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Record W2966237581 · doi:10.4155/bio-2018-0097

Pharmacokinetic Interaction Between Linagliptin and Tadalafil in Healthy Egyptian Males Using a Novel LC–MS Method

2019· article· en· W2966237581 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioanalysis · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of AlbertaAlberta Health Services
FundersU.S. Food and Drug AdministrationEli Lilly and Company
KeywordsPharmacokineticsTadalafilDosingPharmacodynamicsMedicinePharmacologyOral administrationPlasma concentrationBioavailabilityAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Aim: Assessment of pharmacokinetic interaction between linagliptin (LNG) and tadalafil (TDL) in healthy males. Methods: First, a novel LC–MS method was developed; second, a Phase IV, open-label, cross-over study was performed. Volunteers took single 20-mg TDL dose on day 1 followed by wash out period of 2 weeks then multiple oral dosing of 5-mg/day LNG for 13 days. On day 13, volunteers were co-administered 20-mg TDL. Results: LNG and TDL single doses did not affect QTc interval. Smoking did not alter pharmacokinetics/pharmacodynamics of LNG and TDL. Co-administration of LNG with TDL resulted in TDL longer time to reach maximum plasma concentration (Tmax), decreased oral clearance (Cl/F) and oral volume of distribution (Vd/F), increased its maximum plasma concentration (Cmax), area under concentration-time curve (AUC), muscle pain and QTc prolongation. Conclusion: LNG and TDL co-administration warrants monitoring and/or TDL dose adjustment.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.046
GPT teacher head0.365
Teacher spread0.319 · 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