The emergence and spread of antibiotic resistant (ABR) bacteria is defined as a global health problem by the WHO. The situation is at its gravest in low- and middle-income countries (including India), where antibiotic consumption is high and largely unregulated. In Europe, an estimated 25,000 patients die annually from ABR bacteria. Treating resistant infections results in extra costs and productivity losses, for e.g., in USA an estimated $21 - $34 billion and in Europe 1.5 billion Euro annually. Despite Norway having amongst the lowest use of antibiotics in all of Europe, there has been a recent increase in reported cases for various ABR infections.
Lack of rapid point-of-care diagnostic tests is central to this problem, as studies show that up to 70% of antibiotics are prescribed incorrectly. This is due to physicians not being able to diagnose patients accurately in real-time, leading to prescription of antibiotics for viral infections, or prescription of broad-spectrum antibiotics that should ideally be kept in reserve. This diagnostic hitch is due to the current standard methodology employed in identifying bacterial infections, where the wait time for results is typically 2 - 4 days.
Taking advantage of the advances in whole genome sequencing, bioinformatics, proteomics and machine learning methods we plan to develop a decision-making tool AMR-Diag, for the detection of bacterial infection, including its resistance profile. We will sequence a number of human clinical samples to cover Extended Spectrum Beta-Lactamases (ESBLs) in Gram negative bacteria with focus on Escherichia coli, Klebsiella, and Acinetobacter. The developed tool will be evaluated on clinical samples from hospitals in Indian and Norway. AMR-Diag tool will be designed for use by doctors and other health care professionals, providing information needed in order to choose the best treatment. Thereby, resulting in more prudent and appropriate use of antibiotics.
