Timely Ordering of Pharmacogenetic Testing

NCT06902688 | Recruiting

• 1 other identifier: 3423
• Study Type: interventional
• Target: 275
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Prediction Models; Pediatrics; Precision Medicine; Machine Learning

Keywords

precision medicine; machine learning; pharmacogenetics; prediction models; pediatrics

Outcome Measures

Primary Outcomes (1)

• Proportion of Patients with Pharmacogenetic Testing

  The primary outcome will be the proportion of patients with pharmacogenetic testing offered among those who receive a medication with a pharmacogenetic indication within three months of prediction time. Testing must be offered prior to receipt of the first targeted medication.

  Day 1 to 3 months

Secondary Outcomes (2)

• Number of patients with pharmacogenetic results available prior to receipt of targeted medication

  Day 1

• Number of patients who have alteration in medication choice or dose based on pharmacogenetic results

  Day 1

Study Arms (1)

ML model

EXPERIMENTAL

Participants predicted by an ML model to receive a "targeted medication" within three months following admission.

Other: ML-based intervention

Interventions

ML-based intervention OTHER

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.

ML model

Eligibility Criteria

• Age: 6 Months - 18 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64)

You may qualify if:

• Inpatient at The Hospital for Sick Children
• Between 6 months to 18 years old

You may not qualify if:

• Prior pharmacogenetic testing and/or prior receipt of a targeted medication
• Current Intensive Care Unit (ICU) admission
• Expected hospital discharge is prior to midnight on the day of admission

Sponsors & Collaborators

• The Hospital for Sick Children: lead

Study Sites (1)

The Hospital for Sick Children

Toronto, Ontario, M5G1X8, Canada

RECRUITING

Study Officials

• Lillian Sung, MD, PhD

  The Hospital for Sick Children

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Lillian Sung, MD, PhD

CONTACT

4168135287; lillian.sung@sickkids.ca

Agata Wolochacz, BMSc

CONTACT

4168137654; lillian.sung@sickkids.ca

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: SUPPORTIVE CARE
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Chief Clinical Data Scientist, Paediatric Oncologist

Study Record Dates

• First Submitted: March 13, 2025
• First Posted: March 30, 2025
• Study Start: June 10, 2025
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): June 10, 2027
• Last Updated: March 5, 2026

Record last verified: 2026-02

Data Sharing

• IPD Sharing: Will not share

Locations

CA (1)