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.
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Pappalardo, F., Pennisi, M., Cincotti, A., Chiacchio, F., Motta, S., Lollini, PL. (2010). Cancer Immunoprevention: What Can We Learn from in Silico Models?. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_15
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DOI: https://doi.org/10.1007/978-3-642-14831-6_15
Publisher Name: Springer, Berlin, Heidelberg
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