Publications by authors named "Shun-Nan Zhang"

Article Synopsis
  • Intelligent manufacturing technologies have significantly impacted traditional Chinese medicine (TCM) industries but struggle with unstructured data, like research reports and production records.
  • Generative artificial intelligence (AI) has shown promise in managing unstructured data, offering tools for information extraction, knowledge generation, and semantic retrieval within the TCM sector.
  • The study identifies four key applications of generative AI in TCM: a knowledge base, on-the-job training, production quality control, and supply chain management, while proposing the idea of a "smart industrial brain" to enhance AI integration in TCM manufacturing.
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Article Synopsis
  • * Currently, there are challenges in understanding TCM extraction methods and utilizing data effectively, which impede advancements in the industry.
  • * The article discusses major technological challenges in TCM extraction and reviews data-driven approaches for improving extraction processes, including analysis, optimization, online detection, control, and management.
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Owing to the advancement in pharmaceutical technology, traditional Chinese medicine industry has seen rapid development. Preferring conventional manufacturing mode, pharmaceutical enterprises of traditional Chinese medicine have no effective process detection tools and process control methods. As a result, the quality of the final products mainly depends on testing and the quality is inconsistent in the same batch.

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To realize the real-time monitoring of the production process of Yangxue Qingnao Granules and improve the inter-batch consistency of granule quality in the granulation process, this study established a near-infrared quantitative prediction model of moisture, particle size, bulk density, and angle of repose in the fluidized bed granulation process of Yangxue Qingnao Granules based on near-infrared spectroscopy(NIRS). The near-infrared spectra were collected from 355 samples in 12 batches in the granulation process by integrating the sphere detection module of the near-infrared spectrometer. In combination with the pretreatment methods such as the first derivative, multiplicative scatter correction(MSC), and standard normal variate(SNV), the model was established by partial least squares(PLS) regression.

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The mixing process is one of the key operation units for solid preparation of traditional Chinese medicine. The physical properties such as particle size, density and viscosity of the mixture are key factors that need to be controlled, which will directly affect the performance of the preparation molding process and product quality. Subsequent dripping process performance and appearance qua-lity of dripping pills will be affected by dynamic viscosity of materials in the mixing process.

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China healthcare industry has gradually developed the consumer-centric integrated service model. To satisfy consumers' increasing demands on pluralistic, personalized and transparent healthcare services, pharmaceutical manufacturing enterprises must provide high-quality, precise and flexible medicines. This can be achieved by accelerating implementation of intelligent manufacturing, which is the core competitiveness of pharmaceutical manufacturing enterprises.

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This study, based on the findings for Perilla resources, aimed to describe the species, distribution, importance, features, utilization and status of quantitative Perilla resources in China. This not only helps people to know well about the existing resources and researching development, but also indicates the overall distribution, selection and rational use of Perilla resource in the future. According to the output types, Perilla resources are divided into two categories: wild resources and cultivated resources; and based on its common uses, the cultivated resources are further divided into medicine resources, seed-used resources and export resources.

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