Caris CODEai | Caris Life Sciences

Caris CODEai

Caris CODEai™ is the most comprehensive, real-world data platform integrating Caris’ extensive catalog of molecular data with cancer treatment information and clinical outcomes data for more than 295,000 patients covering greater than one million data points per patient.

The Caris CODEai* state-of-the-art informatics system and big data architecture provides an unmatched resource for developing a better understanding of the molecular mechanisms of cancer and helps researchers and biopharmaceutical companies derive unique insights to support commercial and product development objectives, clinical trial services, target identification and research initiatives.

Features multiple data visualization tools to support cohort analysis based on user-defined search queries.

  • Demographic Information
  • Molecular and Diagnostic Data
  • Treatment Information
  • Survival/Outcomes Data

Molecular Data

  • DNA
  • RNA
  • Proteins

Clinical Information

  • Real-World Data
  • Demographic Stats
  • Treatment Information
  • Survival/Outcomes Data

Caris CODEai

  • Molecular Data Combined with Clinical Information
  • Big Data Architecture
  • Data Visualization
  • HIPAA Compliant

Transformative
Healthcare Impact

  • Identify Novel Biomarkers and Molecular Signatures
  • Drives Cancer Insights
  • Optimize Clinical Trials

MATCHED Molecular and Clinical Data

Data Points per Patient

To schedule a demo with a Caris Molecular Science Liaison and for user access, please contact us.

* Caris CODEai is not yet available to international members.

Caris CODEai

Cohort Designer allows users to easily create unique subsets of patients for analysis based on clinical, pathological, molecular features and therapies.

Caris FOLFIRSTai is the first clinically validated, AI-powered molecular predictor of chemotherapy efficacy for mCRC patients. Caris FOLFIRSTai is included for mCRC cases at no additional cost, increased turnaround time or added specimen requirements.

Caris GPSai, a Genomic Probability Score, uses whole exome (DNA) sequencing and whole transcriptome (RNA) sequencing coupled with machine learning to aid in identifying the tissue of origin.

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