As one of the major product clusters on the BDE.top platform, BDE-Herb is used for the discovery of active molecules in traditional Chinese medicine (TCM) and herbs based on deep learning model, clinical analysis of TCM prescriptions (medicinal materials), clinical evaluation of active molecules, druggability analysis, molecular generation or optimization, and process research.
INNOVATIVE DISCOVERY OF TCM AND HERBAL DRUGS
BDE-Herb is an AI platform of active and effective molecular drug discovery and design for TCM researchers. It is based on the company's big data accumulation of traditional Chinese medicine clinical, development of algorithmic models and the global frontier scientific and clinical research experience of TCM. It includes discovery of active molecules, clinical analysis of TCM prescriptions (medicinal materials), clinical evaluation of active molecules, druggability analysis, molecular generation or optimization, process research and molecular virtual sieve, generation, optimization and other functions are designed to help TCM and herb researchers simplify and shorten the time of drug development.
TCM / Herb Clinical Study
BDE-Herb is an AI powered unique and efficient clinical research platform for TCM / herbs based on large-scale research literature, clinical patents, clinical research records, and other data related to TCM prescriptions and medicinal herbs, comprehensively analyzing the effective clinical composition of TCM from three levels: prescriptions, medicinal herbs, and ingredients.
Research on Active Molecules of TCM / Herbal Medicine
A series of AI algorithm models have been constructed based on machine learning and deep learning techniques for systematic research and analysis of over 100K component compounds in large-scale compound and medicinal herbs. These models are used for predicting active molecules in compound and medicinal herbs, predicting the pharmacological properties of active molecules, optimizing, generating and predicting active molecule targets, and providing comprehensive information on the pharmacokinetics of active compounds related to TCM.
Compound Active Molecule Prediction: A compound active molecule prediction model based on a large amount of Chinese herbal compound molecular data.
Prediction of Active Molecules in Medicinal Herbs：A prediction model for active molecules in medicinal herbs based on a large amount of molecular data of medicinal herbs and compounds.
Prediction of Active Molecular Pharmacochemical Properties：A prediction model for active molecular properties based on existing compound property data, including ADMET, etc.
Active Molecule Optimization：Optimizing active molecules for better clinical properties.
Active Molecule Generation: A molecular generation model based on known effective active molecules to generate active molecules with similar or even better properties, in order to break through patent protection barriers.
Active Molecular Target Prediction: A compound target interaction prediction model based on existing data to predict the target of active molecules.
Compound Clinical Research
BDE-Herb systematically constructs the relationship between traditional Chinese medicine prescriptions and the clinical efficacy of various diseases based on a deep learning model, selects effective prescriptions for specific diseases, and achieves precise prescription customization.
It constructs a relationship model between compound and clinical efficacy based on data related to compound clinical research.
Clinical Research on Medicinal Materials
BDE-Herb systematically constructs the relationship between traditional Chinese medicine and the clinical efficacy of various diseases, constructs a large-scale herbal disease adaptive population relationship graph, and provides rapid retrieval and inference of clinical characteristics of medicinal materials.
It builds a relationship model between medicinal herbs and clinical efficacy based on data related to clinical research on medicinal herbs.
BDE-Herb constructs a component compound disease population relationship map, providing detailed information on the clinical characteristics of effective active ingredients and comparative analysis results.
It constructs a relationship model between TCM ingredients and clinical efficacy based on data related to clinical research on TCM ingredients, accurately determines the important components in the compound with model based principle analysis, identifies the main components in TCM with model based principle analysis, conducts prediction and analysis of compound properties, compound optimization, compound generation and prediction of compound targets.
Research on Active Ingredients