Pharmaceutical Platform for TCM Formula Active-Ingredient Discovery
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Solution Overview
Problem
The complexity and variability of Traditional Chinese Medicine (TCM) formulas, coupled with a lack of clinical evidence and understanding of active constituents, pharmacokinetic properties, and interactions, hinder the development of pharmaceutical products that maintain the therapeutic benefits of TCM.
Innovation Solution
A pharmaceutical platform technology (PPT-II) utilizing in silico methodologies, systems biology, systems pharmacology, bioinformatics, and machine learning to identify and quantify active and contributing ingredients in herbal formulas, incorporating in vitro models and analytical units to predict drug-like properties and interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional TCM formulas are used, then therapeutic benefits are maintained, but complexity and variability hinder pharmaceutical development
Solution Approach 1:
The patent segments the complex TCM formula into individual active constituents and their specific functions. By analyzing and separating the roles of different ingredients (emperor, assistant, facilitator, guide), the system transforms the holistic complex formula into manageable components that can be systematically evaluated and reproduced in pharmaceutical development.
Solution Approach 2:
The patent introduces computational models and data mining techniques as intermediaries between traditional TCM knowledge and modern pharmaceutical requirements. These intermediaries process complex formula data, predict active constituents, and bridge the gap between traditional therapeutic benefits and modern development standards.
2Loss of information
If comprehensive analysis of active constituents is performed, then understanding of mechanisms improves, but time and resources are consumed
Solution Approach 1:
The patent performs preliminary computational analysis and data mining to identify potential active constituents and their mechanisms before conducting extensive experimental research. By pre-screening and predicting active ingredients using available data, the system reduces the time and resources needed for subsequent experimental verification.
Solution Approach 2:
The patent creates computational models that replicate and simulate the effects of TCM formulas and their constituents. These in silico models allow researchers to study mechanisms and interactions virtually, reducing the need for time-consuming physical experiments while maintaining comprehensive understanding.
3Reliability
If clinical trials are conducted to verify therapeutic values, then evidence is generated, but extensive sampling and trials are required
Solution Approach 1:
The patent develops computational models that simulate clinical outcomes and predict therapeutic effects before actual clinical trials. These in silico models create virtual copies of clinical scenarios, allowing extensive sampling and trial requirements to be reduced while still generating reliable clinical evidence through validated predictions.
Solution Approach 2:
The patent implements feedback mechanisms where computational models continuously refine their predictions based on available data. By iteratively improving models with feedback from preliminary studies and existing literature, the system reduces the quantity of sampling needed in subsequent clinical trials while maintaining high reliability of evidence.
4Measurement precision
If pharmacokinetic properties are predicted using animal models, then drug-like properties are assessed, but applicability to humans is limited
Solution Approach 1:
The patent changes the parameters and models used for pharmacokinetic predictions from animal-based to human-based physiological parameters. By adjusting models to reflect human-specific characteristics such as metabolism, absorption, and distribution parameters, the system improves both measurement precision and human applicability simultaneously.
Data Source
AI summary
In one embodiment, the present invention describes a method for identifying an optimized natural medicine containing defined doses of active and contributing ingredients. In one embodiment, the method disclosed in the present invention develops compositions comprising cannabinoids for the treatment of hepatocellular carcinoma.