Evidence map›Paper›PMID 31171383›Full record

ReviewTrends in pharmacological sciences2019

Predicting and Understanding the Human Microbiome's Impact on Pharmacology.

Reese Hitchings, Libusha Kelly

Abstract readReview
In one paragraph

Review in Trends in pharmacological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Article
  2. Pharmacomicrobiomics.Clinical pharmacology and therapeutics · 2025
    Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Interactions Between Antidepressants and Intestinal Microbiota.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023
    Article
  11. Article
  12. Review
  13. Review
  14. Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Reese HitchingsDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, The Bronx, NY, USA.
Libusha KellyDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, The Bronx, NY, USA; Department of Microbiology and Immunology, Albert Einstein College of Medicine, The Bronx, NY, USA. Electronic address: libusha.kelly@einstein.yu.edu.

Funding

CTSA Administrative Supplement for Informatics Core: A novel AI/ML system to predict respiratory failure and ARDS in Covid-19 patientsUL1TR002556 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI KELLER, MARLA J, KIM, MIMI Y · 2018 to 2022
$26.7M
NRSA Training CoreTL1TR002557 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI MARANTZ, PAUL R · 2018 to 2022
$1.0M
Clinical and Translational Science AwardTL1TR001072 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI SHAMOON, HARRY · 2013 to 2017
$909k
NCATS NIH HHS TL1 TR001072NCATS NIH HHS TL1 TR002557NCATS NIH HHS UL1 TR002556
6 · The paper itself

Abstract

Our bodies each possess a unique and dynamic collection of microbes and viruses, collectively the 'microbiome', with distinct metabolic capacities from our human cells. Unforeseen modification of drugs by the microbiome can drastically alter their clinical effectiveness, with the most dramatic cases leading to fatal drug interactions. Pharmaceuticals can be activated, deactivated, toxified, or release metabolites that alter the 'canonical' pharmacokinetics of the drug. Thus, predicting and characterizing microbe-drug interactions is necessary to develop and implement personalized drug administration protocols and, more broadly, to improve drug safety and efficacy. In this review, we focus on microbiome-driven alterations to drug pharmacokinetics and provide a research framework for pharmacologists interested in characterizing microbiome interactions with any drug of interest.

Indexed as

ActinobacteriaAnimalsBacteroidesHelicobacter pyloriHumansMicrobiotaPharmaceutical PreparationsPharmacokineticsPrecision MedicinePharmaceutical Preparationsmicrobiomepharmacodynamicspharmacologyxenobiotics

Identifiers

PMID31171383
PMCPMC6758919

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.