Multiple Myeloma Cell Simulation Using an Agent-Based Framework Coupled with a Continuous Fluid Model

Pau Urdeitx, Sandra Clara-Trujillo, Jose Luis Gomez Ribelles and Mohamed H. Doweidar ()
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Pau Urdeitx: Mechanical Engineering Department, School of Engineering and Architecture (EINA), University of Zaragoza, 50018 Zaragoza, Spain
Sandra Clara-Trujillo: Centre for Biomaterials and Tissue Engineering (CBIT), Universitat Politecnica de Valencia, 46022 Valencia, Spain
Jose Luis Gomez Ribelles: Centre for Biomaterials and Tissue Engineering (CBIT), Universitat Politecnica de Valencia, 46022 Valencia, Spain
Mohamed H. Doweidar: Mechanical Engineering Department, School of Engineering and Architecture (EINA), University of Zaragoza, 50018 Zaragoza, Spain

Mathematics, 2023, vol. 11, issue 8, 1-13

Abstract: Bone marrow mechanical conditions play a key role in multiple myeloma cancer. The complex mechanical and chemical conditions, as well as the interactions with other resident cells, hinder the development of effective treatments. Agent-based computational models, capable of defining the specific conditions for every single cell, can be a useful tool to identify the specific tumor microenvironment. In this sense, we have developed a novel hybrid 3D agent-based model with coupled fluid and particle dynamics to study multiple myeloma cells’ growth. The model, which considers cell–cell interactions, cell maturation, and cell proliferation, has been implemented by employing user-defined functions in the commercial software Fluent. To validate and calibrate the model, cell sedimentation velocity and cell proliferation rates have been compared with in vitro results, as well as with another previously in-house developed model. The results show that cell proliferation increased as cell–cell, and cell–extracellular matrix interactions increased, as a result of the reduction n maturation time. Cells in contact form cell aggregates, increasing cell–cell interactions and thus cell proliferation. Saturation in cell proliferation was observed when cell aggregates increased in size and the lack of space inhibited internal cells’ proliferation. Compared with the previous model, a huge reduction in computational costs was obtained, allowing for an increase in the number of simulated cells.

Keywords: in silico; 3D model; multiple myeloma; tumor aggregate; dense discrete particle model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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