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
- BRCA Gene Rearrangement
- Bladder Cancer
- Breast Cancer
- Cancer
- Cancer of Stomach
- Carcinoma
- Melanoma
- Cancer of Neck
- Mismatch Repair Deficiency
- Myelodysplastic Syndromes
- Cancer Liver
- Cancer of Cervix
- Cancer of Colon
- Urothelial Carcinoma
- Myelofibrosis
- Non Hodgkin Lymphoma
- Cancer Breast
- Mantle Cell Lymphoma
- Ovarian Cancer
- Cancer of Rectum
- Myeloproliferative Disorders
- Cancer Metastatic
- Glioblastoma
- Cancer of Skin
- Cancer of Esophagus
- Myeloproliferative Neoplasm
- Cancer, Lung
- Leukemia
- Cancer of Kidney
- Cancer, Advanced
- Neuroendocrine Tumors
- Cancer of Pancreas
- Cancer Prostate
- Central Nervous System Tumor
- Cholangiocarcinoma
- Cancer of Larynx
- Non -Small Cell Lung Cancer
- Cancer of Liver
- Endometrial Cancer
- Marginal Zone Lymphoma
- Testicular Cancer
- COVID
- Follicular Lymphoma
- 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.