Literature DB >> 19833190

Vaccine protocols optimization: in silico experiences.

Francesco Pappalardo1, Marzio Pennisi, Filippo Castiglione, Santo Motta.   

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.

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Year:  2010        PMID: 19833190     DOI: 10.1016/j.biotechadv.2009.10.001

Source DB:  PubMed          Journal:  Biotechnol Adv        ISSN: 0734-9750            Impact factor:   14.227


  14 in total

1.  Harnessing the power of genomics and immunoinformatics to produce improved vaccines.

Authors:  Leonard Moise; Leslie Cousens; Joanna Fueyo; Anne S De Groot
Journal:  Expert Opin Drug Discov       Date:  2010-12-01       Impact factor: 6.098

2.  Biomimetic Glyconanoparticle Vaccine for Cancer Immunotherapy.

Authors:  Eliran Moshe Reuven; Shani Leviatan Ben-Arye; Hai Yu; Roberto Duchi; Andrea Perota; Sophie Conchon; Shirley Bachar Abramovitch; Jean-Paul Soulillou; Cesare Galli; Xi Chen; Vered Padler-Karavani
Journal:  ACS Nano       Date:  2019-03-11       Impact factor: 15.881

3.  Optimal vaccination schedule search using genetic algorithm over MPI technology.

Authors:  Cristiano Calonaci; Ferdinando Chiacchio; Francesco Pappalardo
Journal:  BMC Med Inform Decis Mak       Date:  2012-11-13       Impact factor: 2.796

Review 4.  Theoretical modeling techniques and their impact on tumor immunology.

Authors:  Anna Lena Woelke; Manuela S Murgueitio; Robert Preissner
Journal:  Clin Dev Immunol       Date:  2010-12-23

5.  Modeling the competition between lung metastases and the immune system using agents.

Authors:  Marzio Pennisi; Francesco Pappalardo; Ariannna Palladini; Giordano Nicoletti; Patrizia Nanni; Pier-Luigi Lollini; Santo Motta
Journal:  BMC Bioinformatics       Date:  2010-10-15       Impact factor: 3.169

6.  SimB16: modeling induced immune system response against B16-melanoma.

Authors:  Francesco Pappalardo; Ivan Martinez Forero; Marzio Pennisi; Asis Palazon; Ignacio Melero; Santo Motta
Journal:  PLoS One       Date:  2011-10-19       Impact factor: 3.240

Review 7.  Emerging vaccine informatics.

Authors:  Yongqun He; Rino Rappuoli; Anne S De Groot; Robert T Chen
Journal:  J Biomed Biotechnol       Date:  2011-06-15

Review 8.  Cancer vaccines: state of the art of the computational modeling approaches.

Authors:  Francesco Pappalardo; Ferdinando Chiacchio; Santo Motta
Journal:  Biomed Res Int       Date:  2012-12-23       Impact factor: 3.411

9.  Mathematical modeling of the immune system recognition to mammary carcinoma antigen.

Authors:  Carlo Bianca; Ferdinando Chiacchio; Francesco Pappalardo; Marzio Pennisi
Journal:  BMC Bioinformatics       Date:  2012-12-13       Impact factor: 3.169

Review 10.  In silico modeling of the immune system: cellular and molecular scale approaches.

Authors:  Mariagrazia Belfiore; Marzio Pennisi; Giuseppina Aricò; Simone Ronsisvalle; Francesco Pappalardo
Journal:  Biomed Res Int       Date:  2014-04-06       Impact factor: 3.411

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