Clinical trial · Interventional
Deep Clinical Trajectory Modeling to Optimize Accrual to Cancer Clinical Trials
NCT06888089CI-TRIAL-00087508completedN/AClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Cancer | Malignant Neoplasm | ALIAS | 0.90 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| AI-assisted MatchMiner Platform | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (3)
- type
- NO_INTERVENTION
- label
- Group 1: MatchMiner
- description
- Treating oncologists and investigators can use the standard method of accessing the MatchMiner tool to identify potential clinical trials for eligible participants based on structured genomic criteria.
- type
- EXPERIMENTAL
- label
- Group 2: MatchMiner Proactive Notification based on AI-detected progression
- description
- treating oncologists will automatically receive emails with lists of potential genomically matched clinical trials identified by MarchMiner for patients in whom our AI algorithm detects an elevated probability of changing treatment based on imaging reports; oncologists can also still use traditional MatchMiner workflows.
- interventionNames
- Other: AI-assisted MatchMiner Platform
- type
- EXPERIMENTAL
- label
- MatchMiner AI with Proactive Notification Based on AI-detected progression + Study Team Confirmation
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: -≥ 18 years of age -adults with any type of cancer whose tumors underwent OncoPanel genomic sequencing from 2013-2022 Exclusion Criteria: -≤ 18 years of age.
References
Publications (1)
- DERIVEDMazor T, Farhat KS, Trukhanov P, Lindsay J, Galvin M, Mallaber E, Paul MA, Hassett MJ, Schrag D, Cerami E, Kehl KL. Clinical Trial Notifications Triggered by Artificial Intelligence-Detected Cancer Progression: A Randomized Trial. JAMA Netw Open. 2025 Apr 1;8(4):e252013. doi: 10.1001/jamanetworkopen.2025.2013. PMID 40257799