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NCT Number: NCT07549230

Model-Informed Precision Dosing of Tacrolimus in Pediatric Kidney Transplantation

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.

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Key information

Age range

Up to 18 year

Sex eligibility

All sexes

Study type

Observational

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Pediatric patients (< 18 years old).
  • First-time kidney transplant recipients who have less than 20% PRA and no DSA.
  • Adherent to tacrolimus for a year post-transplantation.
  • All data, including therapeutic drug monitoring (TDM) data, are available.

Exclusion criteria

  • Non-adherent patients to tacrolimus.
  • Unavailable or missing data.

Treatment and study plan

Primary outcomes

  1. Development of a novel and applicable dosing algorithm.

    Time frame: June 2026 - January 2027

    A dosing algorithm that rapidly achieves accurate tacrolimus levels within the optimal immunosuppression range despite sparse sampling in routine clinical practice.

Secondary outcomes

  1. Reduction in the risk of acute graft rejection.

    Time frame: June 2026 - January 2027

    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.

Sponsors and collaborators

Lead sponsor

Helwan University

Other

Collaborators

  • Cairo University

Registry information

Official study title

Model-Informed Precision Dosing of Tacrolimus in Pediatric Kidney Transplantation: A Hybrid Population Pharmacokinetics-Machine Learning Approach

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
Apr 24, 2026
Registry last updated
Apr 29, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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