We present our experience of the artificial immunity induced by an immuoprevention vaccine succesfully tested on transgenic mice. The model mimics the phenomenon of initial cancer growing starting from the stage of the atypical hyperplasia and reproduces the action of the vaccine in activating the immune response. The model has been validated against in-vivo experiments. Finally we use the model to determine an optimal vaccination scheduling which reduce to a minimum the number of vaccine administrations still preventing the solid tumor formation is a population of virtual mice. The vaccination schedule proposed by the model is substantially lighter than the one's determined by the standard intuitive procedure.

Cancer immunoprevention: What can we learn from in silico models?

PAPPALARDO, FRANCESCO;PENNISI, MARZIO ALFIO;Chiacchio F;MOTTA, Santo;
2010-01-01

Abstract

We present our experience of the artificial immunity induced by an immuoprevention vaccine succesfully tested on transgenic mice. The model mimics the phenomenon of initial cancer growing starting from the stage of the atypical hyperplasia and reproduces the action of the vaccine in activating the immune response. The model has been validated against in-vivo experiments. Finally we use the model to determine an optimal vaccination scheduling which reduce to a minimum the number of vaccine administrations still preventing the solid tumor formation is a population of virtual mice. The vaccination schedule proposed by the model is substantially lighter than the one's determined by the standard intuitive procedure.
9783642148309
Agent Aased Models; Artificial Immunity; Mathemtical Models
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/90275
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