Combination of direct methods and homotopy in numerical optimal control: application to the optimization of chemotherapy in cancer

We consider a state-constrained optimal control problem of a system of two non-local partial-differential equations, which is an extension of the one introduced in a previous work in mathematical oncology. The aim is to minimize the tumor size through chemotherapy while avoiding the emergence of resistance to the drugs. The numerical approach to solve the problem was the combination of direct methods and continuation on discretization parameters, which happen to be insufficient for the more complicated model, where diffusion is added to account for mutations. In the present paper, we propose an approach relying on changing the problem so that it can theoretically be solved thanks to a Pontryagin Maximum Principle in infinite dimension. This provides an excellent starting point for a much more reliable and efficient algorithm combining direct methods and continuations. The global idea is new and can be thought of as an alternative to other numerical optimal control techniques

Modelling interactions between tumour cells and supporting adipocytes in breast cancer

International audienceIn breast cancer, invasion of the micro-environment implies potential bidirectional communica- tion between cancer cells and the adipose tissue. Biological evidence suggests that adipocytes, in particular, are key-actors in tumorigenesis and invasion: they both enhance proliferation of the cancer cells and favor acquisition of a more invasive phenotype. To understand these effects, mathematical modelling (thanks to tools developed in theoretical ecology) is used to perform asymptotic analysis in number of cells and distribution of phenotypes. These models can be tuned through confrontation with experimental data coming from co-cultures of cancer cells with adipocytes.The first part of this report is devoted to presenting the biological background on breast cancer and its environment. We then present the main aspects of the mathematical modelling, and how it is expected to be validated experimentally. In the third part, we summarize and prove many important results that have been obtained on a single integro-differential equation rep- resenting the evolution of a population of individuals structured with a phenotypic trait. The next part consists of a first glance at possible generalizations of those results to a system of integro-differential equations coupled mutualistically. In a fifth and last part, we introduce how we intend to parametrize the models through explicit computations and numerical simulations

Hele-Shaw limit for a system of two reaction-(cross-)diffusion equations for living tissues

Multiphase mechanical models are now commonly used to describe living tissues including tumour growth. The specific model we study here consists of two equations of mixed parabolic and hyperbolic type which extend the standard compressible porous medium equation, including cross-reaction terms. We study the incompressible limit, when the pressure becomes stiff, which generates a free boundary problem. We establish the complementarity relation and also a segregation result. Several major mathematical difficulties arise in the two species case. Firstly, the system structure makes comparison principles fail. Secondly, segregation and internal layers limit the regularity available on some quantities to BV. Thirdly, the Aronson-B{\'e}nilan estimates cannot be established in our context. We are lead, as it is classical, to add correction terms. This procedure requires technical manipulations based on BV estimates only valid in one space dimension. Another novelty is to establish an L1 version in place of the standard upper bound

Linear inverse problems with nonnegativity constraints through the β\beta-divergences: sparsity of optimisers

We pass to continuum in optimisation problems associated to linear inverse problems $y = Ax$ with non-negativity constraint $x \geq 0$. We focus on the case where the noise model leads to maximum likelihood estimation through the so-called $\beta$-divergences, which cover several of the most common noise statistics such as Gaussian, Poisson and multiplicative Gamma. Considering~$x$ as a Radon measure over the domain on which the reconstruction is taking place, we show a general sparsity result. In the high noise regime corresponding to $y \notin \{{Ax}\mid{x \geq 0}\}$, optimisers are typically sparse in the form of sums of Dirac measures. We hence provide an explanation as to why any possible algorithm successfully solving the optimisation problem will lead to undesirably spiky-looking images when the image resolution gets finer, a phenomenon well documented in the literature. We illustrate these results with several numerical examples inspired by medical imaging

Modelling interactions between tumour cells and supporting adipocytes in breast cancer

International audienceIn breast cancer, invasion of the micro-environment implies potential bidirectional communica- tion between cancer cells and the adipose tissue. Biological evidence suggests that adipocytes, in particular, are key-actors in tumorigenesis and invasion: they both enhance proliferation of the cancer cells and favor acquisition of a more invasive phenotype. To understand these effects, mathematical modelling (thanks to tools developed in theoretical ecology) is used to perform asymptotic analysis in number of cells and distribution of phenotypes. These models can be tuned through confrontation with experimental data coming from co-cultures of cancer cells with adipocytes.The first part of this report is devoted to presenting the biological background on breast cancer and its environment. We then present the main aspects of the mathematical modelling, and how it is expected to be validated experimentally. In the third part, we summarize and prove many important results that have been obtained on a single integro-differential equation rep- resenting the evolution of a population of individuals structured with a phenotypic trait. The next part consists of a first glance at possible generalizations of those results to a system of integro-differential equations coupled mutualistically. In a fifth and last part, we introduce how we intend to parametrize the models through explicit computations and numerical simulations

A phenotype-structured model for the tumour-immune response

This paper presents a mathematical model for tumour-immune response interactions in the perspective of immunotherapy by immune checkpoint inhibitors (ICIs). The model is of the integrodifferential Lotka-Volterra type, in which heterogeneity of the cell populations is taken into account by structuring variables that are continuous internal traits (aka phenotypes) representing a lumped ''aggressiveness'', i.e., for tumour cells, ability to thrive in a viable state under attack by immune cells or drugs-which we propose to identify as a potential of de-differentiation-, and for immune cells, ability to kill tumour cells. We analyse the asymptotic behaviour of the model in the absence of treatment. By means of two theorems, we characterise the limits of the integro-differential system under an a priori convergence hypothesis. We illustrate our results with numerical simulations, which show that our model exemplifies the three Es of immunoediting: elimination, equilibrium, and escape

Approximate control of parabolic equations with on-off shape controls by Fenchel duality

We consider the internal control of linear parabolic equations through on-off shape controls, i.e., controls of the form $M(t)\chi_{\omega(t)}$ with $M(t) \geq 0$ and $\omega(t)$ with a prescribed maximal measure. We establish small-time approximate controllability towards all possible final states allowed by the comparison principle with nonnegative controls. We manage to build controls with constant amplitude $M(t) \equiv M$. In contrast, if the moving control set $\omega(t)$ is confined to evolve in some region of the whole domain, we prove that approximate controllability fails to hold for small times. The method of proof is constructive. Using Fenchel-Rockafellar duality and the bathtub principle, the on-off shape control is obtained as the bang-bang solution of an optimal control problem, which we design by relaxing the constraints. Our optimal control approach is outlined in a rather general form for linear constrained control problems, paving the way for generalisations and applications to other PDEs and constraints