Clinical pharmacokinetics · 2026
Structured Evaluation of Model-Informed Precision Dosing of Mycophenolic Acid and Tacrolimus in Pediatric Patients with Kidney Disease.
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Heida Astrid, Cornelissen Elisabeth A M, Aarnoutse Rob E, de Winter Brenda C M, Keizer Ron J, Ter Heine Rob, Jager Nynke G L
Аннотация
BACKGROUND AND OBJECTIVE: Mycophenolic acid and tacrolimus are frequently used in kidney transplant recipients and patients with nephrotic syndrome. For both drugs, therapeutic drug monitoring is recommended. Model-informed precision dosing, not only uses population pharmacokinetic data but also increases flexibility. To optimize treatment with mycophenolic acid and tacrolimus using a limited number of samples, we evaluated model-informed precision dosing for both drugs.
METHODS: We performed the following steps: (1) selection of population pharmacokinetic models; (2) retrospective evaluation using real-world data; and (3) evaluation of limited sampling strategies, (4) prospective evaluation of the predictive performance by predicting an area under the concentration-time curve from time zero to 12 h at a next occasion (3 months later). Acceptable bias and imprecision were defined as a mean prediction error and a normalized root mean square error of less than 25%.
RESULTS: A 3‑point sampling schedule (t = 0, t = 1, t = 2 h) provided accurate area under the concentration-time curve from time zero to 12 h estimation for both drugs, with mean prediction error and normalized root mean square error of 0.1% (- 0.3 to 0.6%) and 21.0% (7.1-34.8%) for mycophenolic acid, and 0.2% (0.03-0.4%) and 7.8% (3.0-12.6%) for tacrolimus. Substantial between-occasion variability limited the prediction of future area under the concentration-time curve from time zero to 12 h. For mycophenolic acid, the mean prediction error was 15.4% (14.4-16.4%) and the normalized root mean square error was 48.6% (18.2-79.0%). For tacrolimus, corresponding values were 64.2% (59.7-68.7%) for mean prediction error and 210% (37.1-383%) for normalized root mean square error.
CONCLUSIONS: Model-informed precision dosing-guided limited sampling strategies are feasible for estimation of current exposure using similar sampling times for mycophenolic acid and tacrolimus. Accurate long-term prediction is not possible, underscoring the need for repeated therapeutic drug monitoring.
CLINICAL TRIAL REGISTRATION: NCT06095895.
METHODS: We performed the following steps: (1) selection of population pharmacokinetic models; (2) retrospective evaluation using real-world data; and (3) evaluation of limited sampling strategies, (4) prospective evaluation of the predictive performance by predicting an area under the concentration-time curve from time zero to 12 h at a next occasion (3 months later). Acceptable bias and imprecision were defined as a mean prediction error and a normalized root mean square error of less than 25%.
RESULTS: A 3‑point sampling schedule (t = 0, t = 1, t = 2 h) provided accurate area under the concentration-time curve from time zero to 12 h estimation for both drugs, with mean prediction error and normalized root mean square error of 0.1% (- 0.3 to 0.6%) and 21.0% (7.1-34.8%) for mycophenolic acid, and 0.2% (0.03-0.4%) and 7.8% (3.0-12.6%) for tacrolimus. Substantial between-occasion variability limited the prediction of future area under the concentration-time curve from time zero to 12 h. For mycophenolic acid, the mean prediction error was 15.4% (14.4-16.4%) and the normalized root mean square error was 48.6% (18.2-79.0%). For tacrolimus, corresponding values were 64.2% (59.7-68.7%) for mean prediction error and 210% (37.1-383%) for normalized root mean square error.
CONCLUSIONS: Model-informed precision dosing-guided limited sampling strategies are feasible for estimation of current exposure using similar sampling times for mycophenolic acid and tacrolimus. Accurate long-term prediction is not possible, underscoring the need for repeated therapeutic drug monitoring.
CLINICAL TRIAL REGISTRATION: NCT06095895.