New traditional Chinese medicine conversion management and intelligent decision support system and method

Abstract

The invention provides a new traditional Chinese medicine conversion management and intelligent decision support system and method, and the method comprises the following specific steps: S1, building an intelligent conversion platform: carrying out the demand analysis and planning: determining the main functions of the platform, and understanding the main demands of traditional Chinese medicine research and development institutions, enterprises and hospitals, an intelligent transformation platform is created to integrate, screen and optimize the new traditional Chinese medicine transformation process, potential medicine targets and action mechanisms are rapidly mined by using big data analysis and an artificial intelligence algorithm, the research and development cycle is shortened, compounds with potential activity are rapidly screened out by using an AI computer simulation technology built in the platform, and the method is suitable for large-scale popularization and application. The workload of experimental screening is reduced, the research and development efficiency is improved, meanwhile, the whole intelligent platform is assisted by multiple intelligent algorithms, and the conversion effect of new traditional Chinese medicine is greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of drug development, and specifically to a traditional Chinese medicine new drug transformation management and intelligent decision-making support system and method. Background Art

[0002] The transformation of traditional Chinese medicine (TCM) new drugs refers to the process of promoting TCM research results from the laboratory stage to clinical application and marketable products. This process involves multiple links, including basic research, drug development, clinical trials, registration and approval, production and marketing, etc. The goal of TCM new drug transformation is to ensure the safety and effectiveness of TCM and transform it into drugs that can benefit patients;

[0003] The transformation of TCM new drugs is the process of promoting TCM research results from the laboratory to clinical application and marketable products, involving multiple links such as basic research, drug development, clinical trials, registration and approval, production and marketing, etc. Through the application of multidisciplinary collaboration, data integration, quality control and intelligent technologies, the transformation of TCM new drugs can be accelerated to benefit patients;

[0004] The low efficiency of TCM new drug transformation is one of the main challenges faced by the current TCM R & D field. The traditional TCM new drug R & D process is complex, has a long cycle, high costs, and there are many bottlenecks. TCM usually contains multiple components, and its mechanism of action is complex. The traditional experimental methods for screening active ingredients are time-consuming and laborious. Secondly, the characteristics of multiple components and multiple targets of TCM make it difficult to clarify its mechanism of action, affecting subsequent R & D. And intelligent technologies (such as artificial intelligence, big data, automated experiments, etc.) can significantly improve the efficiency of TCM new drug transformation. Therefore, there is a need for a TCM new drug transformation management and intelligent decision-making support system and method to overcome the defects in the prior art. Summary of the Invention

[0005] (1) Technical Problems to be Solved

[0006] In view of the deficiencies of the prior art, the present invention provides a traditional Chinese medicine new drug transformation management and intelligent decision-making support system and method, which solves the problems of the complex, long-cycle, high-cost traditional Chinese medicine new drug R & D process and many bottlenecks.

[0007] (2) Technical Solutions

[0008] To achieve the above objectives, the present invention is realized through the following technical solutions: A traditional Chinese medicine new drug transformation management and intelligent decision-making support method includes the following specific steps:

[0009] S1. Create an intelligent transformation platform:

[0010] (1) Requirement analysis and planning: Determine the main functions of the platform and understand the main requirements of TCM R & D institutions, enterprises and hospitals;

[0011] (2) Platform function design: Ensure that the platform has functions for project progress, task assignment, and resource management, and at the same time supports the sharing and analysis of experimental and clinical data;

[0012] (3) Technical architecture: Set up cloud computing and big data processing technologies inside the platform, and build in AI for algorithm assistance;

[0013] (4) Platform development and testing: After creation, conduct tests on functions and security performance, and gradually develop corresponding function modules;

[0014] S2. Integrate the data for the research and development of traditional Chinese medicine new drugs:

[0015] (1) Medical staff upload existing experimental data, clinical data, literature data, and market data, remove duplicate, incorrect, and invalid data, and store the screened data in a NoSQL database;

[0016] (2) Analyze the data through the built-in AI technology for drug screening, drug prediction, and toxicity assessment to provide research and development suggestions;

[0017] S3. Data-driven decision support: Provide data-driven decision support through the big data analysis of the built-in Tableau software;

