黄花菜固体饮料配方及喷雾干燥工艺的研究

本研究旨在研制一种基于黄花菜的固体饮料。以黄花菜为主要原料,以感官评分、冲泡性能为指标,采用响应面试验对黄花菜固体饮料的配方和干燥工艺进行优化。试验表明,黄花菜固体饮料配方的响应面优化结果为:食盐添加量0. 01%,麦芽糊精添加量2. 0%,马铃薯全粉添加量1. 0%,奶粉添加量4. 5%,黄花菜与水比值1∶9(m∶v);此配方下研制出的黄花菜固体饮料流动性最佳,表征值为72. 855 mm。喷雾干燥的最佳工艺参数是进风温度为180℃,入料流量为1. 5 mL/min;所得样品的感官评分值为94. 2,流动性表征值为71. 65mm,润湿性表征值为27. 75 min。     

微弱发光分析技术应用实例(四)

植物生理变化往往伴随着发光过程,探测这种发光过程,寻求其规律性,对于农业、林业科学研究具有重要意义.BPCL型微弱发光测量仪的样品室可以直接测量各种生物（植物、动物）体系的发光.超弱发光测量对于大豆种子生理变化敏感,有可能作为品种鉴定的手段之一.微弱发光动力学测量是具有应用前景的新方法,可用于多种植物的抗逆性研究.     

响应面法优化火麻仁油微胶囊喷雾干燥工艺的研究

为了制备包埋率高、稳定性好的火麻仁油微胶囊,拓展其在食品领域的应用范围,以火麻仁油为芯材、单双脂肪酸甘油酯为乳化剂、酪蛋白酸钠为壁材、固体玉米糖浆为填充剂、柠檬酸钠为缓冲盐、抗坏血酸棕榈酸钠为抗氧化剂,通过喷雾干燥法制备60%载油率的火麻仁油微胶囊,以微胶囊包埋率为响应值,在单因素实验的基础上,以干物浓度、进风温度、出风温度为实验因素,采用Box-Behnken响应面分析法进行优化。随后通过扫描电镜观察火麻仁油微胶囊表面形态结构,以确定包埋效果。并利用油脂氧化分析仪检测火麻仁油微胶囊的氧化稳定性。研究确定微胶囊的最佳工艺条件为：干物浓度42%、进风温度168 ℃、出风温度74 ℃,在此条件下制备得到的火麻仁油微胶囊包埋率可达92.15%。通过扫描电镜观察到火麻仁油微胶囊表面圆滑无裂痕,表明火麻仁油微胶囊包埋效果比较理想。经油脂氧化分析仪测定,与对照组（火麻仁油）相比,试验组（火麻仁油微胶囊）的氧化诱导期时间较长,能够达到30 h以上,说明通过对火麻仁油进行微胶囊包埋可以较大程度地提高油脂的稳定性。研究结果为火麻仁油在食品工业领域的开发和应用提供了理论支持。     

微弱发光分析技术应用实例(三)——药物抗氧化作用的测定

微弱发光分析技术用于测定药物的抗氧化作用方式和抗氧化能力有其独特的优点.简要介绍应用BPCL型微弱发光仪测定了十几种药物的抗氧化性能的方法和初步结论.说明了这种技术和仪器在应用领域的作用.还谈到了BPCL微弱发光测量仪数据采集和分析的主要性能.     

