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

Sex: All

Ages: 2 Years – 65 Years

Healthy volunteers: No

Enrollment: 300

Sponsor: Yasmin medhat munir Mohamed

Summary

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.

Eligibility Criteria

Inclusion Criteria: * • CsA therapy indicated alone or in combination for GVHD prophylaxis. * Aged 2-65 years. * Clinically stable after first HSCT. Exclusion Criteria: * • Inaccurate sampling or dose administration times. * Patients with missing key covariates. * Patients lacking sufficient pharmacokinetic or TDM data

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View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT07695571). StuddyBuddy aggregates publicly available trial information.