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Predicting Long-Term Vaccine Efficacy against Metastases Using Agents

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6840))

Abstract

To move faster from preclinical studies (experiments in mice) towards clinical phase I trials (experiments in advanced cancer patients), the chance to predict the outcome of longer experiments represents a key step. We use the MetastaSim model to predict the long-term effects of the Triplex vaccine against metastases. To this end we simulate follow-ups of two and three of three months (equivalent approximately to 5.83 and 8.75 years in humans) to compare the long-term efficacy of the best protocol used “in vivo” against the one found by the MetastaSim model. We also check the efficacy of these two protocols by delaying the time of the first administration, in order to catch up the maximum time delay between the appearing of metastases and the administration of the vaccine needed to guarantee reasonable treatment efficacy.

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Pennisi, M., Motta, D., Cincotti, A., Pappalardo, F. (2012). Predicting Long-Term Vaccine Efficacy against Metastases Using Agents. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_15

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  • DOI: https://doi.org/10.1007/978-3-642-24553-4_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24552-7

  • Online ISBN: 978-3-642-24553-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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