Pharmacokinetics of Mycophenolic Acid and its Glucuronidated Metabolites in Stable Islet Transplant Recipients
Bibliographic record
Abstract
Given the paucity of data on pharmacokinetics of mycophenolic acid (MPA) in islet transplant, the aim of this study was to characterize pharmacokinetic parameters of MPA and its 2 glucuronidated metabolites in stable islet transplant recipients. Sixteen subjects were entered into this open-label study after written informed consent. Upon administration of a steady-state morning mycophenolate mofetil dose, 12-hour serial concentrations of MPA and its phenolic glucuronide (MPAG) and acyl-glucuronide (AcMPAG) were measured by a validated high-performance liquid chromatography method and pharmacokinetic parameters analyzed by noncompartmental modeling. Subjects included 11 women and 5 men who had received 2.7 +/- 0.8 islet transplants. Age was 50 +/- 8 years, weight 64 +/- 11 kg, serum albumin 4.2 +/- 0.3 g/dL, and serum creatinine 1.1 +/- 0.4 mg/dL. All patients were also on tacrolimus-based steroid-free immunosuppressant regimens. Mycophenolate mofetil dosage ranged from 1 to 2 g daily (25.4 +/- 6.1 mg/kg/d). Pharmacokinetic parameters for MPA were area under the curve 42.9 +/- 21.6 microg h/mL; dose-normalized AUC 52.9 +/- 25.4 microg h/mL/g; maximal concentration (Cmax) 13.0 +/- 6.2 microg/mL; time to Cmax (tmax) 1.2 +/- 0.4 hours; minimum concentration (Cmin) 1.4 +/- 1.0 microg/mL; and MPA-free fraction 1.2% +/- 1.0%. Area under the curve ratios of MPAG/MPA and AcMPAG/MPA were 17.8 +/- 12.4 and 0.1 +/- 0.1, respectively. The wide interpatient variability in all pharmacokinetic parameters of MPA and metabolites are consistent with results from the only other published pharmacokinetic study in islet transplant recipients. A population model and a search for significant covariates may help reduce this variability. Pharmacokinetic parameters calculated in the present study, coupled with findings from the only other published MPA study in islet transplant, form a preliminary base on which to build a population model for future multicenter studies of this little-studied transplant subpopulation.
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.
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) | 0.000 | 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".