Process development of starch hydrolysis using mixing characteristics of Taylor vortices

In food industries, enzymatic starch hydrolysis is an important process that consists of two steps: gelatinization and saccharification. One of the major difficulties in designing the starch hydrolysis process is the sharp change in its rheological properties. In this study, Taylor–Couette flow reactor was applied to continuous starch hydrolysis process. The concentration of reducing sugar produced via enzymatic hydrolysis was evaluated by varying operational variables: rotational speed of the inner cylinder, axial velocity (reaction time), amount of enzyme, and initial starch content in the slurry. When Taylor vortices were formed in the annular space, efficient hydrolysis occurred because Taylor vortices improved the mixing of gelatinized starch with enzyme. Furthermore, a modified inner cylinder was proposed, and its mixing performance was numerically investigated. The modified inner cylinder showed higher potential for enhanced mixing of gelatinized starch and the enzyme than the conventional cylinder.     

改变景观的力量——德克·西蒙斯教授专访

在今天,我们的生存环境面临着诸多挑战,包括气候变化,生物多样性减少,可用于发展的土地资源接近上限等等。面对这些问题,前荷兰首席国家风景园林师德克·西蒙斯认为我们必须关注那些能够改变景观的力量,不管它们是水利工程、旅游业、农业还是新能源。西蒙斯在文中介绍了他的过程导向方法论的思想起点,并通过几个获奖项目阐释了他如何运用这一方法。同时特别强调对生态系统的保护和修复是这个时代最重要的议题之一,也是我们这一代人最重要的使命之一。作为风景园林师,设计结合研究是我们的有力武器。我们不能仅关注眼前工作,还需要用长远的眼光批判地看待整个城市化进程。     

Optimal observation times in experimental epidemic processes

Summary .   This article describes a method for choosing observation times for stochastic processes to maximise the expected information about their parameters. Two commonly used models for epidemiological processes are considered: a simple death process and a susceptible-infected (SI) epidemic process with dual sources for infection spreading within and from outwith the population. The search for the optimal design uses Bayesian computational methods to explore the joint parameter-data-design space, combined with a method known as moment closure to approximate the likelihood to make the acceptance step efficient. For the processes considered, a small number of optimally chosen observations are shown to yield almost as much information as much more intensively observed schemes that are commonly used in epidemiological experiments. Analysis of the simple death process allows a comparison between the full Bayesian approach and locally optimal designs around a point estimate from the prior based on asymptotic results. The robustness of the approach to misspecified priors is demonstrated for the SI epidemic process, for which the computational intractability of the likelihood precludes locally optimal designs. We show that optimal designs derived by the Bayesian approach are similar for observational studies of a single epidemic and for studies involving replicated epidemics in independent subpopulations. Different optima result, however, when the objective is to maximise the gain in information based on informative and non-informative priors: this has implications when an experiment is designed to convince a naïve or sceptical observer rather than consolidate the belief of an informed observer. Some extensions to the methods, including the selection of information criteria and extension to other epidemic processes with transition probabilities, are briefly addressed.     

大尺度景观规划设计的思想与实践——荷兰风景园林师瑞克·德·菲索专访

瑞克·德·菲索先生从他在瓦格宁根度过的学生时代便积累了对大尺度项目的浓厚兴趣,从业多年,他参与并主持了多项重要的大型景观项目,包括马肯湖—瓦登海项目、弗和米尔圩田项目等。通过实践,他展示了自然过程和人类的需求在大尺度项目中很好地整合在一起。他的主要工作方法包括叠图分析、与不同学科背景的专家合作等。此外,他还指出,除了设计的品质,与决策者的沟通也是项目成功的关键。     

Efficient high‐throughput biological process characterization: Definitive screening design with the Ambr250 bioreactor system

The burgeoning pipeline for new biologic drugs has increased the need for high‐throughput process characterization to efficiently use process development resources. Breakthroughs in highly automated and parallelized upstream process development have led to technologies such as the 250‐mL automated mini bioreactor (ambr250?) system. Furthermore, developments in modern design of experiments (DoE) have promoted the use of definitive screening design (DSD) as an efficient method to combine factor screening and characterization. Here we utilize the 24‐bioreactor ambr250? system with 10‐factor DSD to demonstrate a systematic experimental workflow to efficiently characterize an Escherichia coli (E. coli) fermentation process for recombinant protein production. The generated process model is further validated by laboratory‐scale experiments and shows how the strategy is useful for quality by design (QbD) approaches to control strategies for late‐stage characterization. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1388–1395, 2015     

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.     

