Horizon 2020 BADGER project
Clinical validation for combination therapy
The calScreener™ is being clinically evaluated as a rapid AST instrument for synergy identification in antibiotic combinations against MDR isolates.
The pathogens that are investigated are MDR Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, & Acinetobacter baumannii.
Collaborators

Dr. Christian Giske
EUCAST Chairman
Karolinska Hospital

Dr. Gian Rossolini
Director of Clinical Microbiology
University of Florence

Dr Rafael Canton
EUCAST Clinical Data Coordinator
Hospital RYC, Madrid

Dr. Niels Frimodt-Møller
Head of Clinical Microbiology
Rigshospitalet

Dr. Annelies Verbon
Chair of Medical Microbiology
Erasmus MC

Dr. Willem van Wamel
Head of Staphylococcus Group
Erasmus MC
Clinical Studies
Clinical Study 1
Validated the calScreener™ following clinical routine protocols. Susceptible and resistant reference strains where tested against multiple antibiotics. The results were in concordance with BMD.
Clinical Study 2
Conducted susceptibility testing of stored MDR patient isolates, using a mono and combination therapy for synergy and antagonism identification. The identified synergist combinations were validated in-vivo in a murine sepsis model.
Clinical Study 3
Was conducted as a clinical performance evaluation study following ISO standard 20776-2 using fresh/recent clinical MDR isolates.
Workflow
Monotherapy

Combination Therapy

Results
The first publication from the BADGER project is now available
Isothermal microcalorimetry has several advantages compared to traditional assay technologies for studying AST. The technology has a very high sensitivity compared to optical readouts, enabling a potential early detection of inhibition. The IMC technology can be used under a variety of media conditions, and being a label-free technology, it can also be applied for measurement of samples with complex geometries such as turbid or complex samples.
Want to see some of the preliminary combination testing data? Head over to our clinical application page:

H2020-SMEInst-2-2016-2017
This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 784514.