Development and Qualification of a Scale-Down Mammalian Cell Culture Model and Application in Design Space Development by Definitive Screening Design.

Scale-down models are indispensable and crucial tools for process understanding and continuous process improvement in product life-cycle management. In this study, a scale-down model representing commercial-scale cell culture process of adalimumab biosimilar HS016 was first developed based on constant power per volume (P/V) principle and then qualified by multivariate data analysis (MVDA) and equivalence test method. The trajectories of the bench-scale process lie in the middle of the control range of large-scale process, built by multivariate evolution model based on nutrients, metabolites, and process performance datasets. This indicates that the small-scale process performance is comparable with that of the full-scale process. The final product titer, integrated viable cell density (iVCD), viability, aggregates, acid peak content, total afucosylation level, and high mannose content recognized as key process attributes (KPAs) or critical quality attributes (CQAs) were equivalent across the scales upon comparison using equivalence test method. The qualified scale-down model was then used for process characterization using a definitive screening design (DSD) where five independent variables including pH, shifted temperature, inoculation seeding density, viable cell density (VCD) at first feeding, VCD at temperature shift were evaluated. Three quadratic polynomial models for final product titer, aggregation, and high mannose were then established using the DSD results. The design space was finally developed using a probability-based Monte Carlo simulation method and was verified with the operation setpoint and worst-case condition. The case study presented in this report shows a feasible roadmap for cell culture process characterization.

Rapid analysis of the Tanreqing injection by near-infrared spectroscopy combined with least squares support vector machine and Gaussian process modeling techniques.

Near-infrared spectroscopy (NIRS) combined with chemometrics was used to analyze the main active ingredients including chlorogenic acid, caffeic acid, luteoloside, baicalin, ursodesoxycholic acid, and chenodeoxycholic acid in the Tanreqing injection. In this paper, first, two hundred samples collected in the product line were divided into the calibration set and prediction set, and the reference values were determined by the High Performance Liquid Chromatography- Diode Array Detector/Evaporative Light Scattering Detector (HPLC-DAD/ELSD) method. Partial least squares (PLS) analysis was implemented as a linear method for models calibrated with different preprocessing means. Wavelet transformation (WT) was introduced as a variable selection technique by means of multiscale decomposition, and wavelet coefficients were employed as the input for modeling. Furthermore, two nonlinear approaches, least squares support vector machine (LS-SVM) and Gaussian process (GP), were applied to exploit the complicated relationship between the spectra and active ingredients. The optimal models for each ingredient were obtained by LS-SVM and GP methods. The performance of the final models was evaluated by the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (R). All of the models in the paper give a good calibration ability with an R value above 0.92, and the prediction ability is also satisfactory, with an R value higher than 0.85. The overall results demonstrate that nonlinear models are more stable and predictable than linear ones, and they will be more suitable for the CHM system when high accuracy analysis is required. It can be concluded that NIRS with the LS-SVM and GP modeling methods is promising for the implementation of process analytical technology (PAT) in the pharmaceutical industry of Chinese herbal injections (CHIs).

Optimization of a Coupling Process for Insulin Degludec According to a Quality by Design (QbD) Paradigm.

This case study described a successful application of the quality by design (QbD) principles to a coupling process development of insulin degludec. Failure mode effects analysis (FMEA) risk analysis was first used to recognize critical process parameters (CPPs). Five CPPs, including coupling temperature (Temp), pH of desB30 solution (pH), reaction time (Time), desB30 concentration (Conc), and molar equivalent of ester per mole of desB30 insulin (MolE), were then investigated using a fractional factorial design. The curvature effect was found significant, indicating the requirement of second-order models. Afterwards, a central composite design was built with an augmented star and center points study. Regression models were developed for the CPPs to predict the purity and yield of predegludec using above experimental data. The R2 and adjusted R2 were higher than 96 and 93% for the two models respectively. The Q2 values were more than 80% indicating a good predictive ability of models. MolE was found to be the most significant factor affecting both yield and purity of predegludec. Temp, pH, and Conc were also significant for predegludec purity, while Time appeared to remarkably influence the yield model. The multi-dimensional design space and normal operating region (NOR) with a robust setpoint were determined using a probability-based Monte-Carlo simulation method. The verified experimental results showed that the design space was reliable and effective. This study enriches the understanding of acetylation process and is instructional to other complicated operations in biopharmaceutical engineering.

