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Record W2900842113 · doi:10.1002/9780470921920.edm145

Oxidative Drug Metabolism by Mammalian Cytochrome<scp>P450</scp>Enzymes Using Their Monooxygenase and Peroxygenase Functions

2017· other· en· W2900842113 on OpenAlexaff
Eugene G. Hrycay, Stelvio M. Bandiera

Bibliographic record

VenueEncyclopedia of Drug Metabolism and Interactions · 2017
Typeother
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMonooxygenaseCytochrome P450BiotransformationDrug metabolismEnzymeChemistryBiochemistryCytochromeProdrugOxidative phosphorylationDrugMetabolismPharmacologyBiology

Abstract

fetched live from OpenAlex

Abstract The cytochrome P450 (CYP) enzyme system represents the predominant biotransformation pathway in the human body for lipophilic exogenous and endogenous compounds. The monooxygenase reaction catalyzed by CYP enzymes involves the addition of one oxygen atom from molecular oxygen to a lipophilic substrate, while incorporating the other oxygen atom into a molecule of water, thereby leading to the production of more polar and easily excreted metabolites. Thus, CYP enzymes are major determinants of duration of action and clearance of drugs. In some cases, CYP enzymes are involved in the formation of chemically reactive and potentially toxic metabolites, as well as in clinically significant drug–drug interactions, which are a widely recognized cause of adverse drug reactions in humans. This chapter focuses on the oxidative biotransformation of therapeutic drugs catalyzed by human CYP enzymes. The topics covered include the identification of human hepatic and extrahepatic CYP enzymes involved in drug biotransformation, CYP bioactivation of prodrugs to pharmacologically active compounds, human CYP drug–drug interactions, CYP monooxygenase and peroxygenase reactions involving drug substrates, and mechanisms involved in CYP oxidative drug reactions.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.315
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.358
Teacher spread0.318 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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