Curetis: Cebit 2017: Computational Biologists Predict Antibiotic Resistances Using Biotech
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Every year, some 25,000 people die in the European Union from antibiotic-resistant, hard to treat bacteria. Although there are diagnostic methods in place to recognize such resistances in advance, these are typically very time-consuming. Researchers from the Center for Bioinformatics at Saarland University, in cooperation with the molecular diagnostics company Curetis, are developing techniques to uncover these dangerous resistances a lot faster. Their secret weapons: a comprehensive gene database, and powerful algorithms. The researchers will be presenting their rapid test procedures, and their outlook for the future, at Stand E28 at the Cebit computer trade show in Hannover, Germany.
Just a few days ago, the World Health Organization (WHO) published a list of twelve antibiotic-resistant bacterial strains, which are considered to be the "greatest threats to human health".
Andreas Keller, professor for Clinical Bioinformatics at Saarland University, is also studying these bacterial resistances. “If a patient receives faster access to the treatment best suited to fight the disease in question, it is not only to the benefit of the patient. It also helps dispensing currently available antibiotics in a more targeted manner, so that the development of resistances can be slowed down,” Keller explains.