Modeling biology by agents
Filippo Castiglione
National Research Council of Italy
Objectives: We describe the agent-based modelling methodology for simulating complex biological phenomena.
Overview/Description of presentation: The agent-based modelling (ABM) paradigm is nowadays recognised as a strong alternative to classical differential equation modelling. In my talk I will introduce the origins, main concepts and the pro and cons of this methodology. I will then make few examples of application of the ABM to clarify the generality and the extreme versatility of this approach. I will also show how to combine more classical approaches to construct complex multi-scale biological simulation tools that may turn out useful to perform in-silico clinical trials.
Conclusions/Take home message: Agent-based modelling is currently a popular approach in the computational biology field but it is much less known in the pharmacometrics domain. My prediction is that ABM will gain increasing interest in the field to be used as alternatives or (more likely) in combination with PD/PK in preclinical studies.
References:
[1] Marilda Sotomayor, David Perez-Castrillo and F. Castiglione (Eds.). Complex Social and Behavioral Systems Game Theory and Agent-Based Models. Springer US, Aug 21, 2020 ISBN 978-1-07-160367-3
[2] An G, Mi Q, Dutta-Moscato J, Vodovotz Y (2009). "Agent-based models in translational systems biology". Wiley Interdisciplinary Reviews. Systems Biology and Medicine. 1 (2): 159–171. doi:10.1002/wsbm.45.
[3] Filippo Castiglione (2006) Agent based modeling. Scholarpedia, 1(10):1562.