title: Vaccine protocols optimization: in silico experiences.
abstract: Vaccines represent a special class of drugs, capable of stimulating immune system responses against pathogens and tumors. Vaccine development is a lengthy process that includes expensive laboratory experiments in order to assess safety and effectiveness. As the efficacy of a vaccine was demonstrated by biological/chemical investigations and pre-clinical studies, then a major problem is represented by the search for an optimal vaccination dosage. Optimality here assumes the meaning of assuring a high degree of efficacy and safety (lack of toxic or side effects). In lack of quantitative methods, this is usually achieved by a consensus technique, a public statement on a particular aspect of medical knowledge available at the time it was written, and that is generally agreed upon as the evidence-based, state-of-the-art (or state-of-science) knowledge by a representative group of experts in that area. In this article, we focus on the difficult problem of the search for an optimal vaccination dosage in the field of tumor immunology, that is a major issue in biomedical research. This, indeed, represents a first step toward a personalized medicine approach.
authors.affiliation: Institute for Computing Applications M. Picone, National Research Council (CNR), Rome, Italy. francesco@dmi.unict.it
authors.forename: Francesco
authors.initials: F
authors.lastname: Pappalardo
authors.forename: Marzio
authors.initials: M
authors.lastname: Pennisi
authors.forename: Filippo
authors.initials: F
authors.lastname: Castiglione
authors.forename: Santo
authors.initials: S
authors.lastname: Motta
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D055808:Drug Discovery; D006801:Humans; D008957:Models, Genetic; D018448:Models, Immunological; D014612:Vaccines
chemical_list: D014612:Vaccines