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Timely Ordering of Pharmacogenetic Testing
Sponsor: The Hospital for Sick Children
Summary
The goal of this trial is to learn if a machine learning (ML) model can help optimize drug therapy in the pediatric population. The main question\[s\] it aims to answer are whether a machine learning model predicting receipt of a targeted medication within the next three months: * Increases the offering of pharmacogenetic testing prior to receipt of a targeted medication * Increases the number of patients with pharmacogenetic results prior to receipt of a targeted medication * Increases the number of patients who have alteration in medication choice or dose based on pharmacogenetic results This trial only focuses on the prediction and provision of participants with a high-risk of receiving a medication with a pharmacogenetic indication in the next three months.
Official title: Timely Ordering of Pharmacogenetic Testing in Pediatric Oncology
Key Details
Gender
All
Age Range
6 Months - 18 Years
Study Type
INTERVENTIONAL
Enrollment
275
Start Date
2025-06-10
Completion Date
2027-06-10
Last Updated
2026-03-05
Healthy Volunteers
No
Interventions
ML-based intervention
A ML-based model will predict and identify participants that are at high-risk of receiving a targeted medication within three months after their hospital admission date.
Locations (1)
The Hospital for Sick Children
Toronto, Ontario, Canada