[Research progress on method validation of near infrared spectroscopy in quantitative analysis].

Due to the advantages of fast and noninvasive, requiring almost no sample preparation, supplying chemical and physical information, near infrared (NIR) spectroscopy is widely used in the pharmaceutical industry. In the life cycle of an established analytical method, rigorous validation should be performed before routine use. However,there is no detailed experimental standards or decision rules for the NIR methods validation currently, and various approaches were applied to validate the established NIR quantification models in literatures.In this paper, progress on the validation of NIR methods developed for the pharmaceutical application was reviewed, concentrating on the standard documents and main ideas of validation.It will provide references for the standardized application of NIR spectroscopy in the pharmaceutical industries.

[Chinese medicine industry 4.0：advancing digital pharmaceutical manufacture toward intelligent pharmaceutical manufacture].

A perspective analysis on the technological innovation in pharmaceutical engineering of Chinese medicine unveils a vision on "Future Factory" of Chinese medicine industry in mind. The strategy as well as the technical roadmap of "Chinese medicine industry 4.0" is proposed, with the projection of related core technology system. It is clarified that the technical development path of Chinese medicine industry from digital manufacture to intelligent manufacture. On the basis of precisely defining technical terms such as process control, on-line detection and process quality monitoring for Chinese medicine manufacture, the technical concepts and characteristics of intelligent pharmaceutical manufacture as well as digital pharmaceutical manufacture are elaborated. Promoting wide applications of digital manufacturing technology of Chinese medicine is strongly recommended. Through completely informationized manufacturing processes and multi-discipline cluster innovation, intelligent manufacturing technology of Chinese medicine should be developed, which would provide a new driving force for Chinese medicine industry in technology upgrade, product quality enhancement and efficiency improvement.

Design space development for the extraction process of Danhong injection using a Monte Carlo simulation method.

A design space approach was applied to optimize the extraction process of Danhong injection. Dry matter yield and the yields of five active ingredients were selected as process critical quality attributes (CQAs). Extraction number, extraction time, and the mass ratio of water and material (W/M ratio) were selected as critical process parameters (CPPs). Quadratic models between CPPs and CQAs were developed with determination coefficients higher than 0.94. Active ingredient yields and dry matter yield increased as the extraction number increased. Monte-Carlo simulation with models established using a stepwise regression method was applied to calculate the probability-based design space. Step length showed little effect on the calculation results. Higher simulation number led to results with lower dispersion. Data generated in a Monte Carlo simulation following a normal distribution led to a design space with a smaller size. An optimized calculation condition was obtained with 10,000 simulation times, 0.01 calculation step length, a significance level value of 0.35 for adding or removing terms in a stepwise regression, and a normal distribution for data generation. The design space with a probability higher than 0.95 to attain the CQA criteria was calculated and verified successfully. Normal operating ranges of 8.2-10 g/g of W/M ratio, 1.25-1.63 h of extraction time, and two extractions were recommended. The optimized calculation conditions can conveniently be used in design space development for other pharmaceutical processes.

[Innovation guidelines and strategies for pharmaceutical engineering of Chinese medicine and their industrial translation].

This paper briefly analyzes the bottlenecks and major technical requirements for pharmaceutical industry of Chinese medicine, providing current status of pharmaceutical engineering of Chinese medicine. The innovation directions and strategies of the pharmaceutical engineering for manufacturing Chinese medicine are proposed along with the framework of their core technology. As a consequence, the development of the third-generation pharmaceutical technology for Chinese medicine, featured as "precision, digital and intelligent", is recommended. The prospects of the pharmaceutical technology are also forecasted.

