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Record W2914208687 · doi:10.1002/cpt.1392

No Clinically Relevant Interactions of St. John's Wort Extract Ze 117 Low in Hyperforin With Cytochrome P450 Enzymes and P‐glycoprotein

2019· article· en· W2914208687 on OpenAlexaboutno aff
Catherine Zahner, Esther Kruttschnitt, Julia Uricher, Michael Lissy, Martin Hirsch, Simon Nicolussi, Stephan Krähenbühl, Jürgen Drewe

Bibliographic record

VenueClinical Pharmacology & Therapeutics · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDextromethorphanHypericum perforatumHyperforinPharmacokineticsPharmacologyCYP3A4CYP2D6Cytochrome P450ChemistryP-glycoproteinHypericumCYP2C9EnzymeMedicineBiochemistryTraditional medicineAntibiotics

Abstract

fetched live from OpenAlex

Hypericum perforatum L . (St. John's wort) is used to treat mild‐to‐moderate depression. Its potential safety risks are pharmacokinetic drug interactions via cytochrome P450 (CYP) enzymes and P‐glycoprotein, presumably caused by hyperforin. In a phase I, open‐label, nonrandomized, single‐sequence study, the low‐hyperforin Hypericum extract Ze 117 was investigated using a drug cocktail in 20 healthy volunteers. No pharmacokinetic interactions of Ze 117 were observed for CYP 1A2, CYP 2B6, CYP 2C9, CYP 2C19, CYP 3A4, and P‐glycoprotein. Area under the curve ( AUC ) and peak plasma concentration (C max ) of the used probe drugs showed 90% confidence intervals (CIs) of the geometric mean ratios of the drugs taken together with Ze 117 vs. probe drug alone, well within the predefined bioequivalence range of 80–125%. Though Ze 117 did not induce dextromethorphan metabolism by CYP 2D6, it weakly increased dextromethorphan AUC ratio (mean 147.99, 95% CI 126.32–173.39) but not the corresponding metabolic ratio. Ze 117 does not show clinically relevant pharmacokinetic interactions with important CYP s and P‐glycoprotein.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.358
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2019
Admission routes1
Has abstractyes

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