A Beginners Guide to Systems Simulation in Immunology

TL;DR

This paper introduces a quick guide for systems simulation in immunology, emphasizing its importance, outlining development steps, and demonstrating its application through an example to encourage adoption in immunological research.

Contribution

It provides the first comprehensive guide for developing immune system simulation models and highlights the need for increased adoption in immunology research.

Findings

Guidelines for immune system simulation development

Identification of challenges in model creation

Successful application of the guidelines in an example

Abstract

Some common systems modelling and simulation approaches for immune problems are Monte Carlo simulations, system dynamics, discrete-event simulation and agent-based simulation. These methods, however, are still not widely adopted in immunology research. In addition, to our knowledge, there is few research on the processes for the development of simulation models for the immune system. Hence, for this work, we have two contributions to knowledge. The first one is to show the importance of systems simulation to help immunological research and to draw the attention of simulation developers to this research field. The second contribution is the introduction of a quick guide containing the main steps for modelling and simulation in immunology, together with challenges that occur during the model development. Further, this paper introduces an example of a simulation problem, where we test our guidelines.