Coffee inhibition of <scp>CYP</scp>3A4 in vitro was not translated to a grapefruit‐like pharmacokinetic interaction clinically
Bibliographic record
Abstract
Abstract Grapefruit can augment oral medication bioavailability through irreversible (mechanism‐based) inhibition of intestinal CYP3A4. Supplementary data from our recent coffee–drug interaction clinical study showed some subjects had higher area under the plasma drug concentration ‐ time curve (AUC) and plasma peak drug concentration (Cmax) of the CYP3A4 probe felodipine compared to aqueous control. It was hypothesized that coffee might interact like grapefruit in responsive individuals. Beans from six geographical locations were consistently brewed into coffee that was separated chromatographically to a methanolic fraction for in vitro inhibition testing of CYP3A4 metabolism of felodipine at 1% coffee strength. The effect of simultaneous incubation and 10‐min preincubation with coffee fractions determined whether coffee had direct and mechanism‐based inhibitory activity. A subsequent five‐way randomized balanced controlled crossover clinical study evaluated the clinical pharmacokinetic interaction with single‐dose felodipine. Grapefruit juice, water, or three of the in vitro tested coffees were ingested at 300 mL alone 1 h before and then with felodipine. In vitro, all six coffees decreased felodipine metabolism for both simultaneous and preincubation exposure compared to corresponding control. Five coffees demonstrated mechanism‐based inhibition. Grapefruit increased felodipine AUC0–8 (25 vs. 13 ng.h/mL, P < 0.001) and Cmax (5.8 vs. 2.7 ng/mL, P < 0.001) and decreased dehydrofelodipine/felodipine AUC0–8 ratio (0.84 vs. 1.29, P < 0.001), while the three coffees caused no change in these parameters compared to water. Despite high in vitro potency of CYP3A4 inhibition, the coffees did not cause a clinical pharmacokinetic interaction possibly from insufficient amount of inhibitor(s) in coffee reaching intestinal CYP3A4 during the absorption phase of felodipine. The results of this study highlight the need for follow‐up clinical testing when in vitro results indicate the possibility of an interaction.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".