scholarly journals Raw Material Variability and Its Impact on the Online Adaptive Control of Cohesive Powder Blend Homogeneity Using NIR Spectroscopy

Processes ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 568 ◽  
Author(s):  
Guolin Shi ◽  
Bing Xu ◽  
Zhiqiang Zhang ◽  
Chan Yang ◽  
Shengyun Dai ◽  
...  
Keyword(s):  
Latent Variable ◽  
Near Infrared ◽  
Process Analytical Technology ◽  
Nir Spectroscopy ◽  
Active Pharmaceutical Ingredient ◽  
Raw Material ◽  
Critical Material ◽  
Critical Material Attributes ◽  
Blending Process ◽  
Cohesive Powders

It is significant to analyze the blend homogeneity of cohesive powders during pharmaceutical manufacturing in order to provide the exact content of the active pharmaceutical ingredient (API) for each individual dose unit. In this paper, an online monitoring platform using an MEMS near infrared (NIR) sensor was designed to control the bin blending process of cohesive powders. The state of blend homogeneity was detected by an adaptive algorithm, which was calibration free. The online control procedures and algorithm’s parameters were fine-tuned through six pilot experiments and were successfully transferred to the industrial production. The reliability of homogeneity detection results was validated by 16 commercial scale experiments using 16 kinds of natural product powders (NPPs), respectively. Furthermore, 19 physical quality attributes of all NPPs and the excipient were fully characterized. The blending end time was used to denote the degree of difficulty of blending. The empirical relationships between variability of NPPs and the blending end time were captured by latent variable modeling. The critical material attributes (CMAs) affecting the blending process were identified as the particle shape and flowability descriptors of cohesive powders. Under the framework of quality by design (QbD) and process analytical technology (PAT), the online NIR spectroscopy together with the powder characterization facilitated a deeper understanding of the mixing process.

scholarly journals Application of near-infrared spectroscopy for the rapid analysis ofLonicerae Japonicae Flossolution extracted by water

2014 ◽  
Vol 07 (04) ◽  
pp. 1350063 ◽  
Author(s):  
Xue Xiao ◽  
Jinfang Ma ◽  
Fahuan Ge ◽  
Xiangdong Zhang ◽  
Huihua Yang ◽  
...  
Keyword(s):  
Chlorogenic Acid ◽  
Standard Error ◽  
Latent Variable ◽  
High Performance ◽  
Near Infrared ◽  
Process Analytical Technology ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Variable Number ◽  
Array Detection

A rapid quantitative analytical method for three components of Lonicerae Japonicae Flos solution (Lonicera Japonica Thumb.) extracted by water was developed using near-infrared (NIR) spectroscopy and the partial least-squares (PLS) method. The NIR spectra of 81 samples collected from a production line were obtained. The concentrations of secologanic acid, chlorogenic acid and galuteolin were determined by using high-performance liquid chromatography-diode array detection as the reference method. Several pretreatment methods for the NIR spectra were used during PLS calibration. The most appropriate latent variable number of the PLS factor was selected based on the standard error of cross-validation (SECV). The performance of the final PLS models was evaluated according to SECV, standard error of prediction (SEP) and determination coefficient (R2). The compounds secologanic acid, chlorogenic acid and galuteolin had SEP values of 0.030, 0.061 and 1.668 μg/mL, respectively and R2values over 0.85. This work shows that NIR spectroscopy is a rapid and convenient method for the analysis of Lonicerae Japonicae Flos solution extracted by water. The proposed method can help in the application of process analytical technology in the pharmaceutical industry, particularly in traditional Chinese medicine injections.

Focusing near Infrared Spectroscopy on the Business Objectives of Modern Pharmaceutical Production

1998 ◽  
Vol 6 (A) ◽  
pp. A13-A19 ◽  
Author(s):  
T.G. Axon ◽  
R. Brown ◽  
S.V. Hammond ◽  
S.J. Maris ◽  
F. Ting
Keyword(s):  
High Performance ◽  
Near Infrared ◽  
Real Life ◽  
Nir Spectroscopy ◽  
Raw Material ◽  
Develop Model ◽  
Data Sets ◽  
Total Quality ◽  
Model Free ◽  
Pharmaceutical Production

The early use of near infrared (NIR) spectroscopy in the pharmaceutical industry was for raw material identification, later moving on to some conventional “calibrations” for various ingredients in a variety of sample types. The approach throughout this development process has always been “conventional” with one measurement by NIR directly replacing some other slower method, be it Mid-IR identification, or determinations by Karl Fischer, high performance liquid chromatography (HPLC)etc. A significant change in approach was demonstrated by Plugge and Van der Vlies1 in 1993, where a qualitative system was used to provide “quantitative like” answers for potency of a drug substance. Following on from that key paper, there has been a realisation that the qualitative analysis ability of NIR, has the potential to be a powerful tool for process investigation, control and validation. The final step has been to develop “model free” approaches, that consider individual data sets as unique systems, and present the opportunity for NIR to escape the shackles of “calibration” in one form or another. The use of qualitative, or model free, approaches to NIR spectroscopy provides an effective tool for satisfying many of the demands of modern pharmaceutical production. “Straight through production,” “right first time,” “short cycle time” and “total quality management” philosophies can be realised. Eventually the prospect of parametric release may be materialised with a strong contribution from NIR spectroscopy. This paper will illustrate the above points with some real life examles.

