Evidence map›Paper›PMID 27519549›Full record

ArticleDrug metabolism and disposition: the biological fate of chemicals2016

Hepatic Clearance Predictions from In Vitro-In Vivo Extrapolation and the Biopharmaceutics Drug Disposition Classification System.

Christine M Bowman, Leslie Z Benet

Open access · greenAbstract read
In one paragraph

Article in Drug metabolism and disposition: the biological fate of chemicals, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
3.3field-weighted citation impact, top 6% 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

24 citing papers in PubMed, 51 citations in OpenAlex.

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  9. Recent developments inDrug metabolism reviews · 2021
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  13. In Vitro-In Vivo Inaccuracy: The CYP3A4 Anomaly.Drug metabolism and disposition: the biological fate of chemicals · 2019
    Article
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  20. An examination of protein binding and protein-facilitated uptake relating to in vitro-in vivo extrapolation.European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences · 2018
    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

2 authors at 1 institution in 1 country.

Christine M BowmanDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California.
Leslie Z BenetDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California leslie.benet@ucsf.edu.
University of California, San Francisco · US

Funding

PHARMACEUTICAL SCIENCES AND PHARMACOGENOMICST32GM007175 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AHITUV, NADAV, KROETZ, DEANNA L · 1985 to 2021
$7.1M
NIGMS NIH HHS T32 GM007175
6 · The paper itself

Abstract

Predicting in vivo pharmacokinetic parameters such as clearance from in vitro data is a crucial part of the drug-development process. There is a commonly cited trend that drugs that are highly protein-bound and are substrates for hepatic uptake transporters often yield the worst predictions. Given this information, 11 different data sets using human microsomes and hepatocytes were evaluated to search for trends in accuracy, extent of protein binding, and drug classification based on the Biopharmaceutics Drug Disposition Classification System (BDDCS), which makes predictions about transporter effects. As previously reported, both in vitro systems (microsomes and hepatocytes) gave a large number of inaccurate results, defined as predictions falling more than 2-fold outside of in vivo values. The weighted average of the percentage of inaccuracy was 66.5%. BDDCS class 2 drugs, which are subject to transporter effects in vivo unlike class 1 compounds, had a higher percentage of inaccurate predictions and often had slightly larger bias. However, since the weighted average of the percentage of inaccuracy was still high in both classes (81.9% for class 2 and 62.3% for class 1), it may be currently hard to use BDDCS class to predict potential accuracy. The results of this study emphasize the need for improved in vitro to in vivo extrapolation experimental methods, as using physiologically based scaling is still not accurate, and BDDCS cannot currently help predict accurate results.

Indexed as

BiopharmaceuticsHepatocytesHumansKineticsLiverMicrosomes, LiverPharmaceutical PreparationsPharmaceutical Preparations

Identifiers

PMID27519549
PMCPMC11024986
OpenAlexW2512897046

What OpenQuestion holds

Textmetadata
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.