ESR-3 Carla Troisi

Università di Bologna, Italy

Integrating TDM and PK/PD to predict outcomes in sepsis and HAP/VAP

Antimicrobial stewardship programs are gaining more and more relevance in optimizing anti-infective treatment and in preventing emergence of antimicrobial resistance. Personalization of antimicrobial treatment based on real-time TDM and dosing adaptation may represent an important tool in antimicrobial stewardship programs. In this ESR/PhD project we aim to characterize the relationship existing between TDM‐based datasets across multiple antibiotics, MICs of clinical isolates and biomarkers profiles (i.e. CRP, procalcitonin and others) in sepsis and pneumonia patients admitted in different hospital wards (i.e. infectious disease, oncohaematological, internal medicine and intensive care unit) with clinical outcomes metrics using pharmacokinetic/pharmacodynamic (PK/PD) modelling. We are interested in comparing classical PK/PD index‐based dosing regimens with PK/PD model‐based predictions of optimal dose regimens that include MIC and biomarker profiles. The ultimate aim of this project is to identify a model based characterization of the relation between PK, MIC and biomarkers to predict outcomes and the role of biomarkers to predict individual PK. We expect that the final optimal model‐based dosing

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Supervisors: Federico Pea, Fabrizio De Ponti

Interests and Hobbies: MOOCs, reading, crafts, archery, meeting people, going on cultural outings, traveling, mathematics, volunteering, learning (all subjects), eating