Methods for predicting vaccine immunogenicity and reactogenicity

Autor(es)

Gonzalez-Dias, Patricia ^[1] ; Lee, Eva K. ^[2] ; Sorgi, Sara ^[3] ; de Lima, Diogenes S. ^[1] ; Urbanski, Alysson H. ^[1] ; Silveira, Eduardo Lv ^[1] ; Nakaya, Helder I. ^{[1, 4]}

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Sch Pharmaceut Sci, Dept Clin & Toxicol Anal, BR-05508000 Sao Paulo - Brazil

^[2] Georgia Inst Technol, Ctr Operat Res Med & HealthCare, Atlanta, GA 30332 - USA

^[3] Univ Siena, Dept Med Biotechnol, Siena - Italy

^[4] Univ Sao Paulo, Sci Platform Pasteur, Sao Paulo - Brazil

• Tipo de documento: Artigo de Revisão
• Fonte: HUMAN VACCINES & IMMUNOTHERAPEUTICS; v. 16, n. 2 DEC 2019.
• Citações Web of Science: 1

Resumo

Subjects receiving the same vaccine often show different levels of immune responses and some may even present adverse side effects to the vaccine. Systems vaccinology can combine omics data and machine learning techniques to obtain highly predictive signatures of vaccine immunogenicity and reactogenicity. Currently, several machine learning methods are already available to researchers with no background in bioinformatics. Here we described the four main steps to discover markers of vaccine immunogenicity and reactogenicity: (1) Preparing the data; (2) Selecting the vaccinees and relevant genes; (3) Choosing the algorithm; (4) Blind testing your model. With the increasing number of Systems Vaccinology datasets being generated, we expect that the accuracy and robustness of signatures of vaccine reactogenicity and immunogenicity will significantly improve. (AU)

• Processo FAPESP: 13/08216-2 - CPDI - Centro de Pesquisa em Doenças Inflamatórias
• Beneficiário: Fernando de Queiroz Cunha
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
• Processo FAPESP: 18/21934-5 - Estatística de redes: teoria, métodos e aplicações
• Beneficiário: André Fujita
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 18/14933-2 - Biologia integrativa aplicada à saúde humana
• Beneficiário: Helder Takashi Imoto Nakaya
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores - Fase 2