The transplanted child: New immunosuppressive agents and the need for pharmacokinetic monitoring
Bibliographic record
Abstract
BACKGROUND: Pharmacokinetic monitoring has been insufficiently studied in paediatric solid organ transplantation, especially because some agents are relatively new to paediatric use, are of new formulation modification or are being used in combinations not previously well studied. The choice of immunosuppressive drugs after paediatric renal transplantation is increasing. Cyclosporine A (CyA), tacrolimus and mycophenolate mofetil (MMF) use has become routine. While pharmacokinetic monitoring of CyA and tacrolimus is routine, few paediatric data on tacrolimus pharmacokinetics exist, and, for MMF, pharmacokinetic monitoring is performed in only a few Canadian centres. The aim of the present article is to provide guidelines for the use of these three drugs by using a large number of full pharmacokinetic profiles in children. METHODS: One hundred forty-nine full pharmacokinetic 10-point profiles on cyclosporine microemulsion, 103 on the classic cyclosporine, 118 on tacrolimus and 114 on MMF were retrospectively analyzed. All pharmacokinetic profiles were obtained from paediatric renal transplant patients in steady state. RESULTS: For pharmacokinetic monitoring of the classic cyclosporine formulation, evaluation of the trough levels suffices to estimate the area under the curve (AUC). For microemulsified cyclosporine, the trough levels do not provide a useful tool, and blood concentrations at 2 or 3 h (C2 or C3) after intake should be measured instead. Tacrolimus trough levels sufficiently estimate the AUC, but measuring the C4 yields the best prediction of the AUC. Nonetheless, C2 also provides a superior tool than the trough levels. Tacrolimus and CyA AUCs change substantially over time after renal transplantation. There is only a poor correlation between the trough level and the AUC for mycophenolic acid (MPA). No single time point provides a surrogate marker of the AUC. At least three time points are required to accurately estimate the AUC, and C1, C2 and C6 serve as the best markers. The article also describes the interaction between MPA and differing concomitant immunosuppression, as well as the variation of the MPA AUC with differing concentrations of cyclosporine. CONCLUSIONS: Pharmacokinetic monitoring of these three drugs is mandatory in paediatric renal transplantation because it is impossible to predict the drug interactions and blood levels from a given dose. Target AUCs for a given time point after transplantation remain to be established.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".