RecruitingObservational

SYNERGY-AI: Artificial Intelligence Based Precision Oncology Clinical Trial Matching and Registry

NCT ID: NCT03452774Sponsor: Massive Bio, Inc.Last updated: 2025-10-28

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 ≥50,000 patients.

Arms & interventions

OtherClinical 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

Proportion of patients Eligible for CTE versus Actual CTE
CTE Accrual
Time frame: Through study completion, an average of 1 year

Secondary

Impact of CTE on Overall Survival (OS), estimated by Kaplan-Meier and Cox multivariable survival analysis
Time frame: 4 years
Impact of CTE on Progression-Free Survival (PFS), estimated by Kaplan-Meier and Cox multivariable survival analysis
Time frame: 4 years
Identification of Barriers to CTE
Time frame: Through study completion, an average of 1 year
Real World Data Analytics
Time frame: Through study completion, an average of 1 year
Virtual Tumor Board Utilization
Time frame: Through study completion, an average of 1 year
Time from Intervention to Actual CTE (months)
Time frame: Through study completion, an average of 1 year

Eligibility criteria

Sex: AllAge: All agesHealthy volunteers: No

Inclusion Criteria: * Pts with solid and hematological malignancies; * Pts cancer-related biomarkers, gene variants, fusion and rearrangements (by immunohistochemistry, PCR, FISH or NGS): PD-L1, MSI (MMR), Claudin18.2, HER2/Neu, 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, CEACAM, NRG1, 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: * ECOG PS \> 2; * Abnormal organ function; * Hospice enrollment

View on ClinicalTrials.gov

Conditions

Cancer, MetastaticCancerCancer of PancreasCancer of LiverCancer of StomachCancer LiverCancer of RectumCancer of KidneyCancer of EsophagusCancer of CervixCancer of ColonCancer of LarynxCancer, LungCancer, BreastCancer, AdvancedCancer ProstateCancer of NeckCancer of SkinNeuroendocrine TumorsCarcinomaMismatch Repair DeficiencyBRCA Gene RearrangementNon Hodgkin LymphomaLeukemiaNon Small Cell Lung CancerCholangiocarcinomaGlioblastomaCentral Nervous System TumorMelanomaUrothelial CarcinomaBladder CancerOvarian CancerEndometrial CancerTesticular CancerBreast CancerCOVIDMyelofibrosisMyeloproliferative NeoplasmMyeloproliferative DisordersFollicular LymphomaMantle Cell LymphomaMarginal Zone LymphomaMyelodysplastic Syndromes

Study details

Enrollment: 50,000 participants

Start date: 2018-01-01

Est. completion: 2040-06

Central contacts

Fiona Evans, MS · Contact