Onko3D

Microtumor development 3D simulation

The Onko3D team aims at developing an in-silico 3-D cell proliferation model in order to investigate possible treatments of tumors. To do so, we are developing a simulator based on three interdependent components:

1/ A behavioral engine, that simulates the behavior of cells (healthy or cancerous): based on checkpoints instead of phases, the behavioral engine takes into account internal and external stimuli (lack of nutriments, drugs, etc.) and its impacts on the cell cycle regulation. The 2-D proliferation of different cell lineages has been successfully simulated and the results of the simulation show a convergence between simulations and their equivalent in-vitro biological experiments.

2/ A simplified biophysics engine, which simulates the physical interactions between cells: this physics engine, inspired from the beam theory makes the simulation step up to the third dimension within a continuous environment while keeping a reasonable computation cost. It simulates the collision and adhesion between cells as well as membrane deformation.

3/ A simplified hydrodynamic model that aims at simulating the diffusion of molecular components within the environment and its penetration in a cell aggregate (more particularly in a 3-D spheroid). We want the simulator to be able to simulate a local lack of nutriment, the diffusion of drug in a spheroid, etc…

 

 

We hope this work will open new perspectives concerning therapeutic strategies: it could be used to predict the impact of preclinical molecules before any in-vitro or in-vivo experience. The idea is to automatically discover optimal treatment protocols in order to efficiently use the drug. Once discovered in-silico, the treatment can then be tested in-vitro and/or in-vivo to be validated. Using the simulator might strongly reduce the time and cost effort necessary to validate a treatment.

Team leader

Sylvain Cussat-Blanc

Partner Lab

Key points

Selected references
  • Sylvain Cussat-Blanc, Kyle Harrington, Jordan Pollack. Gene Regulatory Network Evolution Through Augmenting Topologies. IEEE Transactions on Evolutionary Computation, IEEE, 2015, Journal paper (IF=3.65, rank A*1)
  • Sylvain Cussat-Blanc, Jordan Pollack. Cracking the Egg: Virtual Embryogenesis of Real Robots. Artificial Life, MIT Press, USA, Vol. 20 N. 3, July 2014.
    Jean Disset, Sylvain Cussat-Blanc, Yves Duthen. MecaCell: an Open-source Efficient Cellular Physics Engine (short paper). European Conference on Artificial Life (ECAL 2015), York, 20/07/2015-24/07/2015, MIT Press, July 2015.
  • Sylvain Cussat-Blanc, Kyle Harrington. Genetically-regulated Neuromodulation Facilitates Multi-Task Reinforcement Learning (regular paper). Genetic and Evolutionary Computation COnference (GECCO 2015), Madrid, 11/07/2015-15/07/2015, ACM, July 2015.
  • Jean Disset, Sylvain Cussat-Blanc, Yves Duthen. Self-organization of Symbiotic Multicellular Structures (regular paper). Artificial Life, New York, 30/07/2014-02/08/2014, The MIT Press, July 2014.
Team members
  • Sylvain CUSSAT-BlANC (MCU),
  • Yves DUTHEN (PR),
  • David BERNARD (PhD student)
Collaborations
  • IP3D Team (ITAV),
  • Serious Game Research Lab (C.Univ. J.-F. Champollion),
  • Molecular Dynamics of Lymphocyte interactions (INSERM – CNRS – UMR1043),
  • Institut de Mathématiques de Toulouse (IMT).

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