Linking the Gastrointestinal Behavior of Ibuprofen with the Systemic Exposure between and within Humans—Part 2: Fed State
Bibliographic record
Abstract
Exploring the intraluminal behavior of an oral drug product in the human gastrointestinal (GI) tract remains challenging. Many in vivo techniques are available to investigate the impact of GI physiology on oral drug behavior in fasting state conditions. However, little is known about the intraluminal behavior of a drug in postprandial conditions. In a previous report, we described the mean solution and total concentrations of ibuprofen after oral administration of an immediate-release (IR) tablet in fed state conditions. In parallel, blood samples were taken to assess systemic concentrations. The purpose of this work was to statistically evaluate the impact of GI physiology (e.g., pH, contractile events) within and between individuals (intra and intersubject variability) for a total of 17 healthy subjects. In addition, a pharmacokinetic (PK) analysis was performed by noncompartmental analysis, and PK parameters were correlated with underlying physiological factors (pH, time to phase III contractions postdose) and study parameters (e.g., ingested amount of calories, coadministered water). Moreover, individual plasma profiles were deconvoluted to assess the fraction absorbed as a function of time, demonstrating the link between intraluminal and systemic behavior of the drug. The results demonstrated that the in vivo dissolution of ibuprofen depends on the present gastric pH and motility events at the time of administration. Both intraluminal factors were responsible for explaining 63% of plasma C max variability among all individuals. For the first time, an in-depth analysis was performed on a large data set derived from an aspiration/motility study, quantifying the impact of physiology on systemic behavior of an orally administered drug product in fed state conditions. The data obtained from this study will help us to develop an in vitro biorelevant dissolution approach and optimize in silico tools in order to predict the in vivo performance of orally administered drug products, especially in fed state conditions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".