Evidence map›Paper›PMID 26904384›Full record

ArticleCPT: pharmacometrics & systems pharmacology2015

Quantitative prediction and clinical evaluation of an unexplored herb-drug interaction mechanism in healthy volunteers.

B T Gufford, J T Barr, V González-Pérez, M E Layton, J R White, N H Oberlies, M F Paine

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. Identification of Intestinal UDP-Glucuronosyltransferase Inhibitors in Green Tea (Drug metabolism and disposition: the biological fate of chemicals · 2018
    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

7 authors.

B T GuffordCollege of Pharmacy Washington State University Spokane, Washington USA.
J T BarrCollege of Pharmacy Washington State University Spokane, Washington USA.
V González-PérezCollege of Pharmacy Washington State University Spokane, Washington USA.
M E LaytonCollege of Medical Sciences Washington State University Spokane, Washington USA.
J R WhiteCollege of Pharmacy Washington State University Spokane, Washington USA.
N H OberliesDepartment of Chemistry and Biochemistry University of North Carolina at Greensboro Greensboro North Carolina USA.
M F PaineCollege of Pharmacy Washington State University Spokane, Washington USA.

Funding

Indiana University Comprehensive Training in Clinical PharmacologyT32GM008425 · NIGMS · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI Zeruesenay Desta, Michael Thomas Eadon · 1992 to 2026
$7.7M
Mechanisms Underlying Drug-Diet InteractionsR01GM077482 · NIGMS · WASHINGTON STATE UNIVERSITY · PI PAINE, MARY F · 2007 to 2014
$3.3M
NIGMS NIH HHS R01 GM077482NIGMS NIH HHS T32 GM008425
6 · The paper itself

Abstract

Quantitative prediction of herb-drug interaction risk remains challenging. A quantitative framework to assess a potential interaction was used to evaluate a mechanism not previously tested in humans. The semipurified milk thistle product, silibinin, was selected as an exemplar herbal product inhibitor of raloxifene intestinal glucuronidation. Physiologically based pharmacokinetic (PBPK) model simulations of the silibinin-raloxifene interaction predicted up to 30% increases in raloxifene area under the curve (AUC0-inf) and maximal concentration (Cmax). Model-informed clinical evaluation of the silibinin-raloxifene interaction indicated minimal clinical interaction liability, with observed geometric mean raloxifene AUC0-inf and Cmax ratios lying within the predefined no effect range (0.75-1.33). Further refinement of PBPK modeling and simulation approaches will enhance confidence in predictions and facilitate generalizability to additional herb-drug combinations. This quantitative framework can be used to develop guidances to evaluate potential herb-drug interactions prospectively, providing evidenced-based information about the risk or safety of these interactions.

Identifiers

PMID26904384
PMCPMC4759704

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.