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Record W2161848421 · doi:10.1081/dmr-120005667

<i>N</i>-OXIDATION OF DRUGS ASSOCIATED WITH IDIOSYNCRATIC DRUG REACTIONS

2002· review· en· W2161848421 on OpenAlexafffund
Jack Uetrecht

Bibliographic record

VenueDrug Metabolism Reviews · 2002
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsChemistryDrugReactive intermediateRedoxReactive oxygen speciesNitroReactive nitrogen speciesCombinatorial chemistryPharmacologyBiochemistryOrganic chemistryMedicineAlkylCatalysis

Abstract

fetched live from OpenAlex

Circumstantial evidence strongly suggests that most idiosyncratic drug reactions are due to reactive metabolites of drugs rather than due to the drugs themselves. Many of the drugs that are associated with idiosyncratic drug reactions contain nitrogen. There are many possible reasons for this association. One is simply that many drugs, especially CNS active drugs, contain nitrogen. In addition, nitrogen is relatively easy to oxidize because of its lone pair of electrons and many nitrogen-containing compounds readily undergo redox cycling, which can generate reactive oxygen species. There are several nitrogen-containing function groups that are especially associated with adverse reactions. These include aromatic amines, nitro compounds (nitro compounds are reduced to the same reactive intermediates as are formed by oxidation of the corresponding aromatic amine), hydrazines and compounds that can be oxidized to iminoquinone and related compounds. A greater attention to the issue of reactive metabolites during drug development would likely lead to safer drugs; however, not all drugs that form reactive metabolites are associated with a high incidence of idiosyncratic drug reactions. In addition to the presence of such a group, other factors, such as dose and electron density of the compound, appear to play a role in whether the drug containing such functional groups will be associated with a relatively high incidence of idiosyncratic 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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.164
GPT teacher head0.436
Teacher spread0.272 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations61
Published2002
Admission routes2
Has abstractyes

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