Cell-Centric Simulation Ontogeny Engine for Biological Modeling
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Solution Overview
Problem
Current in silico simulation systems for biological events suffer from limited applicability, rigid top-down designs, and static forms that fail to accurately model dynamic biological processes, perturbations, and mutations, requiring complete knowledge of input pathways and structures.
Innovation Solution
A computer-implemented simulation system that models biological events using a cell-centric approach with a processor-based system comprising modules for receiving configurable simulation information, initializing an ontogeny engine, advancing it through simulation steps, and applying physical and chemical interaction rules to simulate biological processes, including cell growth, division, and differentiation, allowing for the development of virtual multicellular tissues with emergent properties like self-repair and adaptive responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current in silico simulation systems use rigid top-down designs with static forms, then complete knowledge of input pathways and structures is required, but this limits applicability and prevents open investigation of perturbations and mutations
Solution Approach 1:
The patent inverts the traditional top-down design approach by implementing a bottom-up construction method where virtual cells are assembled from molecular components (genes, proteins, metabolites) that self-organize into functional biological systems. This allows simulation without requiring complete prior knowledge of system architecture, as the structure emerges from component interactions
Solution Approach 2:
The simulation system transitions from static forms to dynamic, evolving virtual organisms that can adapt to perturbations and mutations. The bottom-up approach enables real-time modification of system properties as components interact and self-organize, allowing open investigation of biological evolution and response to environmental changes
2Reliability
If in silico simulation keeps subject processes and structures within a reasonably complete and detailed context, then dissection without separation is enabled, but this increases computational complexity and data requirements
Solution Approach 1:
The patent segments the biological system into discrete virtual cells, each containing molecular components (genes, proteins, metabolites) that can be independently defined and simulated. This segmentation allows the system to maintain detailed contextual relationships while managing computational complexity through modular organization of simulation entities
Solution Approach 2:
The simulation implements a nested hierarchical structure where molecules are contained within virtual cells, which are contained within virtual tissues or organisms. This nesting allows detailed molecular-level simulation within the context of higher-level biological structures, maintaining reliability across multiple scales of organization
Data Source
AI summary
Systems and methods are provided herein that enable computer-implemented modeling of a biological event. Cell-based models produced from such systems and methods are also disclosed. In some embodiments, systems and methods are provided for cell-centric simulation with accommodating environment feedback. In one embodiment, a computer-implemented method of modeling a biological event can include receiving configurable simulation information and initializing an ontogeny engine to an initial step boundary in accordance with the configurable simulation information. The method can also include advancing the ontogeny engine from a current step boundary to a next step boundary in accordance with the configurable simulation information and the current step boundary. The advancing can include performing a stepCells function. The method can further include continuing the advancing until a halting condition is encountered. In some embodiments, simulation of biological events includes modeling biological processes, such as development of multicellular tissue and differentiation of pluripotent cells.