Evidence map›Paper›PMID 33543792›Full record

ReviewBritish journal of clinical pharmacology2022

A pharmacovigilance study of pharmacokinetic drug interactions using a translational informatics discovery approach.

Lei Wang, Aditi Shendre, Chien-Wei Chiang, Weidan Cao, Xia Ning, Ping Zhang, Pengyue Zhang, Lang Li

Open access · bronzeAbstract readReview
In one paragraph

Review in British journal of clinical pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 26% of its field
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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Lei WangDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.ORCID 0000-0003-1904-1737
Aditi ShendreDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.ORCID 0000-0003-4123-7613
Chien-Wei ChiangDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
Weidan CaoDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
Xia NingDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.ORCID 0000-0002-6842-1165
Ping ZhangDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.ORCID 0000-0002-4601-0779
Pengyue ZhangDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
Lang LiDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
The Ohio State University · USIndiana University School of Medicine

Funding

Machine learning drives translational research from drug interactions to pharmacogeneticsR01LM014199 · NLM · OHIO STATE UNIVERSITY · PI You Chen, Lang Li · 2023 to 2026
$2.5M
Evidence-based Drug-Interaction Discovery: In-Vivo, In-Vitro and ClinicalR01LM011945 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI LI, LANG, ROCHA, LUIS M · 2014 to 2017
$1.8M
A Translational Bioinformatics Approach in the Drug Interaction ResearchR01GM104483 · NIGMS · OHIO STATE UNIVERSITY · PI LI, LANG · 2014 to 2017
$1.5M
NIGMS NIH HHS R01 GM104483NIGMS NIH HHS R01GM104483NLM NIH HHS R01 LM011945NLM NIH HHS R01 LM014199
6 · The paper itself

Abstract

backgroundWhile the pharmacokinetic (PK) mechanisms for many drug interactions (DDIs) have been established, pharmacovigilance studies related to these PK DDIs are limited. Using a large surveillance database, a translational informatics approach can systematically screen adverse drug events (ADEs) for many DDIs with known PK mechanisms.

methodsWe collected a set of substrates and inhibitors related to the cytochrome P450 (CYP) isoforms, as recommended by the United States Food and Drug Administration (FDA) and Drug Interactions Flockhart table™. The FDA's Adverse Events Reporting System (FAERS) was used to obtain ADE reports from 2004 to 2018. The substrate and inhibitor information were used to form PK DDI pairs for each of the CYP isoforms and Medical Dictionary for Regulatory Activities (MedDRA) preferred terms used for ADEs in FAERS. A shrinkage observed-to-expected ratio (Ω) analysis was performed to screen for potential PK DDI and ADE associations.

resultsWe identified 149 CYP substrates and 62 CYP inhibitors from the FDA and Flockhart tables. Using FAERS data, only those DDI-ADE associations were considered that met the disproportionality threshold of Ω > 0 for a CYP substrate when paired with at least two inhibitors. In total, 590 ADEs were associated with 2085 PK DDI pairs and 38 individual substrates, with ADEs overlapping across different CYP substrates. More importantly, we were able to find clinical and experimental evidence for the paclitaxel-clopidogrel interaction associated with peripheral neuropathy in our study.

conclusionIn this study, we utilized a translational informatics approach to discover potentially novel CYP-related substrate-inhibitor and ADE associations using FAERS. Future clinical, population-based and experimental studies are needed to confirm our findings.

Indexed as

Drug-Related Side Effects and Adverse ReactionsPharmacovigilanceAdverse Drug Reaction Reporting SystemsCytochrome P-450 Enzyme InhibitorsCytochrome P-450 Enzyme SystemDatabases, FactualDrug InteractionsHumansUnited StatesUnited States Food and Drug AdministrationCytochrome P-450 Enzyme InhibitorsCytochrome P-450 Enzyme Systemadverse drug eventscytochrome P450drug interactionstranslational research

Identifiers

PMID33543792
PMCPMC12167830
OpenAlexW3128406311

What OpenQuestion holds

Textmetadata
LicenceTDM
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.