Eliminating tens of thousands of manual lab experiments, two University of Houston (UH) professors are working toward a method to cut the development time of new antibiotics.
While current practices typically last for more than a decade, a computerized modeling system being developed at UH will speed up this process.
Vincent Tam, associate professor of clinical sciences, and Michael Nikolaou, professor of chemical and biomolecular engineering, are focusing on dosing regimens to reveal which ones are most likely to be effective in combating infection and which are not worth pursuing. It is hoped that pharmaceutical companies can then focus their tests on the most promising regimens.
Their findings recently appeared in the Public Library of Science’s PLoS Computational Biology. This article chronicles the results of a three-year endeavor that was initially funded by a $400,000 grant from the National Science Foundation.
“With microbial resistance to drugs increasing, there is a need to develop new antimicrobial agents rapidly,” Tam said. “Our work proposes a new computational method that will provide quantitative insight to the interaction between certain antibiotics and pathogens. Through pharmacodynamic modeling, which studies the effects of drugs on organisms, our aim is to both help develop new antibiotics and optimize existing medications to curb the prevalence of drug-resistant bacteria.”