Population pharmacokinetic model and Bayesian estimator for 2 tacrolimus formulations in adult liver transplant patients
| Autor: | Jean Debord, Caroline Monchaud, Camille Riff, Jean-Baptiste Woillard, Pierre Marquet |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Adult
Graft Rejection Male medicine.medical_specialty medicine.medical_treatment Population Urology Liver transplantation Models Biological 030226 pharmacology & pharmacy Tacrolimus Young Adult 03 medical and health sciences 0302 clinical medicine Pharmacokinetics Humans Medicine Pharmacology (medical) Prospective Studies 030212 general & internal medicine Dosing education Aged Pharmacology education.field_of_study business.industry Nonparametric statistics Bayes Theorem Original Articles Middle Aged Liver Transplantation Biological Variation Population Area Under Curve Delayed-Action Preparations Female Transplant patient Adult liver Drug Monitoring business Immunosuppressive Agents |
| Zdroj: | Br J Clin Pharmacol |
| ISSN: | 1365-2125 0306-5251 |
| Popis: | Aims Tacrolimus is a narrow therapeutic range drug that requires fine dose adjustment, for which pharmacokinetic (PK) models have been amply proposed in renal, but not in liver, transplant recipients. This study aimed to build population PK models and Bayesian estimators (BEs) in adult de novo liver transplant patients receiving either the immediate-release (Prograf, twice daily, TD) or prolonged-release (Advagraf, once daily, OD) forms to help PK-guided dose individualization. Methods In total, 160 tacrolimus concentration-time profiles (1654 samples) were collected from 80 patients, at day 7 (D7) and week 6 (W6) post-transplant. Four population PK models were developed using in-parallel parametric and nonparametric approaches for each formulation and period post-transplant. The best limited sampling strategies for estimating the area-under-the-curve (AUC) were selected by comparing predicted values to an independent dataset. Finally, the doses required to reach AUC targets were estimated using each BE and compared to the doses obtained using the trapezoidal AUC. Results Tacrolimus PK was best described using a 1-compartmental model with first-order elimination and 2 γ-distributions to describe the absorption. In the validation datasets, Bayesian AUC estimates yielded mean bias/root mean squared prediction error of −5.06%/13.43% (OD D7), 2.25%/8.51% (OD W6), −2.36%/7.27% (TD D7) and 0.87%/9.07% (TD W6) for the in-parallel parametric approach; and 8.95%/17.84% (OD D7), −0.11%/10.13% (OD W6), 3.57%/18.40% (TD D7) and 4.48%/12.59% (TD W6) for the nonparametric approach. Conclusion The BEs and limited sampling strategies proposed here are able to predict accurately and precisely tacrolimus AUC in liver patients using only 3 plasma concentrations. The dosing methods are available on our ImmunoSuppressive Bayesian dose Adjustment website (www.pharmaco.chu-limoges.fr). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text