Goals and Concept

Algorithm

Traditional and state-of-the-art techniques will be utilized and integrated to identify novel host-pathogen interactions and generate a free-to-use web/app-based TAILORED-Treatment predictive algorithm for use by physicians.

Project Goals

1.  Our main goal is to establish a broad-based strategy (not limited to a particular antibiotic group) that can be implemented on a broad scale to increase the effectiveness of antibiotic and antifungal therapy, reduce adverse events, and help limit the emergence of antimicrobial resistance in children and adults. The TAILORED-Treatment project is designed to maximize impact on patients and physicians while integrating and synergising with current EU funded research strategies.

2.  At the heart of the TAILORED-Treatment project is a prospective clinical study in which we will recruit 1200 patients (>2000 patient samples) presenting with respiratory tract infections and/or sepsis. Patient cohorts will include equal representation of genders, children and adults. State-of-the-art molecular and biochemical technologies will be developed and applied to characterize the host and pathogen at the genomic, transcriptomic, proteomic and clinical level. The result will be a large-scale unique multi-dimensional dataset stored in a publically available database, which is accessible to the EU scientific and clinical community.

3.  Next, the consortium partners will develop and apply new computational tools to interrogate the data, in order to provide new insights into personalized host-pathogen interactions, including the discovery of novel biomarkers for patient diagnosis and disease monitoring. By incorporating these new insights into current clinical knowledge, we will construct a predictive personalized treatment algorithm that will lead to informed and personalized antibacterial, antifungal and antimicrobial treatment regimens (indication, dosage, and duration) that are tailored to the needs (type of infection, presence of novel biomarkers etc) of children and adults presenting with respiratory infections and sepsis. Finally, the algorithm and large-scale unique multi-dimensional dataset will be built into an easily navigable web-based, free-to-use, decision support system ready for use by physicians to explore, test and assist in patient-tailored antimicrobial treatment decisions.

 T he TAILORED-Treatment Concept and Workplan

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