Optimization of a Saccharomyces cerevisiae fermentation process for production of a therapeutic recombinant protein using a multivariate bayesian approach

Various approaches have been applied to optimize biological product fermentation processes and define design space. In this article, we present a stepwise approach to optimize a Saccharomyces cerevisiae fermentation process through risk assessment analysis, statistical design of experiments (DoE), and multivariate Bayesian predictive approach. The critical process parameters (CPPs) were first identified through a risk assessment. The response surface for each attribute was modeled using the results from the DoE study with consideration given to interactions between CPPs. A multivariate Bayesian predictive approach was then used to identify the region of process operating conditions where all attributes met their specifications simultaneously. The model prediction was verified by twelve consistency runs where all batches achieved broth titer more than 1.53 g/L of broth and quality attributes within the expected ranges. The calculated probability was used to define the reliable operating region. To our knowledge, this is the first case study to implement the multivariate Bayesian predictive approach to the process optimization for the industrial application and its corresponding verification at two different production scales. This approach can be extended to other fermentation process optimizations and reliable operating region quantitation. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 28: 1095–1105, 2012     

Technology outlook for real-time quality attribute and process parameter monitoring in biopharmaceutical development—A review

Real-time monitoring of bioprocesses by the integration of analytics at critical unit operations is one of the paramount necessities for quality by design manufacturing and real-time release (RTR) of biopharmaceuticals. A well-defined process analytical technology (PAT) roadmap enables the monitoring of critical process parameters and quality attributes at appropriate unit operations to develop an analytical paradigm that is capable of providing real-time data. We believe a comprehensive PAT roadmap should entail not only integration of analytical tools into the bioprocess but also should address automated-data piping, analysis, aggregation, visualization, and smart utility of data for advanced-data analytics such as machine and deep learning for holistic process understanding. In this review, we discuss a broad spectrum of PAT technologies spanning from vibrational spectroscopy, multivariate data analysis, multiattribute chromatography, mass spectrometry, sensors, and automated-sampling technologies. We also provide insights, based on our experience in clinical and commercial manufacturing, into data automation, data visualization, and smart utility of data for advanced-analytics in PAT. This review is catered for a broad audience, including those new to the field to those well versed in applying these technologies. The article is also intended to give some insight into the strategies we have undertaken to implement PAT tools in biologics process development with the vision of realizing RTR testing in biomanufacturing and to meet regulatory expectations.     

Estimating functions for inhomogeneous spatial point processes with incomplete covariate data

The R package spatstat provides a very flexible and useful frameworkfor analysing spatial point patterns. A fundamental featureis a procedure for fitting spatial point process models dependingon covariates. However, in practice one often faces incompleteobservation of the covariates and this leads to parameter estimationerror which is difficult to quantify. In this paper, we introducea Monte Carlo version of the estimating function used in spatstatfor fitting inhomogeneous Poisson processes and certain inhomogeneouscluster processes. For this modified estimating function, itis feasible to obtain the asymptotic distribution of the parameterestimators in the case of incomplete covariate information.This allows a study of the loss of efficiency due to the missingcovariate data.     

Optimization of a recombinant human growth hormone purification process using quality by design

This work describes a strategy to optimize a downstream processing of a recombinant human growth hormone (rhGH) by incorporating a quality by design approach toward meeting higher quality specifications. The optimized process minimized the presence of impurities and degradation by-products during manufacturing by the establishment of in-process controls. Capillary zone electrophoresis, reverse phase, and size-exclusion chromatographies were used as analytical techniques to establish new critical process parameters for the solubilization, capture, and intermediate purification steps aiming to maintain rhGH quality by complying with pharmacopeial specifications. The results indicated that the implemented improvements in the process allowed the optimization of the specific recovery and purification of rhGH without compromising its quality. In addition, this optimization facilitated the stringent removal of the remaining impurities in further polishing stages, as demonstrated by the analysis of the obtained active pharmaceutical ingredient.     

Process development and analyses for the co-production of 2-methyltetrahydrofuran and 1,4-pentanediol from lignocellulosic biomass

The development of technologies for utilizing biomass has attracted attention because biomass can be produced sustainably worldwide. Biomass-derived 2-methyltetrahydrofuran (MTHF), which is a promising alternative to gasoline, has great market potential and a growing demand. However, in conventional biomass conversion processes, the minimum selling price (MSP) of biochemicals is not economically acceptable. Co-production of biochemicals can increase the economics of biomass utilization. Herein, we developed a process for co-producing MTHF and 1,4-pentanediol (1,4-PDO) from lignocellulosic biomass. After biomass fractionation, cellulose and hemicellulose were converted to levulinic acid (LA), and lignin was used for heat and electricity generation. LA was then converted to γ-valerolactone (GVL). As a platform material for co-production, GVL was converted into MTHF and 1,4-PDO in each subsystem. The split ratio of GVL was controlled to efficiently produce MTHF and 1,4-PDO according to market conditions. Additionally, we performed a techno-economic and life-cycle assessment (TEA and LCA, respectively) for the developed process. The MSP of MTHF was calculated based on the TEA results, and the environmental impacts were quantitatively calculated based on the LCA results. We performed heat integration using pinch analysis and then reduced the energy requirement of the proposed process. The key cost drivers and environmental factors of the proposed process were identified via sensitivity analyses. Consequently, during the processing of 2000 ton/day of corn stover (raw material of lignocellulose), the MSP of MTHF was calculated as $2.64/GGE (gasoline equivalent), and representative environmental impacts such as climate change and fossil depletion were calculated as −0.296 kg CO₂ eq and − 0.056 kg oil eq, respectively. As a result, we can increase the economics of commercial production of MTHF and 1,4-PDO with environmental sustainability. The proposed process can serve as a potential solution to the growing demand for the need for more sustainable biomass utilization.     

