Back

Phage Therapy: Navigating the Mechanisms, Benefits, and Challenges in the Fight Against Multidrug-Resistant Infections

Munshi, M.; Jahangir, S.; Sumaiya, S.

2025-04-22 infectious diseases
10.1101/2025.04.19.25325436 medRxiv
Show abstract

BackgroundThe emergence of multidrug-resistant (MDR) infections represents one of the most critical challenges faced by contemporary medical practice. The World Health Organization (WHO) has identified antibiotic resistance as a significant threat to global health, with MDR bacteria leading to increased morbidity, mortality, and healthcare costs [1]. Objective (PICOS)This review examines (P) MDR infection patients receiving (I) short-term (0-14 day) phage therapy versus (C) long-term/antibiotic treatments, assessing (O) efficacy (eradication rates) and safety (adverse events) through (S) clinical trial/case study analysis. Primary & Secondary Outcome MeasuresEfficacy (bacterial eradication) and safety (adverse events) of 0-14 day phage therapy, compared to conventional antibiotics or longer phage regimens. InterventionApplication of bacteriophages (viruses that infect and lyse bacteria) as targeted antimicrobial agents. MethodsA comprehensive review of clinical trials, case studies, and experimental models from peer-reviewed literature. ResultsPhage therapy demonstrates high bacterial specificity, adaptability to resistance, and synergistic effects with antibiotics. Article SummaryWhile phage therapy offers a promising alternative to antibiotics, its clinical integration faces regulatory, logistical, and safety challenges. Strengths and limitations of this studyThe strengths include detailed analysis of phage mechanisms, clinical applications, and therapeutic potential. The limitations are limited large-scale randomized controlled trials (RCTs) and standardized treatment protocols & last is This review was not registered in PROSPERO. ConclusionPhage therapy holds transformative potential in combating MDR infections but requires further research, regulatory standardization, and clinical validation.

Published in Open Access Journal of Pharmaceutical Sciences and Drugs · not in our set (fewer than 10 published preprints to learn from) · training set

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.