Chemometric histopathology via coherent Raman imaging for precision medicine

Introduction

The CHARM project aims to radically transform the cancer diagnosing process and bring the emerging field of digital histopathology to the next level. It introduces a novel technology for tissue analysis, capable of measuring the molecular composition of patient tissue samples and recognizing and classifying tumors in a completely label/stain-free way.

Technology Overview

The instrument, integrated with artificial intelligence (AI), will offer histopathologists a reliable, fast, and low-cost Clinical Decision Support System (CDSS) for cancer diagnosis and personalized cancer therapy.

Medical Device Development

We will develop a Class C medical device (IVDR, In-Vitro Diagnostic Regulation) consisting of a turnkey low-cost broadband Coherent Raman Scattering (CRS) microscope. This device will be enabled by our patented graphene-based fiber laser technology and will be named the Chemometric Pathology System (CPS).

AI Integration

The CPS will integrate an AI module based on deep learning, statistics, and machine learning. It will be capable of automatically analyzing unstained tissues, providing fast and accurate tumor identification by differentiating normal versus neoplastic tissues with accuracy greater than 98%.

Diagnostic Accuracy

The system will also predict final tumor diagnosis by differentiating and grading histologic subtypes with accuracy greater than 90%. This will offer histopathologists a decision tree compatible with existing clinical protocols but with biomolecular-based objectivity and reduced time to result (TRL6).

Business Development

We will develop a robust business case for the application and ensure the project's continuation to higher TRLs and the final market entrance.

Project Foundation

This proposal builds on the results of the ERC POC project GSYNCOR.