Treatment of complex infections (like drug-resistant bacteria and bacteria residing in biofilms) is challenging. The currently used diagnostic strategies have their limitations, and as a result clinicians are regularly confronted with discrepancies between lab-determined antibiotic susceptibilities of the pathogens involved and the clinical performance of the selected antibiotic drug regimens. Specific data for The Netherlands are lacking yet antibiotic resistance alone is responsible for an estimated 25,000 deaths/year in the EU and associated with €1.5 billion/year in healthcare costs and productivity losses. In view of the increasing numbers of patients with complex, difficult to treat bacterial infections for which only limited therapeutic options remain, it is crucial to develop novel strategies to facilitate fast and appropriate selection of suitable antibiotic drug options and dosing strategies
Biotrack developed a machine that, based on in situ hybridization, can determine rapidly changes in bacteria after exposure to antibiotics. The objective of this project is to investigate if we can quickly determine with the Biotrack platform the impact of antibiotics on bacteria when they are still in the matrix in which they were present in humans. We anticipate that by combining these data with clinical outcome of the conventional therapy will add essential data to our pharmacometric and machine-learning models, to support development of guidelines that can determine the impact of antibiotic faster and more accurate than the conventional systems. During this project we will increase our scientific knowledge on in vivo behaviour of bacteria, in particular their sensitivity for antibiotics.
With this knowledge we will develop new applications for the Biotrack platform to help clinicians in the near future combatting these devastating infections. A development that will reduce the mortality rate, support recovery and consequently will reduce the health care-, and societal burden for this patients.