Intelligent co-design of material, process, and equipment for manufacturing high-quality traditional Chinese medicine preparations / 中国中药杂志

In the context of Pharma 4.0, the design tools that support the pharmaceutical Quality by Design(QbD) are iterating fast toward intelligent or smart design. The conventional development methods for traditional Chinese medicine(TCM) preparations have the limitations such as over dependence on experience, low dimensions for the designed experiment parameters, poor compatibility between the process and equipment, and high trial-and-error cost during process scale-up. Therefore, this paper innovatively proposed the intelligent co-design involving material, process, and equipment for manufacturing high-quality TCM preparations, and introduced the design philosophy, targets, tools, and applications with TCM oral solid dosage(OSD) as an example. In terms of design philosophy, the pharmaceutical design tetrahedron composed of critical material attributes, critical process parameters, critical equipment attributes, and critical quality attributes was developed. The design targets were put forward based on the product performance classification system. The design tools involve a design platform that contains several modules, such a as the iTCM material database, the processing route classification system, the system modeling and simulation, and reliability-based optimization. The roles of different modules in obtaining essential and universal design knowledge of the key common manufacturing units were introduced. At last, the applications of the co-design methodology involving material, process, and equipment in the high shear wet granulation process development and the improvement of the dissolving or dispersion capability of TCM formula granules are illustrated. The research on advanced pharmaceutical design theory and methodology will help enhance the efficiency and reliability of drug development, improve the product quality, and promote the innovation of high-end TCM products across the industry.

Research Advances in Musculoskeletal Biomechanical Modeling in 2021 / 医用生物力学

Biomechanical model of musculoskeletal system has accurate human anatomy and good biological fidelity. It can accurately and effectively reveal the biomechanical state and predict the internal mechanical response of musculoskeletal system. Therefore, it has been widely used in biomechanical study of musculoskeletal system, diagnosis and treatment of bone diseases, implant optimization design and preoperative planning. In 2021, the latest advances in biomechanical modeling method of musculoskeletal system mainly included three aspects, i.e., individualized finite element modeling, statistical model modeling and musculoskeletal system modeling. On this basis, the latest relevant literatures were summarized in this review to illustrate the progress and main applications of the above modeling method, and the future development direction of musculoskeletal modeling was discussed.

Key technologies and applications of industrial big data in manufacturing of Chinese medicine / 中国中药杂志

Along with the striding of the Chinese medicine(CM) manufacturing toward the Industry 4.0, some digital factories have accumulated lightweight industrial big data, which become part of the enterprise assets. These digital assets possess the possibility of solving the problems within the CM production system, like the Sigma gap and the poverty of manufacturing knowledge. From the holistic perspective, a three-tiered architecture of CM industrial big data is put forward, and it consists of the data integration layer, the data analysis layer and the application scenarios layer. In data integration layer, sensing of CM critical quality attributes is the key technology for big data collection. In data analysis and mining layer, the self-developed iTCM algorithm library and model library are introduced to facilitate the implementation of the model lifecycle methodologies, including process model development, model validation, model configuration and model maintenance. The CM quality transfer structure is closely related with the connection mode of multiple production units. The system modeling technologies, such as the partition-integration modeling method, the expanding modeling method and path modeling method, are key to mapping the structure of real manufacturing system. It is pointed out that advance modeling approaches that combine the first-principles driven and data driven technologies are promising in the future. At last, real-world applications of CM industrial big data in manufacturing of injections, oral solid dosages, and formula particles are presented. It is shown that the industrial big data can help process diagnosis, quality forming mechanism interpretations, real time release testing method development and intelligent product formulation design. As renewable resources, the CM industrial big data enable the manufacturing knowledge accumulation and product quality improvement, laying the foundation of intelligent manufacturing.

Web-based neuromuscular simulator applied to the teaching of principles of neuroscience

INTRODUCTION: The learning of core concepts in neuroscience can be reinforced by a hands-on approach, either experimental or computer-based. In this work, we present a web-based multi-scale neuromuscular simulator that is being used as a teaching aid in a campus-wide course on the Principles of Neuroscience. METHODS: The simulator has several built-in individual models based on cat and human biophysics, which are interconnected to represent part of the neuromuscular system that controls leg muscles. Examples of such elements are i) single neurons, representing either motor neurons or interneurons mediating reciprocal, recurrent and Ib inhibition; ii) afferent fibers that can be stimulated to generate spinal reflexes; iii) muscle unit models, generating force and electromyogram; and iv) stochastic inputs, representing the descending volitional motor drive. RESULTS: Several application examples are provided in the present report, ranging from studies of individual neuron responses to the collective action of many motor units controlling muscle force generation. A subset of them was included in an optional homework assignment for Neuroscience and Biomedical Engineering graduate students enrolled in the course cited above at our University. Almost all students rated the simulator as a good or an excellent learning tool, and approximately 90% declared that they would use the simulator in future projects. CONCLUSION: The results allow us to conclude that multi-scale neuromuscular simulator is an effective teaching tool. Special features of this free teaching resource are its direct usability from any browser (http://remoto.leb.usp.br/), its user-friendly graphical user interface (GUI) and the preset demonstrations.

Drug targets discovery based on dynamic signal transduction networks / 药学学报

Since last century, drug discovery efforts mostly focus on searching for chemicals which can inhibit some specific steps in a well-described disease pathway. However, this kind of highly specific inhibitors can not be effective for complex diseases, like cancer, diabetes, schizophrenia and mental illness. Therefore, we need to rethink the drug discovery and therapeutic strategies. In this review, the strategies of selection of cellular signal transduction networks and their dynamics as the targets for drug discovery and pharmacological treatments will be discussed. The properties and analytical methods of these signal transduction networks, internet sources and software tools for performing these strategies will be described. Strategies and procedures of using network- based drug discovery will be emphasized, including multi-targets drug design and network-based drug discovery.