Model-Informed Precision Dosing on Cyclosporine Therapy in Hematopoietic Stem Cell Transplant Recipients

Starting soon

Conditions studied: Bone Marrow Transplantation, AML

In brief

The purpose of this study is to develop a new tool that helps doctors choose the right cyclosporine dose for patients undergoing bone marrow transplantation. The tool is designed to predict the best dose using sparse sampling, making it practical for everyday clinical care. It combines information about population pharmacokinetics of cyclosporine with advanced artificial intelligence techniques, including machine learning and deep learning. This tool aims to improve treatment, personalize dosing for each patient, and reduce the risk of graft-versus-host disease.

Key facts

Study ID

NCT07695571

Run by

Yasmin medhat munir Mohamed

People needed

300

Starts

2026-08-01

Expected to finish

2027-06-01

Last updated by the study team

2026-07-10

Who can join

Age: 2 and older, up to 65. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• • CsA therapy indicated alone or in combination for GVHD prophylaxis.
• Aged 2-65 years.
• Clinically stable after first HSCT.

You may not qualify if…

• • Inaccurate sampling or dose administration times.
• Patients with missing key covariates.
• Patients lacking sufficient pharmacokinetic or TDM data

Full record on ClinicalTrials.gov

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