Antibiotics Resistance: Scientists Develop Algorithm-Based Technique To Personalize Antibiotic Treatments
“It is now possible to computationally predict the level of bacterial resistance for infection-causing bacteria. This is done by weighing of demographic data, including age, gender, pregnancy … together with levels of resistance [which are] measured in the patient’s previous urine cultures as well as their drug purchase history,” Israel Hayom quoted Yelin.
For the research, the scientists analyzed over 700,000 urine cultures. Then they focussed on urine tract infections that involve various types of bacteria, including E. coli, Klebsiella pneumonia and Proteus mirabilis.
The researchers then developed an algorithm, which was based on antibiotic purchases made in the past 10 years for over five million cases. The algorithm provided treatment recommendations based on the infection’s antibiotics resistance.