EU Project : PATH-TOX

PATH-TOX: Drug discovery is a time consuming, expensive and risky process. Each drug to market must undergo safety/ toxicity testing in animals which yields thousands of tissue sections that currently must be assessed manually by a trained veterinary pathology. However, there is a looming crisis due to the lack pathologists.

The PATH-TOX consortium is led by Irish SME, Deciphex Ltd, and includes key partners such as Janssen Pharmaceuticals in Belgium and Pathology Data Systems Ltd a Swiss based SME. They are creating PATHOLYTIX-TOX a computer aided diagnostic system to streamline the pathology review process. Using state-of-the-art artificial intelligence (AI) image analysis tools it will automatically identify the normal and abnormal tissues upfront, allowing the pathologist to focus mainly on the abnormal cases, hence accelerate workflow.

To date, we have built a working prototype of the image analysis engine, which can identify abnormal tissue in liver. In this project we will optimise the engine further to improve performance and expand its use into other tissues. We will also develop other features such as the user interface, data management and cloud framework. Once developed, we will perform a comprehensive validation and benchmarking study to compare to manual pathology assessment.

There is a large, growing, global target market for PATHOLYTIX-TOX. Pharma and CROs worldwide routinely perform thousands of animal toxicology tests each year, who are potential customers. With regards to competitors, there is no direct competition. Competitors offer individual components of the pathological workflow, not fit-for-purpose solutions for the toxicology pathology market.

Overall, PATHOLYTIX would have a big impact on drug development, by reducing the time required for pathology review and associated costs. This should have a knock on effect for the global and EU markets, reducing time and cost for new drugs to get to market.

Coordination : Janssen Pharmaceutica NV

Funding Scheme : IA – Innovation action

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