MétaCan
Menu
Back to cohort
Record W4414740677 · doi:10.1093/clinchem/hvaf086.663

B-276 Excretion of codeine in human fingerprint sweat and pharmacokinetics following controlled oral codeine administration

2025· article· en· W4414740677 on OpenAlexaff
Daniel J. Brown, Anne Marie Salapatek, Philip Mathew, Venkata Yellepeddi, Paul Wilson

Bibliographic record

VenueClinical Chemistry · 2025
Typearticle
Languageen
FieldChemistry
TopicChemical synthesis and alkaloids
Canadian institutionsGlaxoSmithKline (Canada)
Fundersnot available
KeywordsCodeinePharmacokineticsSWEATBioequivalenceUrineDrugNaltrexone

Abstract

fetched live from OpenAlex

Abstract Background The detection of prescription and/or recreational drugs is important to ensure workplace safety, to enforce judicial actions, and to monitor detoxification. Drugs and drug metabolites are expressed in blood, urine, and oral fluid such that those specimens can be used to detect recent drug use. These specimen matrices offer varying degrees of privacy and invasiveness to the subject. In addition, the ease-of-use in workplace settings varies in terms of convenience, infrastructure requirements, and procedural controls. Sweat patches have been proposed to provide a record of an individual’s drug use, but these typically are worn for one week or longer. Analysis of fingerprint sweat offers a more convenient method of drug detection. This study assessed the comparative profiling of codeine in human fingerprint sweat following controlled codeine administration under naltrexone blockade in the clinic. Methods Thirty-nine healthy adults, including male and non-pregnant female subjects, completed a clinical trial under an ethics board-approved protocol. Each subject received three 60 mg codeine phosphate doses, with four hours between doses. To prevent any opioid effects, each subject received three 50 mg doses of naltrexone hydrochloride: 12 hours, one hour prior, and 12 hours after the first codeine phosphate administration. Fingerprint sweat, blood, and oral fluid specimens were collected at eighteen time points per subject for codeine analysis, beginning at 90 minutes prior to the first codeine phosphate dosage, with the final collection point at 24 hours after the initial codeine dosage. Specimens were collected in order of fingerprint sweat, oral fluid, and blood. Urine specimens were collected ad libitum. Codeine in fingerprint sweat, whole blood, oral fluid, and urine was determined using a validated LC-MS/MS method. Pharmacokinetic parameters were calculated using noncompartmental analysis with PKanalix version 2023R1, Lixoft SAS, a Simulations Plus company. Results Codeine in fingerprint sweat and oral fluid follows the trend seen in whole blood, most notably in response to the three doses of 60 mg codeine phosphate administered at 0, 4, and 8 hours. The concentration versus time profile of codeine in whole blood and fingerprint sweat shows that codeine was first detected in blood and fingerprint within approximately 30 minutes after oral administration of codeine. The calculated Tmax (with standard error) for the first codeine dosage in whole blood, fingerprint sweat, oral fluid, and urine are 1.96 (0.74), 2.08 (0.88), 1.73 (0.85), and 2.20 (1.17) hours, respectively. PK parameters for the excretion of codeine in the terminal phase of the study also compared favorably. Furthermore, PK parameters for this study show broad agreement with published results for blood and oral fluid. Conclusion The time course of mean codeine in fingerprint sweat follows the same response profile as for mean codeine in whole blood and oral fluid. PK parameters computed for codeine in fingerprint sweat, whole blood, oral fluid and urine show broad agreement and statistical agreement for Tmax during the first four hours following oral ingestion of 60 mg codeine, and for T1/2 during the terminal phase of the study following the third dose of codeine.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.369
Teacher spread0.345 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueClinical ChemistrySame topicChemical synthesis and alkaloidsFrench-language works237,207