Evidence map›Paper›PMID 37724167›Full record

ReviewMedical review (2021)2022

An update on placental drug transport and its relevance to fetal drug exposure.

Qingcheng Mao, Xin Chen

Open access · diamondAbstract readReview
In one paragraph

Review in Medical review (2021), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

18 citing papers in PubMed, 23 citations in OpenAlex.

  1. Obstetric pharmacogenomics.Journal of basic and clinical physiology and pharmacology · 2026
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  11. Modeling human placental biology: a review of organoid technologies.Frontiers in cell and developmental biology · 2025
    Review
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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

2 authors at 1 institution in 1 country.

Qingcheng MaoDepartment of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington, USA.ORCID https://orcid.org/0000-0002-0830-7627
Xin ChenDepartment of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington, USA.ORCID https://orcid.org/0000-0002-9294-7204
University of Washington · US

Funding

Understanding Fetal Exposure to Cannabinoids Through In Vitro and In Vivo StudiesP01DA032507 · NIDA · UNIVERSITY OF WASHINGTON · PI UNADKAT, JASHVANT D · 2013 to 2023
$12.4M
A Systems Pharmacology approach to predict the effects of pregnancy and infectious diseases on transporter-mediated drug dispositionR01HD102786 · NICHD · UNIVERSITY OF WASHINGTON · PI LANCHOTE, VERA LUCIA, UNADKAT, JASHVANT D · 2021 to 2024
$2.1M
NICHD NIH HHS R01 HD102786NIDA NIH HHS P01 DA032507
6 · The paper itself

Abstract

Pregnant women are often complicated with diseases that require treatment with medication. Most drugs administered to pregnant women are off-label without the necessary dose, efficacy, and safety information. Knowledge concerning drug transfer across the placental barrier is essential for understanding fetal drug exposure and hence drug safety and efficacy to the fetus. Transporters expressed in the placenta, including adenosine triphosphate (ATP)-binding cassette efflux transporters and solute carrier uptake transporters, play important roles in determining drug transfer across the placental barrier, leading to fetal exposure to the drugs. In this review, we provide an update on placental drug transport, including

Indexed as

adenosine triphosphate-binding cassette transportersfetal drug exposurephysiologically based pharmacokinetic modeling and simulationplacental drug transportsolute carrier transporters

Identifiers

PMID37724167
PMCPMC10388746
OpenAlexW4309560738

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.