The TAILORED-Treatment consortium was established to develop new tools aimed 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 consortium was established to develop new tools aimed to increase the effectiveness of antibiotic and antifungal therapy, reduce adverse events, and help limit the emergence of antimicrobial resistance in children and adults. In reality, targeted antimicrobial therapy can most effectively be achieved by utilizing personalized data to facilitate a tailored and optimized approach to individual patient treatment. This can best be achieved by utilizing knowledge gained from both host-centered and pathogen-centered parameters during health and disease. Unfortunately, these parameters have traditionally, tended to be measured independently (for example using microbial culture or PCR-based methods for microbial detection, or measurement of the immune response to infections and/or blood-based biomarkers in the host), and used on an ad hoc basis without careful integration for the best treatment of the patient. However, recent advances in the development of high-throughput and sensitive molecular-based technologies, on-line internet database access tools, and bioinformatics analysis, now means that the goal of personalized medicine and treatment is in sight. Unfortunately however, there currently exists a technological gap between recent state-of-the-art methodologies (for example with respect to gaining new insights into novel host-pathogen interactions) and laboratory-to-bedside results to benefit patients, physicians and society as a whole. The TAILORED-Treatment project is designed to bridge this technological gap in order to generate novel insights and innovations that are readily exploitable for the maximum benefit of multiple stakeholders in the field of personalized medicine and infectious diseases.
Study Type
OBSERVATIONAL
Enrollment
1,200
Hillel Yaffe Medical Center
Hadera, Israel
Sensitivity and specificity for a multi-parametric diagnostic model, incorporating different pathogen- and host-related factors, in differentiating between bacterial and viral etiology in patients with LRTI and/or sepsis
The assesment of the sensitivity and specificity of a multi-parametric diagnostic model, incorporating different pathogen- and host-related factors, in differentiating between bacterial and viral etiology in patients with LRTI and/or sepsis
Time frame: 4 years
Sensitivity and specificity ≥70% for host-related individual biomarkers, in differentiating bacterial or viral or fungal etiology from other etiologies in patients with LRTI and/or sepsis
To identify host-related individual biomarkers that have sensitivity and specificity of ≥70% in differentiating bacterial or viral or fungal etiology from other etiologies in patients with LRTI and/or sepsis
Time frame: 4 years
Sensitivity and specificity ≥70% for sets of blood biomarkers, in differentiating Gram positive or Gram negative or atypical etiology from other disease etiologies in patients with LRTI and/or sepsis
To identify sets of blood biomarkers with sensitivity and specificity of ≥70% in differentiating Gram positive or Gram negative or atypical etiology from other disease etiologies in patients with LRTI and/or sepsis
Time frame: 4 years
Monitoring the temporal dynamics concentrations of blood biomarkers levels during the course of disease in patients with LRTI and/or sepsis
To monitor the temporal dynamics concentrations of blood bio-markers levels during the course of disease in patients with LRTI and/or sepsis including determination of the time required to reach peak levels and the time required to return to normal values.
Time frame: 4 years
A list of significant bacterial microbiome components that are associated with poor or favorable clinical outcome in patients with LRTI and/or sepsis
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To create a list of significant bacterial microbiome components that are associated with poor or favorable clinical outcome in patients with LRTI and/or sepsis
Time frame: 4 years
Sensitivity and specificity ≥70% for liquid chromatography-mass spectrometry and lipid-based Protein Immobilization proteomics-based rapid detection technique in identifying pathogens in clinical samples of patients with LRTI and/or sepsis
To achieve sensitivity and specificity of ≥70% for liquid chromatography-mass spectrometry (LC-MS/MS) and lipid-based Protein Immobilization (LPI) proteomics-based rapid detection technique in identifying pathogens in clinical samples of patients with LRTI and/or sepsis
Time frame: 4 years
To build a web-based application that provides physicians with a recommended antimicrobial treatment based on patients clinical, molecular and biochemical data.
To create an open web-based application that provides physicians with a recommended antimicrobial treatment based on a patient clinical, molecular and biochemical data.
Time frame: 4 years