Multi-scale Biological Simulation for Heart Models
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Solution Overview
Problem
Current biological simulation techniques, such as those simulating cardiomyocyte and heart models, face challenges in achieving accurate results due to the use of average models for small structures like sarcomeres, leading to inaccuracies in understanding the interactions between organs and cells.
Innovation Solution
A biological simulation program and device that utilize multi-scale analysis by employing macro, meso, and micro models, with processors calculating behaviors at each scale, performing non-linear equation linearization using the Newton-Raphson method and Schur complement calculations to achieve accurate multi-scale analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If average models are used for simulating small structures like sarcomeres, then the device complexity is reduced, but the measurement precision of simulation results deteriorates
Solution Approach 1:
The patent divides the biological system into multiple hierarchical scales: organ level (heart), cell level (cardiomyocyte), and subcellular level (sarcomere). Each scale is modeled separately with appropriate detail, allowing accurate representation of small structures without requiring the entire system to be overly complex. The multi-scale modeling framework enables precise simulation of sarcomeres while maintaining manageable overall system complexity.
2Measurement precision
If multi-scale analysis with detailed models is performed, then the measurement precision of simulation results is improved, but the productivity of simulation computation deteriorates
Solution Approach 1:
The computation is segmented across different spatial and temporal scales. The organ-level model operates at a coarser resolution with larger time steps, while cell and subcellular models use finer resolutions with smaller time steps. This segmentation allows the system to achieve high precision where needed without applying fine-grained computation everywhere, thus maintaining overall computational efficiency.
Solution Approach 2:
The patent applies detailed multi-scale modeling only to specific regions and structures where high precision is critical (e.g., sarcomeres in regions of interest), while using coarser models in other areas. This partial application of detailed action achieves necessary accuracy without the excessive computational cost of applying fine-grained models throughout the entire system.
Data Source
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AI summary
A biological simulation method includes calculating a behavior of a material contained in a cell of an organ of a biological body, calculating a behavior of the cell based on the calculated behavior of the material, calculating a behavior of the organ based on the calculated behavior of the cell, reflecting the calculated behavior of the organ to the behavior of the cell, and reflecting the behavior of the cell to which the behavior of the organ has been reflected to the behavior of the material.