Carlos Roberto Prudencio has completed his PhD from Federal University of Uberlandia and Postdoctoral studies from University of Sao Paulo and Universidad Castilla-la Mancha, Spain. He is the Coordinator of Immunotechnology Lab of the Center of Immunology at Adolfo Lutz Institute, Secretary of Health of Sao Paulo State; a public health institute with mission focused in research, epidemiological, sanitary and environmental surveillance in Sao Paulo State. He is a Member of the Post-graduation program (CAPES) devoted to Applied Health Sciences. He has published papers in reputed journals and also has been serving as an Editorial Board Member of repute. He is the Inventor holding eight patents related to the field of biotechnology of vaccines and diagnosis with expertise in innovation management and technological transfer focused in health. His research is focused on high-throughput approaches based in phage display technology applied to study host-pathogen interactions and the discovery of targets to develop new diagnosis, drugs and vaccines of interest to public health.


Given the growing number of diseases caused by emerging or endemic pathogens in Brazil, like Ricketsias and Zika virus, new strategies are urgently required for the development of disease diagnostic markers and vaccines. In this context, identification and development of these markers require high-throughput screening of combinatorial libraries. Phage-display is a powerful technique for selecting unique molecules with selective affinity for a specific target from high-complexity combinatorial phage display peptide libraries. The technology was applied initially to allow identification of high-affinity peptides after in vivo and in vitro screening. By high-throughput sequencing of the pool of recombinant phage clones following in silico analyses amongst hypothetical proteins of these pathogens, all categorized sequences provided the profile of the best candidates. Thus, we heightened the powerful screening capacity of this technique adding complementary approaches based on deep sequencing to identification and characterization of antigen candidates. By combining such approaches, we maximized the selection of molecules potentially relevant for diagnostics and vaccine development for pathogens of interest to public health.