NCT06902688

Timely Ordering of Pharmacogenetic Testing

Timely Ordering of Pharmacogenetic Testing in Pediatric Oncology

• Status: Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 275 (estimated)
• Sponsor: The Hospital for Sick Children · Academic / Other
• Sex: All
• Age: 6 Months – 18 Years
• Healthy volunteers: Not accepted

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.

Detailed description

This study aims to evaluate the effectiveness of a ML model in predicting patients at high risk of requiring a "targeted medication" within the next three months. A machine learning model will predict, the morning following admission to any inpatient service, whether there will be receipt of a targeted medication within the next three months. The research team will be notified regarding eligible patients each morning, and the research team or pharmacogenomics team will approach the patient's primary care team as applicable. By leveraging ML, this study seeks to enhance the identification of patients who would benefit from such medications in a timely and resource-efficient manner. The study team identified specific medications as indications for pharmacogenetic testing based on prevalence and level of evidence for modifying prescribing practices. These pre-selected medications are referred to as "targeted medications" and are as follows: azathioprine, brivaracetam, clobazam, clopidogrel, flecainide, phenytoin, tacrolimus, voriconazole and warfarin. Only systemically administered (oral, subcutaneous, intramuscular or intravenous) medications or prescriptions (e.g. not topical, intrathecal or intravitreal) are included. Phenytoin was only considered if given orally (to exclude emergency administration without a plan for ongoing treatment). Pharmacogenetic testing will be offered to participants and conducted as addressed in an associated pharmacogenetic testing protocol (REB# 1000053445 PI: Iris Cohn).

Conditions

• Machine Learning
• Prediction Models
• Pediatrics
• Precision Medicine

Interventions

Type	Name	Description
OTHER	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.

Timeline

• Start date: 2025-06-10
• Primary completion: 2026-06-01
• Completion: 2027-06-10
• First posted: 2025-03-30
• Last updated: 2026-03-05

Locations

1 site across 1 country: Canada