A team of Israeli biophysicists and doctors say they have developed a mathematical model that could help medical professionals predict whether certain bacteria-fighting antibiotic treatments will fail or succeed. This information could help doctors handpick antibiotics with a greater chance of success and increase patient survival rates.Hebrew University of Jerusalem Prof. Nathalie Balaban and Dr. Maskit Bar-Meir of Jerusalem’s Shaare Zedek Medical Center demonstrated that bacteria thought to be resilient to antibiotic treatment may be treated by currently available antibiotics. “We can predict which antibiotic combination would work on these bacteria and which would not,” Balaban told The Jerusalem Post. “Our understanding could help doctors choose what treatment to give.”It could also save lives.Bacteria develop defenses against hostile elements in their environment,” HU said in a press release. One common tactic is “tolerance” – lying dormant during antibiotic treatment, which allows the bacteria to survive, since antibiotics only spot and kill growing targets.Ultimately, these bacteria become resistant.Antibiotic resistance causes at least 700,000 deaths a year worldwide. In the US, more than 35,000 people die and 2.8 million get sick from antibiotic-resistant infections annually.Without action, according to some reports, the death toll could rise to 10 million people a year by 2050, overtaking cancer as a leading cause of death.In a previous study, Balaban and PhD student Irit Levin-Reisman studied lab-controlled bacteria. They developed a mathematical model that successfully described, measured and predicted when bacteria would develop tolerance to a particular antibiotic. Furthermore, they observed that when bacteria developed tolerance to one antibiotic, they were more likely to develop resistance, HU said.“We observed that bacteria acquired tolerance within a few days,” Balaban said. “These tolerant mutations then acted as a stepping stone to acquire resistance and, ultimately, treatment failure” was the result.Balaban’s lab and Dr. Jiafeng Liu teamed up with Bar-Meir and repeated their study and tolerance-test technique, analyzing daily bacterial samples from patients hospitalized at Shaare Zedek with life-threatening, persistent methicillin-resistant Staphylococcus aureus (MRSA) infections. The pattern they found was strikingly similar to their lab findings: First, the patients’ bacteria developed tolerance, then resistance, and ultimately, antibiotic treatment failed.The intermediary “antibiotic tolerance” stage lasts only a few days and cannot be detected in standard medical labs. But it can be detected using Balaban’s mathematical model.Now, Balaban said she hopes to repeat this experiment in other hospitals and with large enough cohorts of patients to demonstrate efficacy. Then, she said, she will be able to encourage medical centers to adopt the test her team developed, the readout of which would enable doctors to quickly and easily detect whether a patient’s bacteria are tolerant to a planned antibiotic treatment before it is administered.Moreover, based on the patient’s bacteria profile, doctors could handpick antibiotics with a greater chance of success, HU said.“Using the right combination of available antibiotic drugs at the outset could dramatically increase a patients’ survival rate before their infection becomes tolerant to all the antibiotics in our arsenal,” Balaban said.In the long term, she believes the same evolutionary processes involved in the development of antibiotic tolerance and resistance are likely at play in cancer and might be used to inform treatment: Tumor cells might first become tolerant of chemotherapy, develop resistance to it and then develop resistance to other cancer drugs.The study was published in Science magazine.