Evidence map›Paper›PMID 37566133›Full record

ArticleEuropean journal of clinical pharmacology2023

Will artificial intelligence chatbots replace clinical pharmacologists? An exploratory study in clinical practice.

François Montastruc, Wilhelm Storck, Claire de Canecaude, Léa Victor, Julien Li, Candice Cesbron, Yoann Zelmat, Romain Barus

Abstract read
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In one paragraph

Article in European journal of clinical pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  3. Review
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  5. Article
  6. How is AI developing in pharmacovigilance?Therapeutic advances in drug safety · 2026
    Article
  7. Article
  8. Article
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  14. Editorial: Traditional and innovative approaches for signal detection.Frontiers in drug safety and regulation · 2024
    Article
  15. Article
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

8 authors.

François MontastrucDepartment of Medical and Clinical Pharmacology, Centre of Pharmacovigilance and Pharmacoepidemiology, Faculty of Medicine, Toulouse University Hospital (CHU), Toulouse, France.
Wilhelm StorckDepartment of Medical and Clinical Pharmacology, Centre of Pharmacovigilance and Pharmacoepidemiology, Faculty of Medicine, Toulouse University Hospital (CHU), Toulouse, France.
Claire de CanecaudeDepartment of Medical and Clinical Pharmacology, Centre of Pharmacovigilance and Pharmacoepidemiology, Faculty of Medicine, Toulouse University Hospital (CHU), Toulouse, France.
Léa VictorDepartment of Medical and Clinical Pharmacology, Centre of Pharmacovigilance and Pharmacoepidemiology, Faculty of Medicine, Toulouse University Hospital (CHU), Toulouse, France.
Julien LiDepartment of Medical and Clinical Pharmacology, Centre of Pharmacovigilance and Pharmacoepidemiology, Faculty of Medicine, Toulouse University Hospital (CHU), Toulouse, France.
Candice CesbronDepartment of Medical and Clinical Pharmacology, Centre of Pharmacovigilance and Pharmacoepidemiology, Faculty of Medicine, Toulouse University Hospital (CHU), Toulouse, France.
Yoann ZelmatDepartment of Medical and Clinical Pharmacology, Centre of Pharmacovigilance and Pharmacoepidemiology, Faculty of Medicine, Toulouse University Hospital (CHU), Toulouse, France.
Romain BarusDepartment of Medical and Clinical Pharmacology, Centre of Pharmacovigilance and Pharmacoepidemiology, Faculty of Medicine, Toulouse University Hospital (CHU), Toulouse, France. romain.barus@univ-tlse3.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeRecently, there has been a growing interest in using ChatGPT for various applications in Medicine. We evaluated the interest of OpenAI chatbot (GPT 4.0) for drug information activities at Toulouse Pharmacovigilance Center.

methodsBased on a series of 50 randomly selected questions sent to our pharmacovigilance center by healthcare professionals or patients, we compared the level of responses from the chatbot GPT 4.0 with those provided by specialists in pharmacovigilance.

resultsChatbot answers were globally not acceptable. Responses to inquiries regarding the assessment of drug causality were not consistently precise or clinically meaningful.

conclusionThe interest of chatbot assistance needs to be confirmed or rejected through further studies conducted in other pharmacovigilance centers.

Indexed as

Artificial IntelligencePhysiciansHealth PersonnelHumansPharmacovigilanceSoftwareAdverse drug reactionChatGPTDrug information servicePharmacovigilanceSafety

Identifiers

What OpenQuestion holds

Textmetadata
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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.