Healthcare-associated infections (HAI) are a severe public health problem. Among the pathogens related to HAI, the group of bacteria is the one that stands out. According to the Brazilian Health Surveillance Agency (ANVISA) March 2014's Health Services Quality and Patient Safety Bulletin, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter spp., and Pseudomonas aeruginosa are the primary pathogens associated with catheter-related bloodstream infections in adult patients hospitalized at Brazilian intensive care units. The antimicrobial resistance associated with these infections has been considered one of the main challenges of humanity in the 21st century. Its incidence has been increasing at alarming levels, leading to loss of effectiveness of antimicrobial agents, increased morbimortality, and hospitalization time of patients.
One of the research approaches used in biology to construct knowledge is the empirical one, executed with observable experiments and without inferring the dynamicity of the biological system. On the other hand, theoretical approaches aim to construct mathematical models that, although precise, often do not accurately represent the biological system reliably. The results are much more promising when considering these two approaches simultaneously, as systems biology proposes.
Understanding how complex phenotypes arise from individual molecules and their interactions is a primary challenge in biology, and computational approaches are mandatory to tackle this challenge. The Computational Modeling of Multidrug-resistant Bacteria research group proposes creating innovative models, techniques, and computational methods to identify new potential therapeutic targets in multidrug-resistant bacteria using a systems biology approach. Two strengths of this group are interdisciplinarity and complementarity of competencies. These characteristics are indispensable for the achievement of the group's objectives. This research group is registered with CNPq and certified by FIOCRUZ.