Imagine you have 20 novel compounds that have shown some promise in the treatment of TB, a disease that affects 10 million people worldwide and claims 1.5 million lives annually. Because the TB bacteria behave differently in various cell environments and, in some cases, evolve to become drug-resistant, patients will need to take two-drug combinations medications for months or even years in order to receive an effective treatment. Approximately 6,000 possible combinations are provided by 20 compounds in three- and four-drug combinations. How do you choose which medications to test concurrently?
Researchers from Tufts University recently used data from large studies that included laboratory measurements of two-drug combinations of 12 anti-tuberculosis drugs in their study, which was published in the September issue of Cell Reports Medicine. The researchers used mathematical models to come up with a list of requirements that drug pairs must meet in order to be considered as possible treatments in three- and four-drug cocktails.
The amount of testing required before two-drug combinations is moved into further study is significantly reduced when drug pairs are used instead of three-and-four-drug combination measurements.
Bree Aldridge, an associate professor of molecular biology and microbiology at Tufts University School of Medicine and of biomedical engineering at the School of Engineering, as well as an immunologist and molecular microbiologist, says, “Using the design rules we’ve established and tested, we can substitute one drug pair for another drug pair and know with a high degree of confidence that the drug pair should work in concert with the other drug pair to kill the TB bacteria in the rodent model.” “Compared to earlier processes, which had to take into account fewer combinations, the selection process we developed is both more efficient and more accurate in predicting success.”
The Aldridge lab has previously developed and uses DiaMOND, or diagonal measurement of n-way drug interactions, a method to systemically study pairwise and high-order drug combination interactions in order to identify shorter, more effective treatment regimens for TB and possibly other bacterial infections. Aldridge is a corresponding author on the paper and also associate director of the Tufts Stuart B. Levy Center for Integrated Management of Antimicrobial Resistance. Researchers say that the design rules that came out of this new study will make it easier and faster to treat tuberculosis, which is the second-leading infectious killer in the world.