Estimation of Eucalyptus delegatensis wood properties by near infrared spectroscopy

2001 ◽  
Vol 31 (10) ◽  
pp. 1671-1675 ◽  
Author(s):  
L R Schimleck ◽  
R Evans ◽  
J Ilic
Keyword(s):  
Large Scale ◽  
Near Infrared ◽  
Microfibril Angle ◽  
Nir Spectroscopy ◽  
Wood Properties ◽  
Raw Material ◽  
Modulus Of Rupture ◽  
Single Type ◽  
Wide Range ◽  
Eucalyptus Delegatensis

The use of calibrated near infrared (NIR) spectroscopy for the prediction of a range solid wood properties is described. The methods developed are applicable to large-scale nondestructive forest resource assessment and to tree breeding and silvicultural programs. A series of Eucalyptus delegatensis R.T. Baker (alpine ash) samples were characterized in terms of density, longitudinal modulus of elasticity (EL), microfibril angle (MFA), and modulus of rupture (MOR). NIR spectra were obtained from the radial–longitudinal face of each sample and used to generate calibrations for the measured physical properties. The relationships were good in all cases, with coefficients of determination ranging from 0.77 for MOR through 0.90 for EL to 0.93 for stick density. In view of the rapidly expanding range of applications for this technique, it is concluded that appropriately calibrated NIR spectroscopy could form the basis of a "universal" testing instrument capable of predicting a wide range of product properties from a single type of spectrum obtained from the product or from the raw material.

Evaluation of Soya Bean Quality for Tofu Processing by near Infrared Spectroscopy

1998 ◽  
Vol 6 (A) ◽  
pp. A325-A328
Author(s):  
T.L. Hong ◽  
Samson C.S. Tsou ◽  
S.-J. Tsai
Keyword(s):  
Water Absorption ◽  
Absorption Rate ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Soya Bean ◽  
Control Measures ◽  
Raw Material ◽  
Prolonged Storage ◽  
Tannin Content ◽  
Water Absorption Rate

Soya bean, as the raw material for tofu processing, is required to be of high quality. The variety characteristics, storage conditions and harvesting seasons of soya bean are the major contributors to soya bean quality. This study attempted to use near infrared (NIR) spectroscopy to evaluate the processing quality of soya bean. Evaluation models using NIR spectroscopy were developed for the analyses of tannin content, degrees of lipid oxidation, detection of harvest seasons and measurement of water absorption rate. Simulation experiments demonstrated that these models were not only able to analyse major compositions of soya bean, but also to sort out soya bean samples and their suitability for tofu making regardless of various defects, such as high tannin content, low water absorption rate, prolonged storage and unfavourable harvest seasons. Statistic analysis suggested that these models could be used as mass-screening techniques for breeding programmes and quality control measures in tofu-processing factories.

scholarly journals Applications of Statistical Tools for Optimization and Development of Smart Drug Delivery System

2021 ◽  
Author(s):  
Pankaj Sharma
Keyword(s):  
Dosage Form ◽  
Quality By Design ◽  
Process Analytical Technology ◽  
Quality Attributes ◽  
Critical Material ◽  
Statistical Tools ◽  
Pharmaceutical Dosage Form ◽  
Critical Quality Attributes ◽  
Critical Material Attributes ◽  
Form Development

In the novel dosage form development, quality is the key criterion in pharmaceutical industry. The quality by design tools used for development of the quality products with tight specification and rigid process. The specifications of statistical tools are essentially based upon critical process parameters (CPPs), critical material attributes (CMAs), and critical quality attributes (CQAs) for the development of quality products. The application of quality by design in pharmaceutical dosage form development is systematic, requiring multivariate experiments employing process analytical technology (PAT) and other experiments to recognize critical quality attributes depend upon risk assessments (RAs). The quality by design is a modern technique to stabilize the quality of pharmaceutical dosage form. The elements of quality by design such as process analytical techniques, risk assessment, and design of experiment support for assurance of the strategy control for every dosage form with a choice of regular monitoring and enhancement for a quality dosage form. This chapter represents the concepts and applications of the most common screening of designs/experiments, comparative experiments, response surface methodology, and regression analysis. The data collected from the dosage form designing during laboratory experiments, provide the substructure for pivotal or pilot scale development. Statistical tools help not only in understanding and identifying CMAs and CPPs in product designing, but also in comprehension of the role and relationship between these in attaining a target quality. Although, the implementation of statistical approaches in the development of dosage form is strongly recommended.

