<aside> ♋ Looking at imaging tech to identify prognostic markers in tumor slide samples and stains to assist pathologists and accelerate the discovery of clinical biomarkers.

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3 Key Services:

1. Incorporates this AI-based biomarker for patient stratification + Data generation for finding correct screening targets
2. Translational research to find novel biomarkers and assess them based on associations with MoA, pharmacodynamics, patient selection, stratification in clinical trials, etc.
3. CDx and Qualified Biomarker Development → you find histological markers based on associations from phenotype→genotype so that you can assist in detection, symptom, and causation, and potentially inform treatment

• first testing is with NASH [pretty common disease to tackle as we know the biological factors influencing it but also have the highest error rate due to the intricate workings of the disease at levels of progression (similar to cancer)]
• goal is to expand platform into all facets of biopharmaceutical research (identifying drug targets → commercialization)

“Identifying the underlying molecular drivers of cancer has tremendous significance not only for our fundamental understanding of the disease biology but because these image-based assays may also play an important role in making patient treatment decisions in the future, like choosing the most effective therapeutic,” said PathAI co-founder and Chief Executive Officer Andy Beck MD, Ph.D. “Our ability to find these signatures in widely available H&E images suggests that our models could have a great impact, and we look forward to investigating this further and validating these results in future studies.”

How can we get the most accurate patient data from the least amount of input, and map the output to the most actionable markers and metrics?

Phase 1: In the first phase of testing, a collaborative team has trained the PathAI system to look at slides from untreated patients and distinguish tumor from normal tissue. The system can also identify different cell types on a slide reliably.

Before Path AI

After Path AI