Evidence map›Paper›PMID 34085128›Full record

ArticleThe AAPS journal2021

Translational CNS Steady-State Drug Disposition Model in Rats, Monkeys, and Humans for Quantitative Prediction of Brain-to-Plasma and Cerebrospinal Fluid-to-Plasma Unbound Concentration Ratios.

Sho Sato, Kota Matsumiya, Kimio Tohyama, Yohei Kosugi

Open access · hybridAbstract read
In one paragraph

Article in The AAPS journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.1field-weighted citation impact, top 10% 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

17 citing papers in PubMed, 33 citations in OpenAlex.

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  7. Synergistic induction of blood-brain barrier properties.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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

4 authors at 1 institution in 1 country.

Sho SatoGlobal DMPK, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited, Shonan Health Innovation Park (iPark), 26-1, Muraoka-Higashi 2-Chome, Fujisawa, Kanagawa, 251-8555, Japan. sho.sato@takeda.com.
Kota MatsumiyaGlobal DMPK, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited, Shonan Health Innovation Park (iPark), 26-1, Muraoka-Higashi 2-Chome, Fujisawa, Kanagawa, 251-8555, Japan.
Kimio TohyamaGlobal DMPK, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited, Shonan Health Innovation Park (iPark), 26-1, Muraoka-Higashi 2-Chome, Fujisawa, Kanagawa, 251-8555, Japan.
Yohei KosugiGlobal DMPK, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited, Shonan Health Innovation Park (iPark), 26-1, Muraoka-Higashi 2-Chome, Fujisawa, Kanagawa, 251-8555, Japan.
Takeda (Japan) · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Capturing unbound drug exposure in the brain is crucial to evaluate pharmacological effects for drugs acting on the central nervous system. However, to date, there are no reports of validated prediction models to determine the brain-to-plasma unbound concentration ratio (K

Indexed as

Models, BiologicalAnimalsATP Binding Cassette Transporter, Subfamily B, Member 1ATP Binding Cassette Transporter, Subfamily G, Member 2Blood-Brain BarrierCerebrospinal FluidHumansMacaca fascicularisMaleRatsSpecies SpecificityTissue DistributionATP Binding Cassette Transporter, Subfamily B, Member 1ATP Binding Cassette Transporter, Subfamily G, Member 2BCRPblood-brain barrierKp,uu,brainKp,uu,CSFMDR1

Identifiers

PMID34085128
PMCPMC8175309
OpenAlexW3165254967

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.