Relationships between Endogenous Plasma Biomarkers of Constitutive Cytochrome <scp>P</scp>450 3<scp>A</scp> Activity and Single‐Time‐Point Oral Midazolam Microdose Phenotype in Healthy Subjects
Bibliographic record
Abstract
Due to high basal interindividual variation in cytochrome P450 3A (CYP3A) activity and susceptibility to drug interactions, there has been interest in the application of efficient probe drug phenotyping strategies, as well as endogenous biomarkers for assessment of in vivo CYP3A activity. The biomarkers 4β-hydroxycholesterol (4βHC) and 6β-hydroxycortisol (6βHCL) are sensitive to CYP3A induction and inhibition. However, their utility for the assessment of constitutive CYP3A activity remains uncertain. We investigated whether endogenous plasma biomarkers (4βHC and 6βHCL) are associated with basal CYP3A metabolic activity in healthy subjects assessed by a convenient single-time-point oral midazolam (MDZ) phenotyping strategy. Plasma 4βHC and 6βHCL metabolic ratios (MRs) were analysed in 51 healthy adult participants. CYP3A activity was determined after administration of an oral MDZ microdose (100 μg). Simple linear and multiple linear regression analyses were performed to assess relationships between MDZ oral clearance, biomarkers and subject covariates. Among study subjects, basal MDZ oral clearance, 4βHC and 6βHCL MRs ranged 6.5-, 10- and 13-fold, respectively. Participant age and alcohol consumption were negatively associated with MDZ oral clearance (p = 0.03 and p = 0.045, respectively), while weight and female sex were associated with lower plasma 4βHC MR (p = 0.0003 and p = 0.032, respectively). Neither 4βHC nor 6βHCL MRs were associated with MDZ oral clearance. Plasma 4βHC and 6βHCL MRs do not relate to MDZ single-time-point metabolic phenotype in the assessment of constitutive CYP3A activity among healthy individuals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".