微小RNA分析技术研究进展

微小RNA（miRNA）是一类起重要调控作用的非编码小分子RNA。准确分析组织或细胞中miRNA的表达水平是研究其生物学功能的基础。近年,研究者开发出多种方法检测不同生理、病理过程中miRNA的差异表达,发现miRNA的异常表达与癌症等多种疾病密切相关。目前,miRNA已逐渐成为重要的疾病诊断生物标志物乃至治疗靶点。miRNA的分析技术贯穿miRNA的研究和药物研发过程,并起到关键作用。我们针对miRNA的不同研究阶段所采用的定性和定量分析方法,着重阐述了用于初始miRNA研究的克隆测序类技术、分析miRNA表达谱的高通量芯片技术、研究具体目标miRNA及其前体表达的qPCR和改良Northern印迹技术,以及将修饰后miRNA作为药物的药代动力学评价技术。     

Effect of Drying Process on Heavy Metals Fractionation of Contaminated Sludge for Land Application

Metal fractionation studies on metals in sludge are usually done on dried sludge. Although there are advantages in this form of sludge, it is possible that fractionation of metals in sludge may be influenced by the drying process, which consequently affects mobility of metals at disposal. In this study, sequential chemical extraction was done to assess the effect of drying on fractionation of cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), nickel (Ni), and zinc (Zn) on wet and dewatered (air-dried and oven-dried) anaerobically digested sludge samples in Bangkok, Thailand. Results revealed an insignificant difference in the fractionation profile of metals for both wet and dewatered sludge. The higher percentage of residual fraction for Cu and oxidizable fraction for Zn in the wet sludge, however, makes this form more suitable for direct land application. In the case of oven-dried and air-dried sludge, the forms of some metals (e.g., Pb and Zn) seem to vary significantly as the sludge is oven-dried, with Pb decreasing its residual phase by 15%, and Zn increasing in oxidizable phase by 41%. The results seem to indicate that drying affects bioavailability of metals in sludge and air-drying seems to favor sludge for land application.     

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

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

Bioprocessing in the Digital Age: The Role of Process Models

In this age of technology, the vision of manufacturing industries built of smart factories is not a farfetched future. As a prerequisite for Industry 4.0, industrial sectors are moving towards digitalization and automation. Despite its tremendous growth reaching a sales value of worth $188 billion in 2017, the biopharmaceutical sector distinctly lags in this transition. Currently, the challenges are innovative market disruptions such as personalized medicine as well as increasing commercial pressure for faster and cheaper product manufacturing. Improvements in digitalization and data analytics have been identified as key strategic activities for the next years to face these challenges. Alongside, there is an emphasis by the regulatory authorities on the use of advanced technologies, proclaimed through initiatives such as Quality by Design (QbD) and Process Analytical Technology (PAT). In the manufacturing sector, the biopharmaceutical domain features some of the most complex and least understood processes. Thereby, process models that can transform process data into more valuable information, guide decision‐making, and support the creation of digital and automated technologies are key enablers. This review summarizes the current state of model‐based methods in different bioprocess related applications and presents the corresponding future vision for the biopharmaceutical industry to achieve the goals of Industry 4.0 while meeting the regulatory requirements.     

Evaluation of manometric temperature measurement (MTM), a process analytical technology tool in freeze drying, part III: Heat and mass transfer measurement

This article evaluates the procedures for determining the vial heat transfer coefficient and the extent of primary drying through manometric temperature measurement (MTM). The vial heat transfer coefficients (K_v) were calculated from the MTM-determined temperature and resistance and compared with K_v values determined by a gravimetric method. The differences between the MTM vial heat transfer coefficients and the gravimetric values are large at low shelf temperature but smaller when higher shelf temperatures were used. The differences also became smaller at higher chamber pressure and smaller when higher resistance materials were being freeze-dried. In all cases, using thermal shields greatly improved the accuracy of the MTM K_v measurement. With use of thermal shields, the thickness of the frozen layer calculated from MTM is in good agreement with values obtained gravimetrically. The heat transfer coefficient “error” is largely a direct result of the error in the dry layer resistance (ie, MTM-determined resistance is too low). This problem can be minimized if thermal shields are used for freeze-drying. With suitable use of thermal shields, accurate K_v values are obtained by MTM; thus allowing accurate calculations of heat and mass flow rates. The extent of primary drying can be monitored by real-time calculation of the amount of remaining ice using MTM data, thus providing a process analytical tool that greatly improves the freeze-drying process design and control.     

