MedTrace Logo

Deep Clinical Trajectory Modeling to Optimize Accrual to Cancer Clinical Trials

NCT06888089 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 20707

Last updated 2025-03-21

No results posted yet for this study

Summary

This study aims to evaluate the effectiveness of proactive notifications to treating oncologist to optimize participant accrual to clinical trials by utilizing the MatchMiner AI platform. This study compares the standard MatchMinder AI access method to two enhanced recruitment methods.

Conditions

Interventions

OTHER

AI-assisted MatchMiner Platform

A medical record data analysis tool that uses conjunction machine learning and natural language processing models to predict changes in treatment and prognosis and ascertain progression of disease and metastatic sites using retrospective imaging reports. MatchMiner is an established clinical operations tool at Dana-Farber Cancer Institute that links OncoPanel next-generation sequencing data to basic clinical information and clinical trial eligibility criteria to suggest biomarker-selected therapeutic trials for participants.

Sponsors & Collaborators

Principal Investigators

  • Kenneth Kehl, MD, MPH · Dana-Farber Cancer Institute

Study Design

Allocation
RANDOMIZED
Purpose
OTHER
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-01-30
Primary Completion
2024-07-15
Completion
2024-07-15

Countries

  • United States

Study Locations

More Related Trials

Entities

Diseases
Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06888089 on ClinicalTrials.gov