A study on the use of near-infrared spectroscopy for the rapid quantification of major compounds in Tanreqing injection.

In this paper we describe the strategy used in the development and validation of a near infrared spectroscopy method for the rapid determination of baicalin, chlorogenic acid, ursodeoxycholic acid (UDCA), chenodeoxycholic acid (CDCA), and the total solid contents (TSCs) in the Tanreqing injection. To increase the representativeness of calibration sample set, a concentrating-diluting method was adopted to artificially prepare samples. Partial least square regression (PLSR) was used to establish calibration models, with which the five quality indicators can be determined with satisfied accuracy and repeatability. In addition, the slope/bias (S/B) method was used for the models transfer between two different types of NIR instruments from the same manufacturer, which is contributing to enlarge the application range of the established models. With the presented method, a great deal of time, effort and money can be saved when large amounts of Tanreqing injection samples need to be analyzed in a relatively short period of time, which is of great significance to the traditional Chinese medicine (TCM) industries.

[Strategy and core technologies for the secondary development of Chinese patent medicine].

Secondary development of Chinese Patent Medicine (CPM) is an effective and innovation-driven way for the leaping development of Chinese medicine industry with less investment and faster return. Aim to improving the efficacy, safety and batch-to-batch consistency of CPMs, the theory and methodology for the secondary development of CPMs, mode for cultivating superior CPM, approaches to reforming the pharmaceutical technology and the corresponding core technologies were proposed in this paper, which is summarized as 'One objective, Three analyses, Five definitudes and Seven improvements'.

Direct analysis in real time mass spectrometry and multivariate data analysis: a novel approach to rapid identification of analytical markers for quality control of traditional Chinese medicine preparation.

The paper presents a novel strategy to identify analytical markers of traditional Chinese medicine preparation (TCMP) rapidly via direct analysis in real time mass spectrometry (DART-MS). A commonly used TCMP, Danshen injection, was employed as a model. The optimal analysis conditions were achieved by measuring the contribution of various experimental parameters to the mass spectra. Salvianolic acids and saccharides were simultaneously determined within a single 1-min DART-MS run. Furthermore, spectra of Danshen injections supplied by five manufacturers were processed with principal component analysis (PCA). Obvious clustering was observed in the PCA score plot, and candidate markers were recognized from the contribution plots of PCA. The suitability of potential markers was then confirmed by contrasting with the results of traditional analysis methods. Using this strategy, fructose, glucose, sucrose, protocatechuic aldehyde and salvianolic acid A were rapidly identified as the markers of Danshen injections. The combination of DART-MS with PCA provides a reliable approach to the identification of analytical markers for quality control of TCMP.

A high throughput chemiluminescence method for determination of chemical oxygen demand in waters.

A novel and high throughput chemiluminescence (CL) method for determination of chemical oxygen demand (COD) in water sample was originally developed based on potassium permanganate-glutaraldehyde CL system. With this method, dissolved organic matter in water samples was digested by excess acid potassium permanganate, the reacted mixture solutions containing surplus KMnO(4) were added in wells of a 96-well plate, followed by injection of glutaraldehyde in the wells, and CL was then produced along with the reaction of the added glutaraldehyde with the surplus KMnO(4) and detected by a photomultiplier tube (PMT). The difference (DeltaI) between the CL intensity for distilled water and that for sample water was proportional to the COD value of water sample. The calibration graph was linear in the range of 0.16-19.24 mg L(-1) with a detection limit of 0.1 mg L(-1). A complete analysis could be performed in 40 min including digestion and detection, giving a very high throughput of 3 x 96 samples in about 60 min. Compared with the conventional methods, this method is simple and sensitive and consumes very limited and cheap reagents. Owing to its rapid, automatic, high throughput and low cost characteristics, the presented CL method has been applied successfully to the determination of COD in real water samples (n=32) with satisfactory results.