朝鲜蓟提取物颗粒剂的制备工艺研究

以单因素试验为基础，采用正交实验设计优化制备朝鲜蓟(Cynara scolymus)提取物颗粒剂的最佳工艺条件。以原料与辅料配比、原料药比例、乙醇浓度及干燥温度为考察因素，以颗粒合格率、溶化时间作为评价指标，采用L₉(3⁴)正交试验分别对颗粒合格率、溶化时间进行直观分析及方差分析。结果表明，最佳成型工艺为乳糖:糊精=3:1，乙醇浓度60%，原料药比例7.0%，干燥温度50 ℃。按此方案进行验证实验，颗粒性状良好，颗粒合格率为91.45%，含水量4.90%，减失重量不超过2.0%，溶解时间85.67 s，均符合2020年中国药典有关规定。通过正交试验优选的颗粒剂制备工艺稳定、简便易行，为朝鲜蓟提取物的剂型开发及工业化生产颗粒剂提供理论依据。     

夏天无药材提取工艺研究

采用正交试验法,以原阿片碱转移率为指标,考察乙醇浓度(A)、乙醇用量(B)、提取时间(C)和提取次数(D)4个因素对夏天无提取工艺的影响。结果表明,优化的夏天无提取工艺为A₃B₁C₃D₃,即取夏天无药材粉碎成粗颗粒,以90%乙醇加热回流提取3次,每次加6倍量乙醇,第一次提取2 h,第二次提取1 h,第三次提取1 h。     

Selection of best conditions of inoculum preparation for optimum performance of the pigment production process by Talaromyces spp. using the Taguchi method

Process optimisation techniques increasingly need to be used early on in research and development of processes for new ingredients. There are different approaches and this article illustrates the main issues at stake with a method that is an industry best practice, the Taguchi method, suggesting a procedure to assess the potential impact of its drawbacks. The Taguchi method has been widely used in various industrial sectors because it minimises the experimental requirements to define an optimum region of operation, which is particularly relevant when minimising variability is a target. However, it also has drawbacks, especially the intricate confoundings generated by the experimental designs used. This work reports a process optimisation of the synthesis of red pigments by a fungal strain, Talaromyces spp. using the Taguchi methodology and proposes an approach to assess from validation trials whether the conclusions can be accepted with confidence. The work focused on optimising the inoculum characteristics, and the studied factors were spore age and concentration, agitation speed and incubation time. It was concluded that spore age was the most important factor for both responses, with optimum results at 5 days old, with the best other conditions being spores concentration, 100,000 (spores/mL); agitation, 200 rpm; and incubation time, 84 h. The interactive effects can be considered negligible and therefore this is an example where a simple experimental design approach was successful in speedily indicating conditions able to increase pigment production by 63% compared to an average choice of settings. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:621–632, 2017     

Computer-aided process analysis and economic evaluation for biosynthetic human insulin production-A case study

Human insulin was the first mammalian protein produced in bacteria using recombinant DNA technology. Two technologies were developed; the first based on the separate expression of precursors of chains A and B of insulin, and the second based on the expression of a precursor of proinsulin as a Trp-E fusion protein. Both technologies utilized Escherichia coli as an expression system. Later, a third technology was developed based on a strain of yeast that can secrete a precursor of insulin. The second E. coli process, a variation of which has been commercialized by Eli Lilly and Co., is analyzed in this article from a process design and economic evaluation viewpoint. The objective of this work is to elucidate the technical complexity and high cost associated with the manufacturing of biopharmaceuticals. Human insulin is a good example of a protein-based biopharmaceutical produced in large quantities (a fex tons per year) that requires large scale equipment and presents a multitude of scale-up challenges. Based onthe analysis, a number of conclusions are drawn regarding the cost breakdown and cost dependency on process parameters. Recommendations are made for cost reduction and environmental impact minimization. This analysis was performed using a software tool for computer-aided bioprocess design. (c) 1995 John Wiley & Sons, Inc.