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SYNTHETIC CONTROL ARMS GENERATED WITH

OSCAR ML

TRANSFORMING AND ACCELERATING YOUR CLINICAL TRIALS

OSCAR ML

OSCAR ML IS A CLOUD-BASED AI/ML APPLICATION FOR CREATING, IN SINGLE-ARM STUDIES, A SYNTHETIC CONTROL ARM (SCA) TO SUBSTITUTE A TRADITIONAL PLACEBO OR CONTROL GROUP WITH REAL-WORLD DATA COLLECTED FROM EXISTING HEALTHCARE INFORMATION

TRANSFORMING AND ACCELERATING CLINICAL TRIALS

WHAT IS OSCAR ML?

SYNTHETIC CONTROL ARMS

It’s a cloud-based, validated AI/ML application for creating synthetic data from real-world data (RWD) collected from existing medical records, disease registries, patient-generated data, claims forms or from other clinical trial data sets, to be used in single-arm studies as a Synthetic Control Arm (SCA) to substitute a traditional placebo or standard of care control group or to be used for the generation of digital twin patients on which to predict the investigational drug or standard of care effect.

The connection to external data sources is via a FHIR protocol, an interoperability standard for electronic exchange of healthcare information.

OSCAR ML offers many interesting features:

  • Stand-alone and cloud-based application
  • Automated patient data anonymization
  • Controlled access and audit trails
  • Selection of data eligible transparent and traceable with audit trials available to Authority’s inspections
  • Universal connector to any kind of external source databases
  • Compliant with the latest Regulatory Authorities guidance on RWD/RWE submission
  • Applicable to any kind of trial protocol
  • Validated according to 21 CFR part 11 and other industry standards
  • GCPs + GDPR compliant

WAITING FOR YOU

We can help you with the evaluation of the most appropriate trial design in order to maximize the chance of success while significantly reduce the overall project timelines and costs.

  • Evaluation of the trial design and methodological support for the submission steps
  • Budgeting and evaluation of the costs
  • Regulatory considerations
  • Data management & analysis

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