Raiz Diagnostics breaks the bottleneck in expert lymphoma pathology by generating a transcriptomic-derived, clinically actionable diagnosis.

Market Opportunity:

Diagnosing lymphoma today takes over 3 weeks and $10,000+ per patient, relying on a sequential cascade of tests and scarce subspecialty pathology review that many community hospitals cannot access locally, delaying treatment. Raiz replaces that cascade with a single comprehensive test, initially focused on U.S. community hospitals through a centralized CLIA laboratory model.

Technology:

Raiz applies machine learning to bulk RNA-sequencing of standard FFPE biopsy tissue to classify lymphoma subtypes in one assay. The classifier is trained on expert-annotated lymphoma datasets assembled each labeled to gold-standard diagnoses by world-leading hematopathologists, turning an iterative multi-test workup into one decision-grade result.

Advantages:

  • Single-test comprehensive classification
  • Expert-annotated training dataset
  • Standard FFPE biopsy input
  • Faster, lower-cost workup
  • Less subspecialty dependence

Development Stage:

  • Pre-clinical — the classifier is in laboratory development and validation, training on retrospective expert-annotated cases.

IP Protection:

  • Patent applications pending. Additional filings in preparation.

Select Press Releases/Publications/Presentations:

  • Awarded a National Cancer Institute SBIR grant (~$2.3M, non-dilutive) supporting development of the technology.

Contact:

Website: www.raizdx.com

Email: info@raizdx.com 

LinkedIn: linkedin.com/company/raizdx/

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