[0018] S4. Screen the active ingredients in multi-source data: Obtain chemical composition information from the database, integrate multi-source data into a unified platform to ensure the standardization of data formats, then use pharmacodynamics rules to preliminarily screen potential active ingredients. Secondly, use CNN to analyze the relationship between molecular structure and pharmacodynamics. Finally, use NLP technology to extract active ingredient information from the database;

[0019] S5. Optimize the research and development process: Optimize the above analysis results through AI, so as to optimize the research and development process;

[0020] S6. Optimize the experimental results: Conduct clinical trials based on the above scientific data, and during the clinical trial process, be able to use historical clinical trial data to optimize the experimental effect and reduce the failure rate of the experiment;

[0021] S7. Result upload and storage: Upload the clinical trial results to the information database inside the platform for storage;

[0022] S8. Monitor the new drug research and development process through the transformation platform: In the subsequent research and development process, monitor the key parameters in new drug production through Internet of Things, sensors, and artificial intelligence technologies. The entire process from collection, screening, decision-making for research and development, successful research and development to mass production is recorded on the transformation platform, and assisted by artificial intelligence algorithms, which can provide high efficiency for research and development;

[0023] S9. Intelligent assistance through artificial algorithms: Use TCMSP to integrate and screen traditional Chinese medicine components, use KNIME to integrate and analyze multi-source data of traditional Chinese medicine, mine potential active ingredients, use PYTHON to build a prediction model to analyze the relationship between traditional Chinese medicine components and pharmacodynamic effects, use KEGG to study the impact of traditional Chinese medicine components on disease-related pathways, use MEdi data and TriNetX to optimize the clinical trials of new traditional Chinese medicine drugs, recruit subjects to optimize the experimental plan, and finally use AWS to store and analyze traditional Chinese medicine R & D data and support AI model training.

[0024] Preferably, the intelligent transformation platform in S1 is encrypted using the BGV algorithm, which belongs to the fully homomorphic encryption algorithm and allows specific calculations to be performed on ciphertext. The calculation result after decryption is the same as the result of performing the same calculation on plaintext. It can be used to perform operations such as statistical analysis on encrypted new traditional Chinese medicine drug data without revealing data privacy, providing support for the secure sharing and collaboration of data.

[0025] A system based on the method for the transformation management and intelligent decision support of a new traditional Chinese medicine drug includes a database module, an AI algorithm module, and a security encryption module. Among them, the database module can integrate and screen the active ingredients and information in traditional Chinese medicine, and the AI algorithm module can optimize the entire development and experimental process of new traditional Chinese medicine drugs. Secondly, the security encryption module can ensure the security of the entire intelligent transformation platform for new traditional Chinese medicine drugs, preventing the risk of experimental results being stolen and leaked.

[0026] (III) Beneficial effects

[0027] The present invention provides a system and method for the transformation management and intelligent decision support of a new traditional Chinese medicine drug, having the following beneficial effects:

[0028] 1. The present invention creates an intelligent transformation platform to integrate, screen, and optimize the process of new traditional Chinese medicine drug transformation. Using big data analysis and artificial intelligence algorithms, it quickly mines potential drug targets and mechanisms of action, shortening the R & D cycle. The built-in AI computer simulation technology in the platform quickly screens out compounds with potential activity, reducing the workload of experimental screening and improving R & D efficiency. At the same time, the entire intelligent platform is assisted by a variety of intelligent algorithms, greatly improving the transformation effect of new traditional Chinese medicine drugs. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is the overall flowchart of a system and method for the transformation management and intelligent decision support of a new traditional Chinese medicine drug proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] Next, in combination with the accompanying drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0031] Embodiment:

[0032] As Figure 1 shown, the embodiment of the present invention provides a method for the transformation management and intelligent decision-making support of traditional Chinese medicine new drugs, including the following specific steps:

[0033] S1. Create an intelligent transformation platform:

[0034] (1) Requirement analysis and planning: Determine the main functions of the platform, understand the main requirements of traditional Chinese medicine research and development institutions, enterprises, and hospitals, and clarify the function modules and development plans of the platform;

[0035] (2) Platform function design: Ensure that the platform has functions such as project progress, task allocation, and resource management, and at the same time support the sharing and analysis of experimental and clinical data, and provide information such as the approval process of traditional Chinese medicine new drugs and regulatory policies;

[0036] (3) Technical architecture: Set up cloud computing and big data processing technologies inside the platform, and build in AI for algorithm assistance;

