Gram-negative infections are becoming increasingly challenging to treat, particularly in hospital settings, where they can lead to conditions such as urinary tract infections, pneumonia, bloodstream infections, surgical or wound infections, and meningitis. These bacteria are particularly resistant due to their protective capsule, which protects them from being ingested by white blood cells responsible for fighting infections. Furthermore, when these resilient bacteria die, they release toxins from their outer membrane, triggering inflammation, fever, or even septic shock. The ability of gram-negative bacteria to resist multiple antibiotics makes them a significant global health threat, complicating treatment efforts. To combat this, researchers are developing more effective combination therapies that can bypass these bacterial defenses.

Researchers at UH College of Pharmacy (Houston, TX, USA) are developing an advanced monitoring device and data-processing algorithm to aid in the creation of these combination therapies. Their approach involves first identifying effective antibiotic combinations for multidrug-resistant bacteria and then validating the predictions made by their mathematical models with actual clinical outcomes. The researchers will focus on three highly resistant gram-negative strains: P. aeruginosa, A. baumannii, and K. pneumoniae. However, the proposed system is not limited to specific antibiotic-pathogen combinations. It has the potential to be applied to a wide range of antimicrobial agents, including antibacterials, antifungals, and antiretrovirals, as well as to pathogens with diverse microbiological characteristics, such as Neisseria gonorrhoeae, Candida auris, and HIV.

“The rate of new drug development is unlikely to keep pace with the increase in multidrug resistance, so a robust method to guide rational selection of combination therapy would be crucial to delay returning to the pre-antibiotic era. Our long-term goal is to optimize clinical use of antibiotics to combat the emergence of resistance,” said Vincent Tam, professor of Pharmacy Practice and Translational Research at the UH College of Pharmacy who will be leading the development. “Upon completion of our research, clinicians could be guided in the selection of combination therapy, without comprehensive knowledge of the resistance mechanisms involved.” 

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