CancerACTIVATENCT07232043
ACTIVATE: AI-driven Clinical-trial Trial-Information and Viability Assessment Tool for EHRs
A study testing MatchMiner-AI Artificial Intelligence Tool in people with Cancer, run by Dana-Farber Cancer Institute at 1 site in United States.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Cancer
- What is being tested?
- MatchMiner-AI Artificial Intelligence Tool
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 70,000 participants
- Where
- 1 siteUnited States
- Study dates
- 20 Jul 2026to 30 Jun 2030
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
Dana-Farber Cancer Institute
Boston, Massachusetts, 02215
Kenneth Kehl, MD, MPH, 617-632-4550, Kenneth_Kehl@dfci.harvard.edu
Kenneth Kehl, MD, MPH
About this study
Official title: AI-driven Clinical-trial Trial-Information and Viability Assessment Tool for EHRs (ACTIVATE)
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.
Read the detailed description
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.
- Conditions
- Cancer
- Being tested
- MatchMiner-AI Artificial Intelligence Tool
- Keywords
- Cancer, Clinical Trial Enrollment, Electronic Health Records, Artificial Intelligence
- Medical subject headings
- Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
MatchMiner-AI Artificial Intelligence ToolOther
Also called MatchMiner-AI Pipeline
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.
| Study group | Role | What they receive |
|---|---|---|
| Standard MatchMiner-AI Workflow | No intervention | Oncologists can access the MatchMiner-AI frontend website to obtain a list of clinical trial options for all participants. |
| Proactive AI-Triggered Notifications | Experimental | 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. Receives: Other: MatchMiner-AI Artificial Intelligence Tool |
What is being measured
The primary outcome is the main question the study is designed to answer.
Proportion clinical trials
The effect of TrialMatch notifications is defined as the proportion of new systemic therapy starts which are clinical trials.
Measured: Assessment will occur at the end of the 1.5 year duration of the intervention.
Secondary outcomes (3)
Proportion clinical trials by race
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.
Measured: Assessment will occur at the end of the 1.5 year duration of the intervention.
Proportion clinical trials by ethnicity
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)
Measured: Assessment will occur at the end of the 1.5 year duration of the intervention.
Proportion clinical trials by age
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.
Measured: Assessment will occur at the end of the 1.5 year duration of the intervention.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Nov 2025
- Study start20 Jul 2026
- Primary completion30 Jun 2030 (estimated)
- Study completion30 Jun 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for CancerStudies of the same condition, open and under way.
- More trials run by Dana-Farber Cancer InstituteThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 70,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Dana-Farber Cancer Institute
- Sponsor type
- University, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Responsible party
- Principal investigator, Kenneth Kehl, Dana-Farber Cancer Institute
- Investigators
- Kenneth L Kehl, MD, Principal investigator, Dana-Farber Cancer Institute
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07232043
- Sponsor's protocol ID
- 25-413
- Other IDs
- 1R37CA295653-01A1
- Acronym
- ACTIVATE
- Status last verified
- Sep 2026
- First submitted
- 14 Nov 2025
- Last updated
- 16 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The Dana-Farber / Harvard Cancer Center encourages and supports the responsible and ethical sharing of data from clinical trials. De-identified participant data from the final research dataset used in the published manuscript may only be shared under the terms of a Data Use Agreement. Requests may be directed to: kenneth\_kehl@dfci.harvard.edu. The protocol and statistical analysis plan will be made available on Clinicaltrials.gov only as required by federal regulation or as a condition of awards and agreements supporting the research.
Study at a glance
From the registry record, last updated by the sponsor on 16 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI-driven Clinical-trial Trial-Information and Viability Assessment Tool for EHRs (ACTIVATE)
- ClinicalTrials.gov ID
- NCT07232043
- Acronym / sponsor ID
- ACTIVATE / 25-413
- Conditions
- Cancer
- Keywords
- Cancer, Clinical Trial Enrollment, Electronic Health Records, Artificial Intelligence
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 70,000 participants (estimated)
- Lead sponsor
- Dana-Farber Cancer InstituteUniversity, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Study start
- 20 Jul 2026 (actual)
- Primary completion
- 30 Jun 2030 (estimated)
- Study completion
- 30 Jun 2030 (estimated)
- First posted
- 18 Nov 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Standard MatchMiner-AI Workflow | No intervention | –Oncologists can access the MatchMiner-AI frontend website to obtain a list of clinical trial options for all participants. |
| Proactive AI-Triggered Notifications | Experimental | Other: MatchMiner-AI Artificial Intelligence ToolOncologists 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- 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.
Key exclusion criteria (1 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| MatchMiner-AI Artificial Intelligence ToolAlso: MatchMiner-AI PipelineOncologists 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 | Proactive AI-Triggered Notifications |
Primary outcome
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.
3 secondary outcomes
Proportion clinical trials by race
Time frame: Assessment will occur at the end of the 1.5 year duration of the intervention.
Proportion clinical trials by ethnicity
Time frame: Assessment will occur at the end of the 1.5 year duration of the intervention.
Proportion clinical trials by age
Time frame: Assessment will occur at the end of the 1.5 year duration of the intervention.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 Sep 2026.
- Individual participant dataSharing planned: Yes. The Dana-Farber / Harvard Cancer Center encourages and supports the responsible and ethical sharing of data from clinical trials. De-identified participant data from the final research dataset used in the published manuscript may only be shared under the terms of a Data Use Agreement. Requests may be directed to: kenneth_kehl@dfci.harvard.edu. The protocol and statistical analysis plan will be made available on Clinicaltrials.gov only as required by federal regulation or as a condition of awards and agreements supporting the research.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Kenneth L Kehl, MD principal investigator
Dana-Farber Cancer Institute
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing MatchMiner-AI Artificial Intelligence Tool in people with Cancer, run by Dana-Farber Cancer Institute at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 16 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Kenneth L Kehl, MD (617-632-4550, kenneth_kehl@dfci.harvard.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Proportion clinical trials (time frame: Assessment will occur at the end of the 1.5 year duration of the intervention.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 16 Sep 2026.