Bayesian optimization of tacrolimus exposure in stable kidney transplant patients

Author:

Nguyen Thomas D.12ORCID,Smith Nicholas M.12ORCID,Attwood Kris3ORCID,Gundroo Aijaz4,Chang Shirley45,Yonis Mahfuz45,Murray Brian45,Tornatore Kathleen M.14ORCID

Affiliation:

1. School of Pharmacy & Pharmaceutical Sciences University at Buffalo Buffalo New York USA

2. New York State Center for Excellence in Bioinformatics and Life Sciences Buffalo New York USA

3. Biostatistics School of Public Health and Health Professions Buffalo New York USA

4. Division of Nephrology Department of Medicine Jacobs School of Medicine and Biomedical Sciences University at Buffalo Buffalo New York USA

5. Erie County Medical Center Buffalo New York USA

Abstract

AbstractStudy ObjectiveThe objective was to compare tacrolimus AUC0‐12 determined by Non‐Compartmental Analysis (NCA) using intensive sampling to Maximum a Posteriori‐Bayesian (MAP‐Bayesian) estimates from robust (n = 9 samples/subject) and sparse (n = 2 samples/subject) sampling in 67 stable KTRs and a validation group of similar patients.DesignThis open‐label, prospective, single center 12‐h PK study included nine serial samples collected in KTRs to determine steady‐state NCA tacrolimus AUC0‐12.SettingThis study was conducted at a single site within a large, urban hospital in the western New York area.PatientsThis study described tacrolimus pharmacokinetics in stable kidney transplant recipients on maintenance tacrolimus therapy.InterventionRobust and sparse AUC0‐12 estimates by a MAP‐Bayesian approach were obtained using the Advanced Dosing Solutions (AdDS) and ADAPT5 freeware. Limited sampling strategies were evaluated using the original population PK model (n = 67), which was also assessed using a validation group (n = 15). AUC0‐12 agreement was tested by paired t‐tests with intraclass correlation coefficient (ICC) and Bland Altman analysis.Measurements and Main ResultsA total of 35 Black and 32 White stable KTRs (estimated glomerular filtration rate [eGFR] = 55.2 ± 15.7 mL/min/1.73m2) received the tacrolimus dose of 3.4 ± 1.7 mg/study with troughs of 6.8 ± 1.8 ng/mL. The NCA‐AUC0‐12 was 123.8 ± 33.6 μg·h/L compared to MAP‐Bayesian estimates for Robust‐AUC0‐12 of 124.7 ± 33.3 μg·h/L and optimal 2‐specimen Sparse‐AUC0‐12 of 119.7 ± 32.7 μg·h/L for the training group. Comparison of Robust‐AUC0‐12 to NCA‐AUC0‐12 had an ICC of 0.96 (p = 0.99) while comparison of Robust‐AUC0‐12 to Sparse‐AUC0‐12 using Pre‐dose trough [C(t0h)] and 1 h [C(t1h)] resulted in an ICC of 0.93 (p = 0.014). In the validation group, 5 Black and 10 White KTRs (eGFR = 56.4 ± 16.8 mL/min/1.73m2) received a mean tacrolimus dose of 1.9 ± 1.2 mg/study with a trough of 6.0 ± 1.7 ng/mL. The validation group's NCA‐AUC0‐12 (88.4 ± 33.1 μg·h/L) was comparable to Robust‐AUC0‐12 (85.1 ± 33.8 μg·h/L, ICC = 0.93; p = 0.12) and Sparse‐AUC0‐12 determined from C(t0h) and C(t4h) (86.7 ± 33.9 μg·h/L, ICC = 0.91; p = 0.61).ConclusionMAP‐Bayesian estimation for patient‐specific AUC0‐12 using sparse, two‐specimen sampling is comparable to NCA and may enhance tacrolimus TDM in stable KTRs.

Funder

National Center for Advancing Translational Sciences

National Institute of Diabetes and Digestive and Kidney Diseases

National Institute on Aging

Publisher

Wiley

Subject

Pharmacology (medical)

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