Healthcare (Commonwealth Union) – Concerns have been mounting over the years in regard to Antimicrobial resistance (AMR) across the globe. Over prescribing of antibiotics have often been blamed for AMR. The rapid evolution of superbugs such as Clostridioides difficile have also been a concern in hospital settings. Research has also indicated that other medications may also play a key role in AMR.
A Monash University, Australia led research team has identified that an unconventional combination of two widely used antibiotics can eliminate and prevent the spread of resistance in the highly drug-resistant bacterium Pseudomonas aeruginosa, a pathogen responsible for serious conditions such as bloodstream infections, pneumonia, and meningitis.
Published in The Lancet Microbe, scientists from the Monash Institute of Pharmaceutical Sciences (MIPS) used a validated laboratory infection model that allowed them to test bacterial samples taken from infected patients under simulated hospital antibiotic dosing conditions.
The study highlights a dual β-lactam antibiotic regimen—both belonging to the most commonly prescribed class of drugs for severe infections—as a promising new approach, particularly given that Pseudomonas aeruginosa is classified by the World Health Organization as a high-priority pathogen requiring urgent action.
AMR remains a major global health threat, causing an estimated 1.14 million deaths in 2021 alone. It also threatens to undermine modern medicine, placing essential medical procedures such as surgery, caesarean sections, and cancer chemotherapy at increased risk.
The development of new antibiotics has not kept pace with the rapid rise of antimicrobial resistance (AMR), leaving some bacteria, including Pseudomonas aeruginosa, resistant to nearly all currently available treatments.
Co-lead author Professor Cornelia Landersdorfer from MIPS said the team tested a combination of two β-lactam antibiotics alongside each drug used individually. The dual therapy proved highly effective, producing significantly faster and stronger bacterial killing compared with either antibiotic on its own. It also markedly reduced the emergence of resistance to both drugs.
The researchers then developed a mathematical framework using quantitative systems pharmacology (QSP) to analyse the results from their laboratory infection model and forecast outcomes in patients. QSP modelling integrates biological data, including genetic information, to better understand and predict how medicines behave in the human body and fight disease.
Professor Landersdorfer indicated that this approach, when combined with genomic testing in hospitals, could help pave the way for more tailored and effective antibiotic treatments for life-threatening Pseudomonas aeruginosa infections.
“This research is important because previous approaches to selecting an antibiotic regimen do not account for important pre-existing bacterial characteristics, including mutations, that can influence resistance emergence in bacterial patient isolates of important pathogens such as Pseudomonas aeruginosa.”
The QSP model developed in this study is the first to integrate data on multiple resistance mechanisms found in bacterial samples taken from infected patients prior to treatment, as well as those that arise during antibiotic therapy.
The model provides a detailed description of the full time-course of bacterial growth, bacterial killing, and the development of antibiotic resistance across a range of Pseudomonas aeruginosa strains isolated from patients. Crucially, it also accounts for different resistance pathways, including mutation-driven mechanisms, that contribute to emerging drug resistance.
The strong predictive capability of this new QSP model suggests it could eventually be used to personalise antibiotic regimens based on the specific resistance profile and other key characteristics of the infecting bacterial strain in individual patients.
Lead author Dr Siobhonne Breen from MIPS noted that Pseudomonas aeruginosa can quickly develop resistance even to newer antibiotics when they are used alone. She emphasised the importance of identifying optimal combination therapies that maximise bacterial killing while also limiting the emergence of further resistance.
As AMR remains a serious concern the development of personalized solution could play a key role in tackling the condition.