scholarly journals An Updated Risk Assessment as Part of the QbD-Based Liposome Design and Development

Pharmaceutics ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1071
Author(s):  
Zsófia Németh ◽  
Edina Pallagi ◽  
Dorina Gabriella Dobó ◽  
Gábor Kozma ◽  
Zoltán Kónya ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Active Pharmaceutical Ingredient ◽  
Experimental Models ◽  
Phospholipid Content ◽  
Formulation Development ◽  
Critical Material ◽  
Critical Material Attributes ◽  
Critical Process Parameters ◽  
Saline Solutions ◽  
Phosphate Buffered Saline

Liposomal formulation development is a challenging process. Certain factors have a critical influence on the characteristics of the liposomes, and even the relevant properties can vary based on the predefined interests of the research. In this paper, a Quality by Design-guided and Risk Assessment (RA)-based study was performed to determine the Critical Material Attributes and the Critical Process Parameters of an “intermediate” active pharmaceutical ingredient-free liposome formulation prepared via the thin-film hydration method, collect the Critical Quality Attributes of the future carrier system and show the process of narrowing a general initial RA for a specific case. The theoretical liposome design was proved through experimental models. The investigated critical factors covered the working temperature, the ratio between the wall-forming agents (phosphatidylcholine and cholesterol), the PEGylated phospholipid content (DPPE-PEG2000), the type of the hydration media (saline or phosphate-buffered saline solutions) and the cryoprotectants (glucose, sorbitol or trehalose). The characterisation results (size, surface charge, thermodynamic behaviours, formed structure and bonds) of the prepared liposomes supported the outcomes of the updated RA. The findings can be used as a basis for a particular study with specified circumstances.

scholarly journals SDAE-BP Based Octane Number Soft Sensor Using Near-infrared Spectroscopy in Gasoline Blending Process

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 770 ◽  
Author(s):  
Ying Tian ◽  
Xinyu You ◽  
Xiuhui Huang
Keyword(s):  
Real Time ◽  
Octane Number ◽  
Near Infrared ◽  
Back Propagation ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Soft Sensor ◽  
Training Time ◽  
Sensor Model ◽  
Blending Process

As the most important properties in the gasoline blending process, octane number is difficult to be measured in real time. To address this problem, a novel deep learning based soft sensor strategy, by using the near-infrared (NIR) spectroscopy obtained in the gasoline blending process, is proposed. First, as a network structure with hidden layer as symmetry axis, input layer and output layer as symmetric, the denosing auto-encoder (DAE) realizes the advanced expression of input. Additionally, the stacked DAE (SDAE) is trained based on unlabeled NIR and the weights in each DAE is recorded. Then, the recorded weights are used as the initial parameters of back propagation (BP) with the reason that the SDAE trained initial weights can avoid local minimums and realizes accelerate convergence, and the soft sensor model is achieved with labeled NIR data. Finally, the achieved soft sensor model is used to estimate the real time octane number. The performance of the method is demonstrated through the NIR dataset of gasoline, which was collected from a real gasoline blending process. Compared with PCA-BP (the dimension of datasets of BP reduced by principal component analysis) soft sensor model, the prediction accuracy was improved from 86.4% of PCA-BP to 94.8%, and the training time decreased from 20.1 s to 16.9 s. Therefore, SDAE-BP is proposed as a novel method for rapid and efficient determination of octane number in the gasoline blending process.

scholarly journals Near-Infrared Spectroscopy as a Process Analytical Technology Tool for Monitoring the Steaming Process of Gastrodiae rhizoma with Multiparameters and Chemometrics

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yamin Zuo ◽  
Jing Yang ◽  
Chen Li ◽  
Xuehua Deng ◽  
Shengsheng Zhang ◽  
...  
Keyword(s):  
Near Infrared ◽  
Multivariate Calibration ◽  
Process Analytical Technology ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Great Promise ◽  
Gastrodiae Rhizoma ◽  
Mean Square Errors ◽  
Analytical Technology ◽  
Hydroxybenzyl Alcohol

