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Excepting the Peripheral and Central Nervous Systems, the Immune System is the most complex of somatic systems in higher animals. This complexity manifests itself at many levels from the molecular to that of the whole organism. Much insight into this confounding complexity can be gained through computational simulation. Such simulations range in application from epitope prediction through to the modelling of vaccination strategies. In this review, we evaluate selectively various key applications relevant to computational vaccinology: these include technique that operates at different scale that is, from molecular to organisms and even to population level., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

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.

Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines conceptual models of the immune system, models of antigen processing and presentation, system-level models of the immune system, Grid computing, and database technology to facilitate discovery, formulation and optimization of vaccines. ImmunoGrid modules share common conceptual models and ontologies. The ImmunoGrid portal offers access to educational simulators where previously defined cases can be displayed, and to research simulators that allow the development of new, or tuning of existing, computational models. The portal is accessible at .

Summary: Since few years the problem of finding optimal solutions for drug or vaccine protocols have been tackled using system biology modeling. These approaches are usually computationally expensive. Our previous experiences in optimizing vaccine or drug protocols using genetic algorithms required the use of a high performance computing infrastructure for a couple of days. In the present article we show that by an appropriate use of a different optimization algorithm, the simulated annealing, we have been able to downsize the computational effort by a factor 10(2). The new algorithm requires computational effort that can be achieved by current generation personal computers., Availability: Software and additional data can be found at http://www.immunomics.eu/SA/

Motivation: Vaccines represent the most effective and cost-efficient weapons against a wide range of diseases. Nowadays new generation vaccines based on subunit antigens reduce adverse effects in high risk individuals. However, vaccine antigens are often poor immunogens when administered alone. Adjuvants represent a good strategy to overcome such hurdles, indeed they are able to: enhance the immune response; allow antigens sparing; accelerate the specific immune response; and increase vaccine efficacy in vulnerable groups such as newborns, elderly or immune-compromised people. However, due to safety concerns and adverse reactions, there are only a few adjuvants approved for use in humans. Moreover, in practice current adjuvants sometimes fail to confer adequate stimulation. Hence, there is an imperative need to develop novel adjuvants that overcome the limitations of the currently available licensed adjuvants. Results: We developed a computational framework that provides a complete pipeline capable of predicting the best citrus-derived adjuvants for enhancing the immune system response using, as a target disease model, influenza A infection. In silico simulations suggested a good immune effi- cacy of specific citrus-derived adjuvant (Beta Sitosterol) that was then confirmed in vivo. [ABSTRACT FROM AUTHOR]

Background: The Triplex cell vaccine is a cancer cellular vaccine that can prevent almost completely the mammary tumor onset in HER-2/neu transgenic mice. In a translational perspective, the activity of the Triplex vaccine was also investigated against lung metastases showing that the vaccine is an effective treatment also for the cure of metastases. A future human application of the Triplex vaccine should take into account several aspects of biological behavior of the involved entities to improve the efficacy of therapeutic treatment and to try to predict, for example, the outcomes of longer experiments in order to move faster towards clinical phase I trials. To help to address this problem, MetastaSim, a hybrid Agent Based -- ODE model for the simulation of the vaccine-elicited immune system response against lung metastases in mice is presented. The model is used as in silico wet-lab. As a first application MetastaSim is used to find protocols capable of maximizing the total number of prevented metastases, minimizing the number of vaccine administrations. Results: The model shows that it is possible to obtain "in silico" a 45% reduction in the number of vaccinations. The analysis of the results further suggests that any optimal protocol for preventing lung metastases formation should be composed by an initial massive vaccine dosage followed by few vaccine recalls. Conclusions: Such a reduction may represent an important result from the point of view of translational medicine to humans, since a downsizing of the number of vaccinations is usually advisable in order to minimize undesirable effects. The suggested vaccination strategy also represents a notable outcome. Even if this strategy is commonly used for many infectious diseases such as tetanus and hepatitis-B, it can be in fact considered as a relevant result in the field of cancer-vaccines immunotherapy. These results can be then used and verified in future "in vivo" experiments, and their outcome can be used to further improve and refine the model. [ABSTRACT FROM AUTHOR]