Process analytical technology implementation for protein refolding: GCSF as a case study

Process analytical technology is gaining interest in the biopharmaceutical industry as a means to enable consistency in processing and thereby in product quality via process control. Protein refolding is known to be significantly impacted by critical process parameters and feed material attributes including composition and pH of the solubilisation and refolding buffers. Hence, to achieve robust process control and product quality, these attributes and parameters need to be monitored. This paper presents an approach towards statistical process control and monitoring of protein refolding, from buffer preparation to refold quenching, during manufacturing of therapeutic proteins from Escherichia coli based systems. The proposed approach utilises measurements of online redox potential, temperature, and pH for development of a statistical model. The model has then been integrated with LabView to permit real-time monitoring of the refolding process. The proposed system has been demonstrated to successfully identify process deviations and thereby enable process control for manufacturing product of consistent quality.     

Process analytical technology case study: Part II. Development and validation of quantitative near-infrared calibrations in support of a process analytical technology application for real-time release

This article is the second of a series of articles detailing the development of near-infrared (NIR) methods for solid dosage-form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to demonstrate a method for developing and validating NIR models for the analysis of active pharmaceutical ingredient (API) content and hardness of a solid dosage form. Robustness and cross-validation testing were used to optimize the API content and hardness models. For the API content calibration, the optimal model was determined as multiplicative scatter correction with Savitsky-Golay first-derivative preprocessing followed by partial least-squares (PLS) regression including 4 latent variables. API content calibration achieved root mean squared error (RMSE) and root mean square error of cross validation (RMSECV) of 1.48 and 1.80 mg, respectively. PLS regression and baseline-fit calibration models were compared for the prediction of tablet hardness. Based on robustness testing, PLS regression was selected for the final hardness model, with RMSE and RMSECV of 8.1 and 8.8 N, respectively. Validation testing indicated that API content and hardness of production-scale tablets is predicted with root mean square error of prediction of 1.04 mg and 8.5 N, respectively. Explicit robustness testing for high-flux noise and wavelength uncertainty demonstrated the robustness of the API concentration calibration model with respect to normal instrument operating conditions. Published: October 6, 2005 The views presented in this article do not necessarily reflect those of the Food and Drug Administration.     

Process analytical technology (PAT) for biopharmaceutical products: Part II. Concepts and applications

Implementing real‐time product quality control meets one or both of the key goals outlined in FDA's PAT guidance: “variability is managed by the process” and “product quality attributes can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental, and other conditions.” The first part of the paper presented an overview of PAT concepts and applications in the areas of upstream and downstream processing. In this second part, we present principles and case studies to illustrate implementation of PAT for drug product manufacturing, rapid microbiology, and chemometrics. We further present our thoughts on how PAT will be applied to biotech processes going forward. The role of PAT as an enabling component of the Quality by Design framework is highlighted. Integration of PAT with the principles stated in the ICH Q8, Q9, and Q10 guidance documents is also discussed. Biotechnol. Bioeng. 2010; 105: 285–295. Published 2009 Wiley Periodicals, Inc.     

Evaluation of manometric temperature measurement, a process analytical technology tool for freeze-drying: Part I, product temperature measurement

This study examines the factors that may cause systematic errors in the manometric temperature measurement (MTM) procedure used to evaluate product temperature during primary drying. MTM was conducted during primary drying using different vial loads, and the MTM product temperatures were compared with temperatures directly measured by thermocouples. To clarify the impact of freeze-drying load on MTM product temperatures, simulation of the MTM vapor pressure rise was performed, and the results were compared with the experimental results. The effect of product temperature heterogeneity in MTM product temperature determination was investigated by comparing the MTM product temperatures with directly measured thermocouple product temperatures in systems differing in temperature heterogeneity. Both the simulated and experimental results showed that at least 50 vials (5 mL) were needed to give sufficiently rapid pressure rise during the MTM data collection period (25 seconds) in the freeze dryer, to allow accurate determination of the product temperature. The product temperature is location dependent, with higher temperature for vials on the edge of the array and lower temperature for the vials in the center of the array. The product temperature heterogeneity is also dependent upon the freeze-drying conditions. In product temperature heterogeneous systems, MTM measures a temperature close to the coldest product temperature, even, if only a small fraction of the samples have the coldest product temperature. The MTM method is valid even at very low product temperature (−45°C). Published: February 10, 2006     