[0037] (4) Development and testing of the platform: After creation, conduct tests on functions and security performance, and gradually develop corresponding function modules, and regularly update and repair vulnerabilities;

[0038] S2. Integrate the research and development data of traditional Chinese medicine new drugs:

[0039] (1) Medical staff upload existing experimental data, clinical data, literature data, and market data, remove duplicate, incorrect, and invalid data, store the screened data in a NoSQL database, and establish a data directory for easy user retrieval;

[0040] (2) Analyze the data through the built-in AI technology to conduct drug screening, drug prediction, and toxicity assessment to provide research and development suggestions, and at the same time use AI mining technology to discover potential new drug candidates;

[0041] S3. Driving Support for Data Decision-Making: Provide data-driven decision-making support through big data analysis of the built-in Tableau software. The specific operation method is as follows: Open the Tableau software, select the corresponding data source type through the "Data" menu, such as databases, Excel files, CSV files, etc. After entering the connection information, you can connect to the big data source. Use the data cleaning function of Tableau to handle missing values, outliers, etc., and data transformation can also be performed, such as calculating new fields and grouping data, to prepare for subsequent analysis. Drag the data fields to the "Rows", "Columns", "Marks" and other functional areas of Tableau to quickly create visual charts such as bar charts, line charts, pie charts, scatter plots, etc., to intuitively understand the distribution, trends and relationships of the data. Use the drill-down function of Tableau to drill down from summary data to detailed data. You can also quickly filter out the data subsets of interest through filters for more detailed analysis;

[0042] S4. Screening Effective Components from Multi-Source Data: Obtain chemical component information from the database, integrate multi-source data onto a unified platform to ensure the standardization of data formats. Then, use pharmacodynamic rules to preliminarily screen potential effective components. Secondly, use CNN to analyze the relationship between molecular structure and pharmacodynamics. Finally, use NLP technology to extract effective component information from the database;

[0043] S5. Optimizing the R & D Process: Optimize the above analysis results through AI, so as to optimize the R & D process. Integrate multi-omics data such as gene expression, protein expression, metabolites, etc. after the action of traditional Chinese medicine, and use AI algorithms for analysis to reveal the mechanism of action of traditional Chinese medicine at the molecular level, providing theoretical support for new drug R & D. Use AI to construct a biological network of traditional Chinese medicine-target-disease, analyze the relationships between various nodes in the network, and clarify the multi-target and multi-pathway action characteristics of traditional Chinese medicine, providing a basis for the R & D of compound new drugs;

[0044] S6. Optimizing Experimental Results: Conduct clinical trials based on the above scientific data, and during the clinical trial process, historical clinical trial data can be used to optimize the experimental effect and reduce the failure rate of the experiment;

[0045] S7. Uploading and Saving Results: Upload the clinical trial results to the information database within the platform for storage;

[0046] S8. Monitoring the New Drug R & D Process through the Transformation Platform: During the subsequent R & D process, monitor the key parameters in new drug production through the Internet of Things, sensors and artificial intelligence technologies. The entire process from collection, screening, decision-making for R & D, successful R & D to mass production is recorded on the transformation platform, and assisted by artificial intelligence algorithms, which can provide high efficiency for R & D;

[0047] S9. Intelligent assistance through artificial algorithms: Use TCMSP to integrate and screen traditional Chinese medicine ingredients, use KNIME to integrate and analyze multi-source data of traditional Chinese medicine, mine potential active ingredients, use PYTHON to build a prediction model to analyze the relationship between traditional Chinese medicine ingredients and efficacy, use KEGG to study the impact of traditional Chinese medicine ingredients on disease-related pathways, use MEdi data and TriNetX to optimize the clinical trials of new traditional Chinese medicine drugs, recruit subjects to optimize the experimental plan, and finally use AWS to store and analyze traditional Chinese medicine R & D data and support AI model training.

[0048] The intelligent transformation platform in S1 is encrypted using the BGV algorithm, which belongs to a fully homomorphic encryption algorithm that allows specific calculations to be performed on ciphertext, and the calculation results after decryption are the same as those obtained by performing the same calculations on plaintext. It can be used to perform operations such as statistical analysis on encrypted new traditional Chinese medicine drug data without revealing data privacy, providing support for the secure sharing and collaboration of data.

