Accepts Healthy Volunteers
Healthy volunteers are participants who do not have a disease or condition, or related conditions or symptoms
An interventional clinical study is where participants are assigned to receive one or more interventions (or no intervention) so that researchers can evaluate the effects of the interventions on biomedical or health-related outcomes.
An observational clinical study is where participants identified as belonging to study groups are assessed for biomedical or health outcomes.
Searching Both is inclusive of interventional and observational studies.
|Eligible Ages||N/A and Over|
- - 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, 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.
- - 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
This trial id was obtained from ClinicalTrials.gov, a service of the U.S. National Institutes of Health, providing information on publicly and privately supported clinical studies of human participants with locations in all 50 States and in 196 countries.
Phase 1: Studies that emphasize safety and how the drug is metabolized and excreted in humans.
Phase 2: Studies that gather preliminary data on effectiveness (whether the drug works in people who have a certain disease or condition) and additional safety data.
Phase 3: Studies that gather more information about safety and effectiveness by studying different populations and different dosages and by using the drug in combination with other drugs.
Phase 4: Studies occurring after FDA has approved a drug for marketing, efficacy, or optimal use.
The sponsor is the organization or person who oversees the clinical study and is responsible for analyzing the study data.
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.
: 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.