The understanding of phage therapy efficacy in the battle against resistant bacteria has been questioned by many. Due to the nature and complexity of bacteriophages, certain mechanisms need to be understood prior to creating effective therapies. Understanding how best they perform against resistant bacteria, particularly under what condition they perform best, or what factors may result in the ineffectiveness of the therapy, is crucial for the development of treatments.
A predictive model for Phage therapy efficacy
Researchers from Inserm, Université Sorbonne Paris Nord, and Université Paris-Cité at the IAME Laboratory, in collaboration with the Institut Pasteur and the Paris Public Hospitals Group (AP-HP), have taken a leap to address this issue. They have developed a model to better predict phage therapy efficacy. This can possibly assist in the development of more robust clinical trials.
It is well known that bacteriophages have the natural ability to control the population of bacteria and maintain balance, by not allowing bacteria to multiply and take over all living forms. However, only with the recent surge of antibiotic resistance have phages been looked at by many across the globe as a therapeutic agent to battle pathogenic bacteria. In this context, understanding how best to utilize the unique biology of bacteriophages in a clinical context is yet to be understood. The main factors for consideration are to understand what exactly happens in the body, the dosage needed, and the most effective administration method.
In the study of Jérémie Guedj’s research team at Inserm, in collaboration with Laurent Debarbieux’s team at Institut Pasteur, the team attempted to address these factors. To do so, they developed a new mathematical model that helped to understand the interactions between bacteriophages and the pathogenic strain of Escherichia coli in animals. This would assist in the identification of the key parameters that play a role in phage therapy efficacy.
Data collection for phage therapy efficacy
Data from in vitro and in vivo experiments were used to construct the model. The team used the phages’ infection parameters that were determined in the laboratory using a mouse model of lung infection. These parameters included; the duration of the infectious cycle of bacteria, the number of phages released when a bacterium was destroyed through lysis, and others.
Some of the mice were infected with a bioluminescent strain of Escherichia coli. Among them, some were treated with phages with different doses and using different therapeutic administrative methods to test phage therapy efficacy. The quantities of bacteria and bacteriophages were recorded over a period of time and the records were used in the mathematical model. This helped identify which parameters were the most effective in phage therapy.
Factors that play a role in phage therapy efficacy
From the data collected, the researchers were able to identify that the method of administration of the phages was a very important factor that played a role in the animals’ survival. It was observed that the quicker the bacteriophages were placed in contact with the pathogenic bacteria, the better the results. Several administration methods were used in the experiment. The intravenous route was less effective when compared to the intratracheal route, as fewer phages were reaching the lungs. The intratracheal administration also showed that the dosage had played a little effect on the phage therapy efficacy.
The model also incorporated data on the animals’ immune responses in the context of phage therapy. Results confirmed that there indeed is a synergy present between the bacteriophages used in the therapy and the immune system of the animals used in the experiment. This also played a role in the effective elimination of pathogenic bacteria.
“In this study, we propose a new approach to streamline the clinical development of phage therapy, which otherwise continues to have its limitations. Our model could be reused to predict the efficacy of any bacteriophage against the bacteria it targets, once a limited number of in vitro and in vivo data are available on its action. Beyond phage therapy, the model could also be used to test anti-infective therapies based on the association between bacteriophages and antibiotics,” concludes Guedj.
Combination of in vivo phage therapy data with in silico model highlights key parameters for pneumonia treatment efficacy