ArticleNature communications2023
A data-driven approach for predicting the impact of drugs on the human microbiome.
Article in Nature communications, 2023. 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, 37 citations in OpenAlex.
- Explainable Stacked Ensemble Learning for Predicting Antibiotic Residues in the Danube River Within the Territory of the City of Novi Sad, Serbia.Antibiotics (Basel, Switzerland) · 2026Article
- Hypocholesterolemic agents and the gut microbiota: a review of interactions and modulatory activity.Pharmacological reports : PR · 2026Review
- Identifying Antibiotic Effects of Investigational Drugs on Commensal Bacteria with Machine Learning.ACS pharmacology & translational science · 2026Article
- The Gut Microbiome Dependency Continuum in Drug Discovery: A Unified Pharmacology Framework Linking Clinical Drugs, Natural Products, and Engineered Microbial Therapeutics.Biotech (Basel (Switzerland)) · 2026Review
- Probiotics mitigate non-antibiotic drug-induced dysbiosis via protein homology-driven competitive binding.Nature communications · 2026Article
- Metagenome-assembled genomes from the gut microbiome of spontaneous diabetic macaques provide insights into microbes associated with type 2 diabetes mellitus.BMC microbiology · 2026Article
- Nutritional Management of Schizophrenia: Gut-Brain Axis Mechanisms and Dietary Interventions.Molecular neurobiology · 2026Review
- Modulating drug response through the gut microbiome: pathways to precision therapy.Archives of microbiology · 2026Review
- Gut dysbiosis in oncology: a risk factor for immunoresistance.Cell research · 2026Review
- Leveraging AI for cell biology discovery.Biochemical Society transactions · 2026Review
- Effects of predatory mite biocontrols on the dispersal of antibiotic resistomes and virulence factors in tea garden soils.Microbiome · 2025Article
- Impact of maternal microbiota imbalance during pregnancy on fetal cerebral neurodevelopment: Is there a link to certain autistic disorders?Brain, behavior, & immunity - health · 2025Review
- Structure-sensitive transformer and multi-view graph contrastive learning enhanced prediction of drug-related microbes.BMC bioinformatics · 2025Article
- A comprehensive landscape of AI applications in broad-spectrum drug interaction prediction: a systematic review.Journal of cheminformatics · 2025Review
- Immunosuppressant imprecision: multidirectional effects on metabolism and microbiome.Clinical microbiology reviews · 2025Review
- Similarity of drug targets to human microbiome metaproteome promotes pharmacological promiscuity.The pharmacogenomics journal · 2025Article
- Pre-trained molecular representations enable antimicrobial discovery.Nature communications · 2025Article
- Risk Factors Analysis of Cutaneous Adverse Drug Reactions Caused by Targeted Therapy and Immunotherapy Drugs for Oncology and Establishment of a Prediction Model.Clinical and translational science · 2025Article
- Molecular Mimicry Between Gut Microbiome and Rheumatoid Arthritis: Current Concepts.Medical sciences (Basel, Switzerland) · 2024Review
- Microplastic diversity increases the abundance of antibiotic resistance genes in soil.Nature communications · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
Many medications can negatively impact the bacteria residing in our gut, depleting beneficial species, and causing adverse effects. To guide personalized pharmaceutical treatment, a comprehensive understanding of the impact of various drugs on the gut microbiome is needed, yet, to date, experimentally challenging to obtain. Towards this end, we develop a data-driven approach, integrating information about the chemical properties of each drug and the genomic content of each microbe, to systematically predict drug-microbiome interactions. We show that this framework successfully predicts outcomes of in-vitro pairwise drug-microbe experiments, as well as drug-induced microbiome dysbiosis in both animal models and clinical trials. Applying this methodology, we systematically map a large array of interactions between pharmaceuticals and human gut bacteria and demonstrate that medications' anti-microbial properties are tightly linked to their adverse effects. This computational framework has the potential to unlock the development of personalized medicine and microbiome-based therapeutic approaches, improving outcomes and minimizing side effects.
Indexed as
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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.