Development and validation of in-line near-infrared spectroscopy based analytical method for commercial production of a botanical drug product

Zhang, Shunnan; Xiong, Haoshu; Zhou, Lihong; Ju, Wei; Yang, Zhexuan; Ke, Yan; Yan, Binjun; Qu, Haibin

doi:10.1016/j.jpba.2019.06.046

Cited by 13 publications

(6 citation statements)

References 20 publications

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“…It is observed that calculated values are very similar to the RMSEE values which indicates the validity of the three models to accurately predict excluded samples. However, results may indicate a possibility of overfitting (Zhang et al, 2019).…”

Section: The Development and Validation Of The Raman Based Pat Methodsmentioning

confidence: 98%

“…Therefore, whilst several investigations have developed inline method for drug quantification purposes, very few have considered the feasibility of validating the established methods (De Leersnyder et al, 2018;Hubert et al, 2007;Saerens et al, 2014b;Zhang et al, 2019). A NIR based PAT method was developed and validated for the production of a drug product (Zhang et al, 2019). All validation parameters were calculated with the exception of precision which was considered unachievable.…”

Section: The Development and Validation Of The Raman Based Pat Methodsmentioning

confidence: 99%

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The development and validation of a quality by design based process analytical tool for the inline quantification of Ramipril during hot-melt extrusion

Dadou

Senta-Loys

Almajaan

et al. 2020

International Journal of Pharmaceutics

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Section: The Development and Validation Of The Raman Based Pat Methodsmentioning

confidence: 98%

Section: The Development and Validation Of The Raman Based Pat Methodsmentioning

confidence: 99%

The development and validation of a quality by design based process analytical tool for the inline quantification of Ramipril during hot-melt extrusion

Dadou

Senta-Loys

Almajaan

et al. 2020

International Journal of Pharmaceutics

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“…The use of NIR in process controls [142] is increasingly common and is has been reported in applications such as the manufacturing of botanical drug products. This class of products has intrinsic variability in the raw materials and ingredients may undergo complex chemical reactions during production.…”

Section: Nir In Food and Pharmaceutical Raw Materialsmentioning

confidence: 99%

“…This class of products has intrinsic variability in the raw materials and ingredients may undergo complex chemical reactions during production. This makes it imperative to perform real-time monitoring of the reactions, such as in the case of production of compound danshen dripping pill (CDDP) reported by Zhang et al [142], where an in-line NIR method was developed for commercial production of the botanical product. In almost all in-line/at-line/on-line applications the NIR method requires careful development and validation.…”

Section: Nir In Food and Pharmaceutical Raw Materialsmentioning

confidence: 99%

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Bwambok

Siraj

Macchi

et al. 2020

Sensors

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Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.

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“…3,4 The NIR quantitative model is crucial in its applications. 5,6 For building the NIR quantitative calibration models, multivariate calibration methods, such as multiple linear regression (MLR), principal component regression (PCR), and partial least squares (PLS) regression are used. In the quantitative analysis of the target components in traditional Chinese medicine, PLS regression is most widely applied method to rapidly predict the target components' contents.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of variable selection methods coupled with partial least squares regression to determine the target component in solid samples

Zhao

et al. 2022

Journal of Near Infrared Spectroscopy

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Variable selection can improve the robustness and prediction accuracy of partial least squares (PLS) regression models and decrease the calculation time by selecting the optimal subset of variables in multivariate calibration. In this study, the performance of two variable selection methods for wavelength interval and individual wavelength coupled with partial least squares regression are investigated by employing the experimental data of asiaticoside (AS) and madecassoside (MS) contents in centella total glucosides (CTG) and a public dataset of corn. The studied variable selection methods include interval partial least squares regression ( iPLS), backward interval partial least squares ( biPLS), synergy interval partial least squares regression ( siPLS), competitive adaptive reweighted sampling (CARS), uninformative variable elimination (UVE) and variable importance in projection (VIP). The results show that the implementation of variable selection methods improved the performance of the model compared with full-spectrum modeling. All variable selection methods improved the prediction of AS or MS contents in CTG. When latent variables for PLS models are less than 10 in the practical application, the RPD value of AS models by iPLS method is 7.5, and the RPD value of MS models by biPLS method is 2.9. The results of wavelength interval selection are better than individual wavelength selection, especially for iPLS and biPLS. The same results were obtained with the public data for moisture in corn, and the RPD value of biPLS model of moisture is 1.6. Therefore, the wavelength interval selection methods, such as iPLS or biPLS, are appropriate for improving the PLS model’s accuracy and robustness to determine the target components’ contents in solid samples.

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Development and validation of in-line near-infrared spectroscopy based analytical method for commercial production of a botanical drug product

Cited by 13 publications

References 20 publications

The development and validation of a quality by design based process analytical tool for the inline quantification of Ramipril during hot-melt extrusion

The development and validation of a quality by design based process analytical tool for the inline quantification of Ramipril during hot-melt extrusion

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Performance evaluation of variable selection methods coupled with partial least squares regression to determine the target component in solid samples

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