The purpose of this study is to develop a novel and applicable dosing algorithm that helps support the clinical decision to achieve tacrolimus levels within the optimal immunosuppression range despite sparse sampling in routine clinical practice in pediatric kidney transplantation. This clinical decision support tool (CDST) is based on a hybrid population pharmacokinetics-machine learning approach aiming for tacrolimus dose individualization and reducing the risk of acute graft rejection.
Study Type
OBSERVATIONAL
Enrollment
130
Development of a novel and applicable dosing algorithm.
A dosing algorithm that rapidly achieves accurate tacrolimus levels within the optimal immunosuppression range despite sparse sampling in routine clinical practice.
Time frame: June 2026 - January 2027
Reduction in the risk of acute graft rejection.
Reduction in the risk of acute graft rejection by developing a clinical decision support tool (CDST) to guide the dose individualization of tacrolimus following pediatric kidney transplantation.
Time frame: June 2026 - January 2027
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