Hospital-Acquired Infections, Multidrug Resistant (MDR) Bacteria, AI, and Alternative Approaches to Antibiotic Therapy
A special issue of Antibiotics (ISSN 2079-6382). This special issue belongs to the section "Antibiotic Therapy in Infectious Diseases".
Deadline for manuscript submissions: 20 September 2026 | Viewed by 355
Special Issue Editors
Interests: host-pathogen interactions; Toll-like receptors signaling in disease models
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Resistance to known and currently used antibiotics represents a growing issue worldwide. It poses a major problem in the treatment of infectious diseases in general and hospital-acquired infections in particular. This is in part due to the overuse and misuse of antibiotics in recent decades, which has led to the selection of highly resistant bacteria and even so-called superbugs, i.e., multidrug-resistant (MDR) bacteria. Nosocomial infections, in particular, are often caused by MDR bacterial pathogens, and their treatment is complicated and extensive, often leading to various side effects. Even though MDR bacteria are widespread globally, their epidemiology varies according to region. Hospital-acquired infections caused by MDR bacteria remain an unresolved problem in the healthcare system. A fundamental part of the overall therapeutic approach is the microbiological examination of adequate clinical materials, in particular, blood culture tests. The results allow for targeted antibiotic therapy based on the identification of bacterial pathogens and the determination of their susceptibility/resistance to antibiotics. Molecular genetic methods play an integral part in solving the problem of bacterial resistance. Only adequately selected molecular typing methods may confirm or rule out epidemiologically related cases. If a new outbreak or even just an increased rate of MDR bacteria is reasonably suspected, then the clonal relationship of strains needs to be analyzed to reveal the source or route of transmission. At the same time, the development of novel antibiotics is lagging, with very few new ones in the pipeline. Finding viable alternatives to treat MDR infections may help in overcoming these therapeutic issues.
Artificial intelligence (AI) and machine learning technologies are emerging as powerful tools in the fight against antimicrobial resistance. AI-powered systems can rapidly analyze microbiological data for faster pathogen identification, predict resistance patterns from genomic sequences, enhance surveillance and outbreak detection, and accelerate drug discovery through computational approaches. These technologies offer promising solutions to improve diagnostic accuracy, optimize treatment protocols, and support antimicrobial stewardship programs.
This Special Issue will showcase papers exploring developments in the field of bacterial resistance, mainly in hospital settings, as well as efficient antibiotic therapy and the identification of useful compounds to tackle this growing issue. We particularly encourage submissions that demonstrate the practical implementation of AI tools in clinical settings and their impact on patient outcomes and antimicrobial stewardship programs. Topics of interest include the following:
- Novel diagnostic methods focusing on rapid MDR identification;
- Alternative therapeutic approaches including combination therapies and stewardship;
- Molecular typing and genomic analysis for understanding resistance transmission;
- AI-powered surveillance, diagnostics and drug discovery to combat antimicrobial resistance.
Dr. Susu Zughaier
Dr. Nayeem Ahmad
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Antibiotics is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- antimicrobial resistance
- hospital-acquired infections
- multidrug resistant
- artificial intelligence
- nosocomial infection
- molecular mechanism of resistant bacteria
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