SYNERGY-AI: Artificial Intelligence Based Precision Oncology Clinical Trial Matching and Registry
Study Details
Study Description
Brief Summary
International registry for cancer patients evaluating the feasibility and clinical utility of an Artificial Intelligence-based precision oncology clinical trial matching tool, powered by a virtual tumor boards (VTB) program, and its clinical impact on pts with advanced cancer to facilitate clinical trial enrollment (CTE), as well as the financial impact, and potential outcomes of the intervention.
Detailed Description
The SYNERGY Registry is an international prospective, observational cohort study of eligible adult and pediatric pts with advanced solid and hematological malignancies, for whom the decision to consider CTE has already been made by their primary providers (PP). Using a proprietary application programming interface (API) linked to existing electronic health records (EHR) platforms, individual clinical data is extracted, analyzed and matched to a parametric database of existing institutional and non-institutional CT. Machine learning algorithms allow for dynamic matching based on CT allocation and availability for optimized matching. Patients voluntarily enroll into the registry, which is non-interventional with no protocol-mandated tests/procedures - all treatment decisions are made at the discretion of PP in consultation with their pts, based on the AI CT matching report, and VTB support. CTE will be assessed on variables including biomarkers, barriers to enrollment. Study duration anticipated as ~36 mo (~24-mo enrollment followed by 12 mo of data collection, to occur every 3 mo). The primary analysis will be performed 12 mo after last pt enrolled. The impact time to initiation of CTE on PFS and OS will be estimated by Kaplan-Meier and Cox multivariable survival analysis. Enrollment is ongoing, with a target of ≥1500 patients.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Study Group Eligible adult and pediatric pts with advanced solid and hematological malignancies, for whom the decision to consider CTE has already been made by their primary providers (PP). |
Other: Clinical Trial Matching
Using a proprietary application programming interface (API) linked to existing electronic health records (EHR) platforms, individual clinical data is extracted, analyzed and matched to a parametric database of existing institutional and non-institutional CT. Machine learning algorithms allow for dynamic matching based on CT allocation and availability for optimized matching.
|
Outcome Measures
Primary Outcome Measures
- Proportion of patients Eligible for CTE versus Actual CTE [Through study completion, an average of 1 year]
CTE Accrual
Secondary Outcome Measures
- Impact of CTE on Overall Survival (OS), estimated by Kaplan-Meier and Cox multivariable survival analysis [4 years]
OS
- Impact of CTE on Progression-Free Survival (PFS), estimated by Kaplan-Meier and Cox multivariable survival analysis [4 years]
PFS
- Identification of Barriers to CTE [Through study completion, an average of 1 year]
To identify barriers to accruals to clinical trials, as measured and reported by a questionnaire
- Real World Data Analytics [Through study completion, an average of 1 year]
To Analyze Individual Standard of Care Chemotherapy Utilization (nominal), across treatment lines (numeric); data will be combined and aggregated to report chemotherapy utilization rate (%).
- Virtual Tumor Board Utilization [Through study completion, an average of 1 year]
VTB Use Rate
- Time from Intervention to Actual CTE (months) [Through study completion, an average of 1 year]
Time to CTE
Eligibility Criteria
Criteria
Inclusion Criteria:
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Pts with solid and hematological malignancies;
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Pts cancer-related biomarkers, gene variants, fusion and rearrangements (by immunohistochemistry, PCR, FISH or NGS): PD-L1, MSI (MMR), Claudin18.2, Tumor mutational burden/load (TMB), ABL1, ACVR1B, AKT1, AKT2, AKT3, ALK, APC, AR, ATM, ATRX, AURKA, AURKB, BAP1, BCL2, BCL6, BRAF, BRCA1, BRCA2, BTK, CCND1, CCND2, CCND3, CDK4, CDK6, CDKN1A/B, CEBPA, CHEK1, CHEK2, CSF1R, CTNNB1, DAXX, DDR1/2, DNMT3A, EGFR, ERBB2, ERBB3, ERBB4, ERCC4, ER, ESR1, FANCA, FAS, FBXW7, FGFR1, FGFR2, FGFR3, FGFR4, FLT3, GATA3, GATA6, GNAS, HDAC1, HGF, HRAS, IDH1, IDH2, IGF1R, JAK1, JAK2, JAK3, KDR (VEGFR2), KIT, KRAS, MAP2K2 (MEK2), MAP3K1, MCL1, MDM2, MDM4, MEN1, MET, MSH2, MSH3, MSH6, MTOR, MUTYH, MYC, MYCL (MYCL1), NF1, NF2, NOTCH1, NPM1, NRAS, NTRK1, NTRK2, NTRK3, PALB2, PARP1, PARP2, PARP3, PBRM1, PDCD1 (PD1), PDCD1LG2 (PD-L2), PDGFRA, PDGFRB, PIK3C, PMS2, POLD1, POLE, PRDM1, PTCH1, PTEN, RAF1, RB1, RET, RICTOR, ROS1, RPTOR, SDHA/B/C, SMAD, SMARC, SMO, STK11, TGFBR2, TP53, TSC1, TSC2, VEGFA, VHL, WT1, ZNF217, ZNF703, among others.
These biomarkers should be determined by local laboratory, external vendor, or next generation sequencing platform
- Decision to consider clinical trial pre-screening enrollment (CTE) by primary provider and/or patient
Exclusion Criteria:
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ECOG PS > 2;
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Abnormal organ function;
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Hospice enrollment
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Massive Bio, Inc | New York | New York | United States | 10006 |
Sponsors and Collaborators
- Massive Bio, Inc.
Investigators
- Principal Investigator: Selin Kurnaz, PhD, Massive Bio, Inc.
Study Documents (Full-Text)
None provided.More Information
Additional Information:
- Feasibility of precision oncology virtual tumour boards to optimise direct point-of-care management and clinical trial enrolment of advanced cancer patients: New models for personalised oncology
- SYNERGY-AI - Journal of Clinical Oncology (JCO)
Publications
None provided.- SYNERGY-AI