Fruit juice inhibition of uptake transport: a new type of food–drug interaction
Bibliographic record
Abstract
A new type of interaction in which fruit juices diminish oral drug bioavailability through inhibition of uptake transport is the focus of this review. The discovery was based on an opposite to anticipated finding when assessing the possibility of grapefruit juice increasing oral fexofenadine bioavailability in humans through inhibition of intestinal MDR1-mediated efflux transport. In follow-up investigations, grapefruit or orange juice at low concentrations potentially and selectively inhibited in vitro OATP1A2-mediated uptake compared with MDR1-caused efflux substrate transport. These juices at high volume dramatically depressed oral fexofenadine bioavailability. Grapefruit was the representative juice to characterize the interaction subsequently. A volume-effect relationship study using a normal juice amount halved average fexofenadine absorption. Individual variability and reproducibility data indicated the clinical interaction involved direct inhibition of intestinal OATP1A2. Naringin was a major causal component suggesting that other flavonoids in fruits and vegetables might also produce the effect. Duration of juice clinical inhibition of fexofenadine absorption lasted more than 2 h but less than 4 h indicating the interaction was avoidable with appropriate interval of time between juice and drug consumption. Grapefruit juice lowered the oral bioavailability of several medications transported by OATP1A2 (acebutolol, celiprolol, fexofenadine, talinolol, L-thyroxine) while orange juice did the same for others (atenolol, celiprolol, ciprofloxacin, fexofenadine). Juice clinical inhibition of OATP2B1 was unresolved while that of OATP1B1 seemed unlikely. The interaction between grapefruit juice and etoposide also seemed relevant. Knowledge of both affected uptake transporter and drug hydrophilicity assisted prediction of the clinical interaction with grapefruit or orange juice.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".