Block Diagram Explorer for Chemical System Modeling
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Solution Overview
Problem
Current methods for drug development and synthetic biology are time-consuming and costly due to the need for extensive laboratory experiments and clinical trials, often resulting in unforeseen side-effects and inefficiencies in modeling complex biological systems.
Innovation Solution
A modeling and simulation environment that allows users to construct and visualize chemical or biochemical systems, enabling the exploration of molecular interactions and dynamics through a block diagram explorer and simulation engine, facilitating the analysis of complex biological processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extensive laboratory experiments and clinical trials are conducted to develop new drugs, then the reliability of drug safety and efficacy is improved, but the time and cost required for drug development increases significantly
Solution Approach 1:
The patent applies preliminary action by conducting in-silico simulations and creating computational models of biological systems before performing actual laboratory experiments and clinical trials. These preliminary computational experiments allow researchers to predict drug behavior, identify potential side effects, and optimize drug candidates in silico, thereby reducing the need for extensive physical trials and accelerating the overall drug development timeline while maintaining safety and efficacy standards
2Reliability
If extensive laboratory experiments and clinical trials are conducted to develop new drugs, then the reliability of drug safety and efficacy is improved, but the cost of drug development increases significantly
Solution Approach 1:
The patent applies copying by creating virtual copies of biological systems through computational modeling and simulation. Instead of repeatedly conducting expensive physical experiments, researchers can simulate drug interactions with these virtual biological systems multiple times at minimal cost. The computational models replicate the behavior of actual biological systems, allowing extensive testing of drug candidates in silico before proceeding to physical experiments, thereby significantly reducing development costs while maintaining reliability
3Ease of operation
If the scope of experiments is narrowed to isolate the subsystem of interest, then the ease of data collection is improved, but the ability to detect unforeseen side effects deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the complex biological system into modular computational models representing different subsystems, tissues, or biological pathways. Researchers can selectively activate or deactivate specific modules in the simulation to study isolated mechanisms while still maintaining the ability to integrate multiple subsystems to predict system-wide side effects. This modular approach allows easy study of specific mechanisms while preserving comprehensive side effect detection capabilities through system integration
4Loss of information
If comprehensive data from all available sources are collected, then the completeness of system understanding is improved, but the difficulty of synthesizing relationships among data increases
Solution Approach 1:
The patent applies universality by developing a standardized computational framework and common data formats that can integrate diverse biological data sources (genomic, proteomic, metabolomic, clinical data) into a unified model. The modular architecture allows the same simulation engine to handle multiple data types and sources, automatically synthesizing relationships among them through standardized interaction rules. This universal framework reduces the complexity of data integration while maintaining comprehensive system understanding
Data Source
AI summary
A system for modeling, simulating and analyzing chemical and biochemical reactions includes a modeling environment for constructing a model of a chemical or biochemical system comprising a plurality of chemical reactions. The system also includes a simulation engine accepting as input said constructed model of the chemical or biochemical system and generating as output an expected result. The modeling environment includes a block diagram explorer for displaying a block diagram in a graphical user interface describing the system as a hierarchical network of interconnected blocks. Each block represents a species participating one of the chemical reactions or one of said chemical reactions in the system. The block diagram explorer allows for a user to manipulate and modify the graphical parameters of the block diagram representation to provide insight into the functionality and operation of the system being modeled.