Meet Dr Tania Dottorini

Dr Dottorini explains: "I aim to identify key drivers and mechanisms underlying the emergence, evolution and transmission of new genetic variants of resistant pathogens and novel AMR traits, while exploring how host, co-infections, climate, ecological and environmental interactions influence genome evolution - and ultimately the dynamics of infection and AMR.

Grounded in a One Health philosophy, which recognises that human, animal and environmental health are deeply intertwined, my data analysis solutions recognise each investigated setting as a network of interconnected systems and environments, observable across multiple scales - from molecules to entire populations. By leveraging diverse data sources, including omics, clinical records, environmental metrics, social variables and climate data, I adopt a holistic approach to studying AMR. This involves examining complex networks of interactions such as horizontal gene transfer, mobile genetic elements (MGEs), microbiome composition, and host-environment interactions.

"Co-infections - where a patient carries more than one pathogen simultaneously - are a central focus of my work, as they often exacerbate AMR, influencing host-pathogen dynamics, immune responses and treatment strategies. AMR arises through resistance gene exchange via MGEs, mutations and microbiome interactions, compounded by complex anthropogenic and ecological factors. To navigate these intricate networks, I employ cutting-edge bioinformatics, AI, digital twinning (the construction of computational replicas of biological systems) and big-data technologies to synthesise insights, correlations and causality across these domains.

"In addition to advancing the understanding of AMR mechanisms, my research supports the development of innovative bioinformatics and AI-powered technologies to drive advancements in diagnostics, surveillance, monitoring, early warning systems and treatment selection.

“Current studies are fragmented and retrospective - showing where resistance appears, but not why it emerges, how it spreads, or how to prevent it. A causal understanding is missing, challenged by the lack of a 360-degree view of interconnected systems of microorganisms, hosts, societies and environments. My research uses AI-enabled solutions to uncover the mechanisms that allow inference of 'why' and 'how' resistance evolves, not merely 'where.'

 "AMR already causes an estimated 1.27 million deaths annually and is projected to reach 10 million per year by 2050. At the individual level, my approach can enable earlier diagnosis, more accurate treatment selection and reduced inappropriate antibiotic use, improving outcomes and limiting treatment failure. At system level, causal digital models and forecasting tools can strengthen national preparedness, allowing earlier detection of emerging resistance patterns and more effective evaluation of intervention strategies.

"My research is fundamentally interdisciplinary and transnational, bringing together clinicians, microbiologists, veterinarians, environmental scientists, AI researchers, hospitals, companies and non-profit organisations within integrated One Health frameworks. I lead and coordinate multiple cross-border initiatives, including an Medical Research Council collaboration with Bangladeshi clinicians and UK microbiologists, Biotechnology and Biological Sciences Research Council project with farms and veterinary partners, and 2 EU funded consortia spanning Switzerland, France, Spain, Italy, Uganda, Ethiopia and South Africa.

"From day one at King's, I have felt fully aligned with its ambition to combine scientific excellence with real-world impact through interdisciplinary approaches. The strong clinical links, the emphasis on translation and the strategic focus on AI and health create an ideal setting to advance my work on AMR within a One Health framework."