Evidence map›Paper›PMID 25816851›Full record

ArticleMolecular pharmaceutics2015

Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions.

Chelsea M Hosey, Leslie Z Benet

Open access · greenAbstract read
In one paragraph

Article in Molecular pharmaceutics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.7field-weighted citation impact, top 13% 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

16 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Open veterinary journal · 2024
    Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Measures of BSEP Inhibition In Vitro Are Not Useful Predictors of DILI.Toxicological sciences : an official journal of the Society of Toxicology · 2018
    Article
  11. Article
  12. Article
  13. Review
  14. BDDCS, the Rule of 5 and drugability.Advanced drug delivery reviews · 2016
    Review
  15. Review
  16. Article
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.

Chelsea M HoseyDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, United States.
Leslie Z BenetDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, United States.
University of California, San Francisco · US

Funding

UCSF Liver Core CenterP30DK026743 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jennifer Y. Chen · 1986 to 2026
$30.7M
PHARMACOGENETICS OF MEMBRANE TRANSPORTERSU01GM061390 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GIACOMINI, KATHLEEN M · 2000 to 2009
$29.2M
Pharmacogenomics of Membrane TransportersU19GM061390 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI YEE, SOOK WAH · 2010 to 2014
$16.3M
PHARMACEUTICAL SCIENCES AND PHARMACOGENOMICST32GM007175 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AHITUV, NADAV, KROETZ, DEANNA L · 1985 to 2021
$7.1M
A novel mechanistic modeling platform for predicting drug clearance and disposition mediated by transporters and enzymesR43GM113597 · NIGMS · OPTIVIA BIOTECHNOLOGY, INC. · PI BENET, LESLIE Z, HUANG, YONG · 2015 to 2015
$225k
NIDDK NIH HHS P30 DK026743NIGMS NIH HHS GM061390NIGMS NIH HHS GM113597NIGMS NIH HHS R43 GM113597NIGMS NIH HHS T32 GM007175NIGMS NIH HHS U01 GM061390NIGMS NIH HHS U19 GM061390
6 · The paper itself

Abstract

The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model, and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72 ± 9%, 49 ± 10%, and 66 ± 7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74 ± 7%, 85 ± 2%, and 73 ± 8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is determined in vitro.

Indexed as

Models, TheoreticalAnimalsCaco-2 CellsComputer SimulationDogsHumansKidneyLabetalolMadin Darby Canine Kidney CellsPermeabilityZidovudineLabetalolZidovudineBDDCSbiliarydrug eliminationmetabolismpermeabilityrenal

Identifiers

PMID25816851
PMCPMC4666302
OpenAlexW2325449247

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.