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NCT Number: NCT07232043

ACTIVATE: AI-driven Clinical-trial Trial-Information and Viability Assessment Tool for EHRs

This study aims to develop and evaluate ACTIVATE, an AI-driven tool for clinical trial information and viability assessment using electronic health records (EHRs). The project will leverage retrospective and prospective EHR data to build and validate algorithms that identify potentially eligible participants for clinical trials and facilitate trial matching.

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Key information

Conditions

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Dana-Farber Cancer Institute

Boston, Massachusetts, 02215, United States

About this study

ACTIVATE is a pragmatic health system intervention designed to improve clinical trial matching and accrual using AI-driven tools integrated with EHR data. The study will first retrospectively analyze data from approximately 70,000 participants who initiated new systemic therapy at Dana-Farber Cancer Institute since 2016 to develop and validate the MatchMiner-AI pipeline.

For the prospective evaluation, all DFCI patients' medical record numbers (MRNs) will be randomized into control and intervention groups. The intervention group will receive proactive notifications to treating oncologists when AI models detect progressive disease and a high probability of starting new treatment, including a ranked list of potential clinical trial options. The control group will continue with standard MatchMiner-AI workflows.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 3.1 The potentially eligible patient population includes any adult (≥18 years old) with a cancer diagnosis receiving care at DFCI. No direct patient recruitment will occur as part of this protocol; all data will be obtained retrospectively or prospectively from routine clinical documentation and electronic health records. TrialForecast will involve aggregate queries of this dataset for cohort size estimation. The randomized interventional component (TrialMatch) is a health system level email "nudge" to treating oncologists providing a list of clinical trial options for patients who have progressive disease based on their imaging reports as detected using our previously developed, validated, and deployed AI model for that purpose. 23-25 Secondary outcomes in our study will include oncologist satisfaction with information delivered via these pipelines. All DFCI oncologists at any DFCI-owned/operated site (Longwood, Chestnut Hill, and regional campus sites) will be eligible to use our pipeline and may receive notifications about clinical trial options for their patients. In 2024, there were approximately 593 such oncologists who had outpatient appointments with at least one patient. Clinicians will constitute study participants as well, since they will have the opportunity to provide feedback on our pipeline to be analyzed by the study team.
  • 3.2 Our project will focus on adults with cancer treated at DFCI, as above. We will not have any mechanism for identifying, targeting, or excluding pregnant women or prisoners.

Exclusion criteria

  • 3.2 Our project will focus on adults with cancer treated at DFCI, as above. We will not have any mechanism for identifying, targeting, or excluding pregnant women or prisoners.

Treatment and study plan

MatchMiner-AI Artificial Intelligence Tool

Other

Oncologists receive email notifications containing a ranked list of potential clinical trial options when AI models detect progressive disease, in addition to standard MatchMiner-AI access.

Other names: MatchMiner-AI Pipeline

Primary outcomes

  1. Proportion clinical trials

    Time frame: Assessment will occur at the end of the 1.5 year duration of the intervention.

    The effect of TrialMatch notifications is defined as the proportion of new systemic therapy starts which are clinical trials.

Secondary outcomes

  1. Proportion clinical trials by race

    Time frame: Assessment will occur at the end of the 1.5 year duration of the intervention.

    The effect of TrialMatch notifications is defined as the proportion of new systemic therapy starts which are clinical trials. The outcome will be stratified by race categories of: American Indian/Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Black or African America, White, and More than One Race.

  2. Proportion clinical trials by ethnicity

    Time frame: Assessment will occur at the end of the 1.5 year duration of the intervention.

    The effect of TrialMatch notifications is defined as the proportion of new systemic therapy starts which are clinical trials. The outcome will be stratified by ethnicity (Hispanic or non-Hispanic)

  3. Proportion clinical trials by age

    Time frame: Assessment will occur at the end of the 1.5 year duration of the intervention.

    The effect of TrialMatch notifications is defined as the proportion of new systemic therapy starts which are clinical trials. The outcome will be stratified by Age categories of: 18-29 years, 30-39 years, 40-49 years, 50-59 years, 60-69 years, 70-79 years, 80-89 years, and 90+ years.

Study contacts

Contact information is provided by the study sponsor or research team.

Kenneth L Kehl, MD

CONTACT

[email protected]

617-632-4550

Sponsors and collaborators

Lead sponsor

Dana-Farber Cancer Institute

Other

Collaborators

  • National Cancer Institute (NCI)

Registry information

Official study title

AI-driven Clinical-trial Trial-Information and Viability Assessment Tool for EHRs (ACTIVATE)

Acronym: ACTIVATE

Important dates

Study start
2026
Primary completion
2030
Study completion
2030
First posted
Nov 18, 2025
Registry last updated
Apr 28, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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