[0049] A system based on the method for the transformation management and intelligent decision support of a new traditional Chinese medicine drug includes a database module, an AI algorithm module, and a security encryption module. Among them, the database module can integrate and screen the active ingredients and information in traditional Chinese medicine, and the AI algorithm module can optimize the entire development and experimental process of new traditional Chinese medicine drugs. Secondly, the security encryption module can ensure the security of the entire intelligent transformation platform for new traditional Chinese medicine drugs and prevent the risk of experimental results being stolen or leaked.

[0050] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for the transformation management and intelligent decision support of a new traditional Chinese medicine, characterized in that, The specific steps include: S1. Create an intelligent conversion platform: (1) Demand analysis and planning: determine the main functions of the platform and understand the main needs of TCM R&D institutions, enterprises, and hospitals; (2) Platform function design: Ensure that the platform has the functions of project progress, task allocation, and resource management, while supporting the sharing and analysis of experimental and clinical data; (3) Technical architecture: Cloud computing and big data processing technologies are set up within the platform, and AI is built in for algorithm assistance; (4) Platform development and testing: After the creation is completed, the functionality and security performance are tested, and the corresponding functional modules are gradually developed; S2. Integrate the research and development data of new Chinese medicines: (1) Medical personnel upload existing experimental data, clinical data, literature data, and market data, remove duplicate, erroneous, and invalid data, and store the filtered data in a NoSQL database; (2) Analyze data through built-in AI technology to conduct drug screening, drug prediction, and toxicity assessment to provide R&D recommendations; S3. Data-driven decision support: Provide data-driven decision support through big data analysis of built-in Tableau software; S4. Screening active ingredients from multi-source data: Obtain chemical component information from the database, integrate multi-source data into a unified platform, ensure the standardization of data format, then use pharmacodynamic rules to preliminarily screen potential active ingredients, then use CNN to analyze the relationship between molecular structure and drug efficacy, and finally use NLP technology to extract active ingredient information from the database; S5. Optimize the R&D process: Optimize the above analysis results through AI, so as to optimize the R&D process; S6. Optimize experimental results: Conduct clinical trials based on the above scientific data, and during the clinical trials, use historical clinical trial data to optimize experimental results and reduce the failure rate of the experiments; S7. Upload and save results: upload clinical trial results to the information database within the platform for storage; S8. Monitor the new drug R&D process through the transformation platform: In the subsequent R&D process, the Internet of Things, sensors and artificial intelligence technologies are used to monitor the key parameters in the production of new drugs. The entire process from collection, screening, R&D decision, successful R&D and batch production is recorded on the transformation platform, and assisted by artificial intelligence algorithms, which can provide high efficiency for R&D; S9. Intelligent assistance through artificial algorithms: Use TCMSP to integrate and screen Chinese medicine ingredients, use KNIME to integrate and analyze multi-source data of Chinese medicine, explore potential effective ingredients, use PYTHON to build prediction models, analyze the relationship between Chinese medicine ingredients and efficacy, use KEGG to study the impact of Chinese medicine ingredients on disease-related pathways, use MEdidata and TriNetX to optimize clinical trials of new Chinese medicines, recruit subjects to optimize experimental plans, and finally use AWS to store and analyze Chinese medicine R&D data and support AI model training.

2. The method for traditional Chinese medicine new drug transformation management and intelligent decision-making support according to claim 1, wherein: The intelligent transformation platform in S1 uses the BGV algorithm for encryption. This algorithm belongs to the fully homomorphic encryption algorithm, which allows specific calculations to be performed on ciphertext. The calculation results are consistent with those obtained by performing the same calculations on plaintext after decryption. It can be used to perform operations such as statistical analysis on encrypted traditional Chinese medicine new drug data without revealing data privacy, providing support for the secure sharing and collaboration of data.

3. A system for a traditional Chinese medicine new drug transformation management and intelligent decision-making support method according to any one of claims 1-2, characterized in that, It includes a database module, an AI algorithm module, and a security encryption module. Among them, the database module can integrate and screen the active ingredients and information in traditional Chinese medicine, and the AI algorithm module can optimize the entire development and experimental process of traditional Chinese medicine new drugs. Secondly, the security encryption module can ensure the security of the entire intelligent transformation platform for traditional Chinese medicine new drugs, preventing the risk of experimental results being stolen and leaked.

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