Application of Online Near Infrared for Process Understanding of Spray-Drying Solution Preparation

Online monitoring for extraction of Tibetan medicine Meconopsis quintuplinervia regel. Based on near infrared spectroscopy coupled with chemometrics

The extraction process plays a crucial role in the production of Tibetan medicines. This study focused on assembling a set of online near-infrared (NIR) spectroscopy detection devices for the extraction of medicinal herbs. The original infrared device was transformed into an online detection system. After evaluating the stability of the system, we applied online NIR spectroscopy monitoring to the flavonoid contents (total flavonoids, quercetin-3-O-sophoroside, and luteolin) of Meconopsis quintuplinervia Regel. during the ultrasonic extraction process and determined the extraction endpoint. Nine batches of samples were employed to construct quantitative and discriminant models, half of the remaining two batches of samples are used for external verification. Our research shows that the residual predictive deviation (RPD) values of total flavonoids, quercetin-3-O-sophoroside and luteolin models exceeded 2.5. The R values for external verification of the three ingredients were above 0.9, with RPD values generally exceeding 2 and RSEP values within 10 %, demonstrating the model's strong predictive performance. Most of the extraction endpoints of the flavonoid components in M. quintuplinervia ranged from 18 to 58 min, with high consistency between the predicted extraction endpoints of the external validation, suggesting accurate determination of extraction endpoints based on predicted values. This study can provide a reference for the online NIR spectroscopy quality monitoring of the extraction process of Chinese and Tibetan herbs.

Application of digital-intelligence technology in the processing of Chinese materia medica

Processing of Chinese Materia Medica (PCMM) is the concentrated embodiment, which is the core of Chinese unique traditional pharmaceutical technology. The processing includes the preparation steps such as cleansing, cutting and stir-frying, to make certain impacts on the quality and efficacy of Chinese botanical drugs. The rapid development of new computer digital technologies, such as big data analysis, Internet of Things (IoT), blockchain and cloud computing artificial intelligence, has promoted the rapid development of traditional pharmaceutical manufacturing industry with digitalization and intellectualization. In this review, the application of digital intelligence technology in the PCMM was analyzed and discussed, which hopefully promoted the standardization of the process and secured the quality of botanical drugs decoction pieces. Through the intellectualization and the digitization of production, safety and effectiveness of clinical use of traditional Chinese medicine (TCM) decoction pieces were ensured. This review also provided a theoretical basis for further technical upgrading and high-quality development of TCM industry.

Application of digital-intelligence technology in the processing of Chinese materia medica

Processing of Chinese Materia Medica (PCMM) is the concentrated embodiment, which is the core of Chinese unique traditional pharmaceutical technology. The processing includes the preparation steps such as cleansing, cutting and stir-frying, to make certain impacts on the quality and efficacy of Chinese botanical drugs. The rapid development of new computer digital technologies, such as big data analysis, Internet of Things (IoT), blockchain and cloud computing artificial intelligence, has promoted the rapid development of traditional pharmaceutical manufacturing industry with digitalization and intellectualization. In this review, the application of digital intelligence technology in the PCMM was analyzed and discussed, which hopefully promoted the standardization of the process and secured the quality of botanical drugs decoction pieces. Through the intellectualization and the digitization of production, safety and effectiveness of clinical use of traditional Chinese medicine (TCM) decoction pieces were ensured. This review also provided a theoretical basis for further technical upgrading and high-quality development of TCM industry.

Stabilizing vaccines via drying: Quality by design considerations

Pandemics and epidemics are continually challenging human beings' health and imposing major stresses on the societies particularly over the last few decades, when their frequency has increased significantly. Protecting humans from multiple diseases is best achieved through vaccination. However, vaccines thermal instability has always been a hurdle in their widespread application, especially in less developed countries. Furthermore, insufficient vaccine processing capacity is also a major challenge for global vaccination programs. Continuous drying of vaccine formulations is one of the potential solutions to these challenges. This review highlights the challenges on implementing the continuous drying techniques for drying vaccines. The conventional drying methods, emerging technologies and their adaptation by biopharmaceutical industry are investigated considering the patented technologies for drying of vaccines. Moreover, the current progress in applying Quality by Design (QbD) in each of the drying techniques considering the critical quality attributes (CQAs), critical process parameters (CPPs) are comprehensively reviewed. An expert advice is presented on the required actions to be taken within the biopharmaceutical industry to move towards continuous stabilization of vaccines in the realm of QbD.

Engineering Advances in Spray Drying for Pharmaceuticals

Spray drying is a versatile technology that has been applied widely in the chemical, food, and, most recently, pharmaceutical industries. This review focuses on engineering advances and the most significant applications of spray drying for pharmaceuticals. An in-depth view of the process and its use is provided for amorphous solid dispersions, a major, growing drug-delivery approach. Enhanced understanding of the relationship of spray-drying process parameters to final product quality attributes has made robust product development possible to address a wide range of pharmaceutical problem statements. Formulation and process optimization have leveraged the knowledge gained as the technology has matured, enabling improved process development from early feasibility screening through commercial applications. Spray drying's use for approved small-molecule oral products is highlighted, as are emerging applications specific to delivery of biologics and non-oral delivery of dry powders. Based on the changing landscape of the industry, significant future opportunities exist for pharmaceutical spray drying.

Novel NIR modeling design and assignment in process quality control of Honeysuckle flower by QbD

Honeysuckle flower is a common edible-medicinal food with significant anti-inflammatory efficacy. Process quality control of its ethanol precipitation is a topical issue in the pharmaceutical field. Near infrared (NIR) spectroscopy is commonly used for process quality analysis. However, establishing a robust and reliable quantitative model of complex process remains a challenge in industrial applications of NIR. In this paper, modeling design based on quality by design concept (QbD) was implemented for the ethanol precipitation process quality control of Honeysuckle flower. According to the 56 models' performances and 25 contour plots, quadratic model was the best with R_adj² increasing from 0.1395 to 0.9085, indicating the strong interaction among spectral pre-processing methods, variable selection methods, and latent factors. SG9 and CARS was an appropriate combination for modeling. Furthermore, spectral assignment method was creatively introduced for variable selection. Another 56 models' performances and 25 contour plots were established. Compared with the chemometric variable selection method, spectral assignment combined with QbD concept made a higher R_pre² and a lower RMSEP. When the latent factors of PLS was small, R_pre² of the model by spectral assignment increased from 0.9605 to 0.9916 and RMSEP decreased from 0.1555 mg/mL to 0.07134 mg/mL. This result suggests that the variable selected by spectral assignment is more representative and precise. This provided a novel modeling guideline for process quality control in PAT.