Building digital twins of the human immune system: toward a roadmap.

Digital twins, customized simulation models pioneered in industry, are beginning to be deployed in medicine and healthcare, with some major successes, for instance in cardiovascular diagnostics and in insulin pump control. Personalized computational models are also assisting in applications ranging from drug development to treatment optimization. More advanced medical digital twins will be essential to making precision medicine a reality. Because the immune system plays an important role in such a wide range of diseases and health conditions, from fighting pathogens to autoimmune disorders, digital twins of the immune system will have an especially high impact. However, their development presents major challenges, stemming from the inherent complexity of the immune system and the difficulty of measuring many aspects of a patient's immune state in vivo. This perspective outlines a roadmap for meeting these challenges and building a prototype of an immune digital twin. It is structured as a four-stage process that proceeds from a specification of a concrete use case to model constructions, personalization, and continued improvement.

An object-oriented modelling framework for the arterial wall.

An object-oriented modelling framework for the arterial wall is presented. The novelty of the framework is the possibility to generate customizable artery models, taking advantage of imaging technology. In our knowledge, this is the first object-oriented modelling framework for the arterial wall. Existing models do not allow close structural mapping with arterial microstructure as in the object-oriented framework. In the implemented model, passive behaviour of the arterial wall was considered and the tunica adventitia was the objective system. As verification, a model of an arterial segment was generated. In order to simulate its deformation, a matrix structural mechanics simulator was implemented. Two simulations were conducted, one for an axial loading test and other for a pressure-volume test. Each simulation began with a sensitivity analysis in order to determinate the best parameter combination and to compare the results with analogue controls. In both cases, the simulated results closely reproduced qualitatively and quantitatively the analogue control plots.

On multiscale approaches to three-dimensional modelling of morphogenesis.

In this paper we present the foundation of a unified, object-oriented, three-dimensional biomodelling environment, which allows us to integrate multiple submodels at scales from subcellular to those of tissues and organs. Our current implementation combines a modified discrete model from statistical mechanics, the Cellular Potts Model, with a continuum reaction-diffusion model and a state automaton with well-defined conditions for cell differentiation transitions to model genetic regulation. This environment allows us to rapidly and compactly create computational models of a class of complex-developmental phenomena. To illustrate model development, we simulate a simplified version of the formation of the skeletal pattern in a growing embryonic vertebrate limb.

CompuCell, a multi-model framework for simulation of morphogenesis.

MOTIVATION: CompuCell is a multi-model software framework for simulation of the development of multicellular organisms known as morphogenesis. It models the interaction of the gene regulatory network with generic cellular mechanisms, such as cell adhesion, division, haptotaxis and chemotaxis. A combination of a state automaton with stochastic local rules and a set of differential equations, including subcellular ordinary differential equations and extracellular reaction-diffusion partial differential equations, model gene regulation. This automaton in turn controls the differentiation of the cells, and cell-cell and cell-extracellular matrix interactions that give rise to cell rearrangements and pattern formation, e.g. mesenchymal condensation. The cellular Potts model, a stochastic model that accurately reproduces cell movement and rearrangement, models cell dynamics. All these models couple in a controllable way, resulting in a powerful and flexible computational environment for morphogenesis, which allows for simultaneous incorporation of growth and spatial patterning. RESULTS: We use CompuCell to simulate the formation of the skeletal architecture in the avian limb bud. AVAILABILITY: Binaries and source code for Microsoft Windows, Linux and Solaris are available for download from http://sourceforge.net/projects/compucell/

Diffusion and deformations of single hydra cells in cellular aggregates.

Cell motion within cellular aggregates consists of both random and coherent components. We used confocal microscopy to study the center of mass displacements and deformations of single endodermal Hydra cells in two kinds of cellular aggregates, ectodermal and endodermal. We first carefully characterize the center of mass displacements using standard statistical analysis. In both aggregates, cells perform a persistent random walk, with the diffusion constant smaller in the more cohesive endodermal aggregate. We show that a simple parametric method is able to describe cell deformations and relate them to displacements. These deformations are random, with their amplitude and direction uncorrelated with the center of mass motion. Unlike for an isolated cell on a substrate, the random forces exerted by the surrounding cells predominate over the deformation of the cell itself, causing the displacements of a cell within an aggregate.

Model of convergent extension in animal morphogenesis.

We argue that energy minimization can explain the pattern of cell movements in the morphogenetic process known as convergent extension provided that the cell-cell adhesive energy has a certain type of anisotropy, which we describe. This single simple property suffices to cause the cell elongation, cell alignment, and lengthening of a cellular array that characterize convergent extension. We show that the final aspect ratio of the array of cells depends on the anisotropy and is independent of the initial configuration and of the degree of cell elongation.

Cell sorting is analogous to phase ordering in fluids.

Morphogenetic processes, like sorting or spreading of tissues, characterize early embryonic development. An analogy between viscoelastic fluids and certain properties of embryonic tissues helps interpret these phenomena. The values of tissue-specific surface tensions are consistent with the equilibrium configurations that the Differential Adhesion Hypothesis predicts such tissues reach after sorting and spreading. Here we extend the fluid analogy to cellular kinetics. The same formalism applies to recent experiments on the kinetics of phase ordering in two-phase fluids. Our results provide biologically relevant information on the strength of binding between cell adhesion molecules under near-physiological conditions.

Hysteresis and avalanches in two-dimensional foam rheology simulations.

Foams have unique rheological properties that range from solidlike to fluidlike. We study two-dimensional noncoarsening foams of different disorder under shear in a Monte Carlo simulation, using a driven large-Q Potts model. Simulations of periodic shear on an ordered foam show several different response regimes. At small strain amplitudes, bubbles deform and recover their shapes elastically, and the macroscopic response is that of a linear elastic cellular material. For increasing strain amplitude, the energy-strain curve starts to exhibit hysteresis before any topological rearrangements occur, indicating a macroscopic viscoelastic response. When the applied strain amplitude exceeds a critical value, the yield strain, topological rearrangements occur, the foam starts to flow, and we observe macroscopic irreversibility. We find that the dynamics of topological rearrangements depend sensitively on the structural disorder. Structural disorder decreases the yield strain; sufficiently high disorder changes the macroscopic response of a foam from a viscoelastic solid to a viscoelastic fluid. This wide-ranging dynamical response and the associated history effects of foams result from avalanchelike rearrangement events. The spatiotemporal statistics of rearrangement events do not display long-range correlations for ordered foams or at low shear rates, consistent with experimental observations. As the shear rate or structural disorder increases, the topological events become more correlated and their power spectra change from that of white noise toward 1/f noise. Intriguingly, the power spectra of the total stored energy also exhibit this 1/f trend.