Evidence map›Paper›PMID 26539530›Full record

ArticleBioMed research international2015

How to Choose In Vitro Systems to Predict In Vivo Drug Clearance: A System Pharmacology Perspective.

Lei Wang, ChienWei Chiang, Hong Liang, Hengyi Wu, Weixing Feng, Sara K Quinney, Jin Li, Lang Li

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

3 citing papers in PubMed, 14 citations in OpenAlex.

  1. Application ofFrontiers in toxicology · 2026
    Review
  2. Article
  3. 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

8 authors at 2 institutions in 2 countries.

Lei WangBioinformatics Research Center, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China ; Biomedical Engineering Institute, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China.
ChienWei ChiangCenter for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA ; School of Informatics and Computing, Indiana University, Indianapolis, IN 46202, USA.
Hong LiangBioinformatics Research Center, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China ; Biomedical Engineering Institute, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China.
Hengyi WuCenter for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA ; School of Informatics and Computing, Indiana University, Indianapolis, IN 46202, USA.
Weixing FengBioinformatics Research Center, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China ; Pattern Recognition and Intelligent System Institute, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China.
Sara K QuinneyCenter for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA ; Department of Obstetrics and Gynecology, School of Medicine, Indiana University, Indianapolis, IN 46202, USA.
Jin LiBioinformatics Research Center, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China ; Biomedical Engineering Institute, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China.
Lang LiCenter for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA ; Department of Medical and Molecular Genomics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA.
Harbin Engineering University · CNIndiana University – Purdue University Indianapolis · US

Funding

Quality Assurance and Quality Control Project Management: Improving Submissions and Study Conduct in the Human Subjects Research Prior Approval ProcessUL1TR002529 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI MOE, SHARON M, WIEHE, SARAH ELIZABETH · 2018 to 2022
$27.2M
Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
Clinical Importance of Drug-Drug InteractionsR01AG025152 · NIA · UNIVERSITY OF PENNSYLVANIA · PI HENNESSY, SEAN, LI, LANG · 2006 to 2021
$8.1M
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
NCATS NIH HHS UL1 TR001108NIA NIH HHS R01 AG025152NIGMS NIH HHS R01 GM104483NIGMS NIH HHS R01GM10448301-A1NLM NIH HHS R01 LM011945NLM NIH HHS R01LM011945-01
6 · The paper itself

Abstract

The use of in vitro metabolism data to predict human clearance has become more significant in the current prediction of large scale drug clearance for all the drugs. The relevant information (in vitro metabolism data and in vivo human clearance values) of thirty-five drugs that satisfied the entry criteria of probe drugs was collated from the literature. Then the performance of different in vitro systems including Escherichia coli system, yeast system, lymphoblastoid system and baculovirus system is compared after in vitro-in vivo extrapolation. Baculovirus system, which can provide most of the data, has almost equal accuracy as the other systems in predicting clearance. And in most cases, baculovirus system has the smaller CV in scaling factors. Therefore, the baculovirus system can be recognized as the suitable system for the large scale drug clearance prediction.

Indexed as

In Vitro TechniquesMetabolic Clearance RateModels, BiologicalHumans

Identifiers

PMID26539530
PMCPMC4619875
OpenAlexW1941354194

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.