Process analytical technology case study part I: Feasibility studies for quantitative near-infrared method development

This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis. Published: October 6, 2005 The views presented in this article do not necessarily reflect those of the Food and Drug Administration.     

Application of Raman spectroscopy in monoclonal antibody producing continuous systems for downstream process intensification

Monoclonal antibodies (mAbs) are biopharmaceuticals produced by mammalian cell lines in bioreactors at a variety of scales. Cell engineering, media optimization, process monitoring, and control strategies for in vitro production have become crucial subjects to meet increasing demand for these high value pharmaceuticals. Raman Spectroscopy has gained great attention in the pharmaceutical industry for process monitoring and control to maintain quality assurance. For the first time, this article demonstrated the possibility of subclass independent quantitative mAb prediction by Raman spectroscopy in real time. The developed model estimated the concentrations of different mAb isotypes with average prediction errors of 0.2 (g/L) over the course of cell culture. In situ Raman spectroscopy combined with chemometric methods showed to be a useful predictive tool for monitoring of real time mAb concentrations in a permeate stream without sample removal. Raman spectroscopy can, therefore, be considered as a reliable process analytical technology tool for process monitor, control, and intensification of downstream continuous manufacturing. The presented results provide useful information for pharmaceutical industries to choose the most appropriate spectroscopic technology for their continuous processes.     

Process analytical technology case study,part III: Calibration monitoring and transfer

This is the third of a series of articles detailing the development of near-infrared spectroscopy methods for solid dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to develop a system for continuous calibration monitoring and formulate an appropriate strategy for calibration transfer. Indcators of high-flux noise (noise factor level) and wave-length uncertainty were developed. These measurements, in combination with Hotelling’s T² and Q residual, are used to continuously monitor instrument performance and model relevance. Four calibration transfer techniques were compared. Three established techniques, finite impulse response filtering, generalized least squares weighting, and piecewise direct standardization were evaluated. A fourth technique, baseline subtraction, was the most effective for calibration transfer. Using as few as 15 transfer samples, predictive capability of the analytical method was maintained across multiple instruments and major instrument maintenance.     

生物分子相互作用分析技术应用实例（四）——实时监测分子生物学过程

利用BIA技术来观察DNA之间的任何相互反应.包括：DNA的延长、连接和退火等.无需任何标记并可测定相互作用的动态参数.     

细石叶工艺产品废弃的文化过程研究

细石叶工艺产品是如何废弃的、受哪些因素影响、又如何在考古遗存中得到表现,这些都是我们面临的课题。本文从考古遗存废弃一般过程的理论研究着手,确定影响细石叶工艺产品的因素包括史前狩猎采集者的生计策略、废弃过程中人们的行为选择两个方面;与此同时结合细石叶工艺性质预测细石叶工艺产品可能的废弃方式;然后回到对经验材料点(籍箕滩遗址)与面(华北地区主要细石叶工艺遗址)相结合的分析。整体而言,华北含细石叶工艺产品诸遗址的废弃呈现出多样的形态,有迅速而预期返回的废弃方式(籍箕滩遗址),有计划且不准备返回的废弃方式(如泗涧遗址),有人类经常光顾但不留宿的遗址(如孟家泉遗址),还有废弃迅速的临时营地(如柿子滩遗址)和狩猎动物的望点(如大岗遗址)。