Steaming is a vital unit operation in traditional Chinese medicine (TCM), which greatly affects the active ingredients and the pharmacological efficacy of the products. Near-infrared (NIR) spectroscopy has already been widely used as a strong process analytical technology (PAT) tool. In this study, the potential usage of NIR spectroscopy to monitor the steaming process of Gastrodiae rhizoma was explored. About 10 lab scale batches were employed to construct quantitative models to determine four chemical ingredients and moisture change during the steaming process. Gastrodin, p-hydroxybenzyl alcohol, parishin B, and parishin A were modeled by different multivariate calibration models (SMLR and PLS), while the content of the moisture was modeled by principal component regression (PCR). In the optimized models, the root mean square errors of prediction (RMSEP) for gastrodin, p-hydroxybenzyl alcohol, parishin B, parishin A, and moisture were 0.0181, 0.0143, 0.0132, 0.0244, and 2.15, respectively, and correlation coefficients ( R p 2 ) were 0.9591, 0.9307, 0.9309, 0.9277, and 0.9201, respectively. Three other batches’ results revealed that the accuracy of the model was acceptable and that was specific for next drying step. In addition, the results demonstrated the method was reliable in process performance and robustness. This method holds a great promise to replace current subjective color judgment and time-consuming HPLC or UV/Vis methods and is suitable for rapid online monitoring and quality control in the TCM industrial steaming process.

scholarly journals In-situ monitoring of saccharides removal of alcohol precipitation using near-infrared spectroscopy

2018 ◽  
Vol 11 (05) ◽  
pp. 1850027 ◽  
Author(s):  
Hongxia Huang ◽  
Haibin Qu
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Process Analytical Technology ◽  
Nir Spectroscopy ◽  
In Situ Monitoring ◽  
Mean Square ◽  
Model Errors ◽  
Precipitation Processes ◽  
Mean Square Errors

As unsafe components in herbal medicine (HM), saccharides can affect not only the drug appearance and stabilization, but also the drug efficacy and safety. The present study focuses on the in-line monitoring of batch alcohol precipitation processes for saccharide removal using near-infrared (NIR) spectroscopy. NIR spectra in the 4000–10,000-cm[Formula: see text] wavelength range are acquired in situ using a transflectance probe. These directly acquired spectra allow characterization of the dynamic variation tendency of saccharides during alcohol precipitation. Calibration models based on partial least squares (PLS) regression have been developed for the three saccharide impurities, namely glucose, fructose, and sucrose. Model errors are estimated as the root-mean-square errors of cross-validation (RMSECVs) of internal validation and root-mean-square errors of prediction (RMSEPs) of external validation. The RMSECV values of glucose, fructose, and sucrose were 1.150, 1.535, and 3.067[Formula: see text]mg[Formula: see text]mL[Formula: see text], and the RMSEP values were 0.711, 1.547, and 3.740[Formula: see text][Formula: see text], respectively. The correlation coefficients [Formula: see text] between the NIR predictive and the reference measurement values were all above 0.94. Furthermore, NIR predictions based on the constructed models improved our understanding of sugar removal and helped develop a control strategy for alcohol precipitation. The results demonstrate that, as an alternative process analytical technology (PAT) tool for monitoring batch alcohol precipitation processes, NIR spectroscopy is advantageous for both efficient determination of quality characteristics (fast, in situ, and requiring no toxic reagents) and process stability, and evaluating the repeatability.

scholarly journals Characterization of herbal powder blends homogeneity using near-infrared spectroscopy

2014 ◽  
Vol 07 (06) ◽  
pp. 1450004 ◽  
Author(s):  
Wenlong Li ◽  
Haibin Qu
Keyword(s):  
High Performance ◽  
Near Infrared ◽  
Fiber Optic ◽  
Nir Spectroscopy ◽  
Fiber Optic Probe ◽  
Liquid Chromatograph ◽  
Noninvasive Technique ◽  
Correlation Spectrum ◽  
Blending Process ◽  
Optic Probe

Homogeneity of powder blend is essential to obtain uniform contents for the tablets and capsules. Near-infrared (NIR) spectroscopy with fiber-optic probe was used as an on-line technique for monitoring the homogeneity of pharmaceutical blend during the blending process instead of the traditional techniques, such as high performance liquid chromatograph (HPLC) method. In this paper NIRS with a SabIR diffuse reflectance fiber-optic probe was used to monitor the blending process of coptis powder and lactose (excipient) with different contents, and further qualitative methods, like similarity, moving block of standard deviation and mean square were used for calculation purposes with the collected spectra after the pretreatment of multiplicative signal correction (MSC) and second derivative. Correlation spectrum was used for the wavelength selection. Four different coptis were blended with lactose separately to validate the proposed method, and the blending process of "liu wei di huang" pill was also simulated in bottles to verify this method on multiple herbal blends. The overall results suggest that NIRS is a simple, effective and noninvasive technique can be successfully applied to the determination of homogeneity in the herbal blend.

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