AMR is a complex, multiscale problem: what makes AMR especially difficult to fight is its multi-dimensional complexity. AMR is driven by an interplay of genetic, clinical, environmental, and socioeconomic factors, from mobile genetic elements (MGEs), resistance genes to clinical practice, and climate. The investigation of AMR insurgence and spread requires a 360-degree approach to observe complex, interconnected systems of microorganisms, hosts, society, and environments. Yet, despite a growing collection of data from omics, clinical records, environmental sensors, and epidemiological surveillance, we lack the tools to bring these layers together.
Within her research group, Tania oversees the development of big data solutions based on bioinformatics and AI to combine such heterogeneous information and data mine novel correlations and causalities. Her goal is to identify drivers and mechanisms underlying the insurgence and spread of new genetic variants of resistant pathogens and novel AMR traits across animals, environment, humans, and food.
In addition to contributing to a better understanding of the mechanisms underlying AMR, Tania’s research aims to support the development of novel solutions to implement surveillance, monitoring, early warning, diagnostics and treatment selection.