Brief Description

A molecular diagnostic platform that enables characterization of cellular stress and damage. This technology may be applied to a broad range of clinical settings, from assessing the efficacy of cancer therapies to detecting inflammatory and autoimmune disorders, ischemia/reperfusion injury, and toxic environmental exposures.

Problem

There is a growing demand for accurate molecular diagnostics to assess cellular damage for disease monitoring and treatment. However, traditional types of biomarkers often face challenges such as limited interoperability, low sensitivity, and a lengthy, costly discovery process. These issues create a bottleneck in the development and implementation of effective new diagnostics.

Solution

Our RNA-based diagnostic platform eliminates the need for cell- and organ-specific gene panels, focusing instead on a single universal class of RNA molecules. This novel approach can generate digital, AI/ML-ready biomarkers adaptable to diverse operational workflows, including digital pathology and biofluid-based laboratory tests.

Technology

Our approach integrates advanced molecular biology, next-generation sequencing (NGS) and computational analysis to produce unique diagnostic biosignatures from ribosomal RNA (rRNA)—a universal and abundant type of RNA. Additionally, we aim to use machine learning (ML) algorithms to facilitate the translation of this technology into practical applications for clinical diagnostics.