ReviewAntibiotics (Basel, Switzerland)2021
Artificial Intelligence and Antibiotic Discovery.
Review in Antibiotics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed.
- Harnessing artificial intelligence for antimicrobial discovery and optimization.Current opinion in microbiology · 2026Review
- Current State of the Fight Against Antimicrobial Resistance: What Are the Different Strategies for Tomorrow?Antibiotics (Basel, Switzerland) · 2026Review
- Artificial Intelligence and the Discovery of Antibiotics: Reinventing with Opportunities, Challenges, and Clinical Translation.Antibiotics (Basel, Switzerland) · 2026Review
- Artificial Intelligence as a Catalyst for Antimicrobial Discovery: From Predictive Models to De Novo Design.Microorganisms · 2026Review
- Bacteriocins fromFrontiers in microbiology · 2026Review
- Glycoconjugate Vaccines Against Nosocomial Klebsiella pneumoniae Infections.Advances in experimental medicine and biology · 2026Article
- CombattingAntibiotics (Basel, Switzerland) · 2025Review
- Advantages and Challenges of Using Antimicrobial Peptides in Synergism with Antibiotics for Treating Multidrug-Resistant Bacteria.ACS infectious diseases · 2025Review
- FDA-Approved Antibacterials and Echinocandins.Antibiotics (Basel, Switzerland) · 2025Review
- Utility of Artificial Intelligence in Antibiotic Development: Accelerating Discovery in the Age of Resistance.Cureus · 2025Review
- Can Artificial Intelligence Enhance the Antimicrobial Effectiveness of Photodynamic Therapy? What We Know and What We Do Not Know?Journal of lasers in medical sciences · 2025Review
- Identifying Potential Natural Antibiotics from Unani Formulas through Machine Learning Approaches.Antibiotics (Basel, Switzerland) · 2024Article
- AI-driven drug discovery: Exploring Abaucin as a promising treatment against multidrug-resistantHealth science reports · 2024Article
- Navigating Antibacterial Frontiers: A Panoramic Exploration of Antibacterial Landscapes, Resistance Mechanisms, and Emerging Therapeutic Strategies.ACS infectious diseases · 2024Review
- Harnessing of Artificial Intelligence for the Diagnosis and Prevention of Hospital-Acquired Infections: A Systematic Review.Diagnostics (Basel, Switzerland) · 2024Review
- Predicting over-the-counter antibiotic use in rural Pune, India, using machine learning methods.Epidemiology and health · 2024Article
- QSAR Studies, Synthesis, and Biological Evaluation of New Pyrimido-Isoquinolin-Quinone Derivatives against Methicillin-ResistantPharmaceuticals (Basel, Switzerland) · 2023Article
- Origin of Antibiotics and Antibiotic Resistance, and Their Impacts on Drug Development: A Narrative Review.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Antibacterial Activity of Nanostructured Zinc Oxide Tetrapods.International journal of molecular sciences · 2023Article
- Molecular interaction of a putative inhibitor with bacterial SHV, an enzyme associated with antibiotic resistance.Royal Society open science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over recent decades, a new antibiotic crisis has been unfolding due to a decreased research in this domain, a low return of investment for the companies that developed the drug, a lengthy and difficult research process, a low success rate for candidate molecules, an increased use of antibiotics in farms and an overall inappropriate use of antibiotics. This has led to a series of pathogens developing antibiotic resistance, which poses severe threats to public health systems while also driving up the costs of hospitalization and treatment. Moreover, without proper action and collaboration between academic and health institutions, a catastrophic trend might develop, with the possibility of returning to a pre-antibiotic era. Nevertheless, new emerging AI-based technologies have started to enter the field of antibiotic and drug development, offering a new perspective to an ever-growing problem. Cheaper and faster research can be achieved through algorithms that identify hit compounds, thereby further accelerating the development of new antibiotics, which represents a vital step in solving the current antibiotic crisis. The aim of this review is to provide an extended overview of the current artificial intelligence-based technologies that are used for antibiotic discovery, together with their technological and economic impact on the industrial sector.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.