SYNERGY-AI: Artificial Intelligence Based Precision Oncology Clinical Trial Matching and Registry
Last updated on July 2021Recruitment
- Recruitment Status
- Recruiting
- Estimated Enrollment
- 1500
Summary
- Conditions
- Cancer of Kidney
- Bladder Cancer
- BRCA Gene Rearrangement
- Breast Cancer
- Cancer of Stomach
- Non Hodgkin Lymphoma
- Cancer of Pancreas
- Cancer of Rectum
- Endometrial Cancer
- Ovarian Cancer
- Cancer Metastatic
- Glioblastoma
- Myelofibrosis
- Neuroendocrine Tumors
- Testicular Cancer
- Central Nervous System Tumor
- Cancer
- Cancer Liver
- Cancer of Neck
- Cancer, Advanced
- Cancer of Cervix
- Cancer Breast
- Cancer, Lung
- Carcinoma
- Cancer Prostate
- Cancer of Colon
- Urothelial Carcinoma
- Myeloproliferative Disorders
- Non -Small Cell Lung Cancer
- COVID
- Mismatch Repair Deficiency
- Mantle Cell Lymphoma
- Cancer of Esophagus
- Cancer of Skin
- Melanoma
- Cancer of Larynx
- Cancer of Liver
- Follicular Lymphoma
- Leukemia
- Marginal Zone Lymphoma
- Myelodysplastic Syndromes
- Myeloproliferative Neoplasm
- Cholangiocarcinoma
- Design
- Observational Model: CohortTime Perspective: Prospective
Participation Requirements
- Age
- Younger than 125 years
- Gender
- Both males and females
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 progra...
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.
Tracking Information
- NCT #
- NCT03452774
- Collaborators
- Not Provided
- Investigators
- Principal Investigator: Selin Kurnaz, PhD Massive Bio, Inc.