In this work, we present the application of a computational modeling infrastructure named UISS (Universal Immune System Simulator) able to simulate the main features and dynamics of the immune system activities. We provide an extended version of UISS to simulate all the underlying MS pathogenesis and its interaction with the host immune system. We simulated MS patients with different relapsing-remitting courses. Even though the model can be further personalized employing immunological parameters and genetic information, based on the available data, we obtained simulation scenarios for each patient who matched the real clinical and MRI history. UISS may have the potential to assist MS specialists in predicting the course of the disease and the response to treatment.

Agent based modeling of relapsing multiple sclerosis: A possible approach to predict treatment outcome

Pappalardo, Francesco;Russo, Giulia;Pennisi, Marzio;Sgroi, Giuseppe;SCUDERI, Alessandro Giuseppe;Motta, Santo;Chiacchio, Ferdinando
2018-01-01

Abstract

In this work, we present the application of a computational modeling infrastructure named UISS (Universal Immune System Simulator) able to simulate the main features and dynamics of the immune system activities. We provide an extended version of UISS to simulate all the underlying MS pathogenesis and its interaction with the host immune system. We simulated MS patients with different relapsing-remitting courses. Even though the model can be further personalized employing immunological parameters and genetic information, based on the available data, we obtained simulation scenarios for each patient who matched the real clinical and MRI history. UISS may have the potential to assist MS specialists in predicting the course of the disease and the response to treatment.
2018
9781538654880
artificial immune system; immune modeling; multiple sclerosis; personalized therapy; Biomedical Engineering; Health Informatics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/361464
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