root cause analysis. This paper examines an application of MVDA towards root cause analysis for identifying scale-up differences and parameter interactions that adversely impact cell culture process performance. Multivariate data analysis and modeling were performed using data from small-scale (2 L), pilot-scale (2,000 L) and commercial-scale (15,000 L) batches. The input parameters examined included bioreactor pCO2, glucose, lactate, ammonium, raw materials and seed inocula. The output parameters included product attributes, product titer, viable cell density, cell viability and osmolality. Time course performance variables (daily, initial, peak and end point) were also evaluated. Application of MVDA as a diagnostic tool was successful in identifying the root cause and designing experimental conditions to demonstrate and correct it. Process parameters and their interactions that adversely impact cell culture performance and product attributes were successfully identified. MVDA was successfully used as an effective tool for collating process knowledge and increasing process understanding.