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Project background

In the DoMore! project, we will explore our unique combination of academic and industrial competence to radically improve prognostication and hence treatment of cancer by using digital tools for pathology.

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3D Tumour Heterogeneity

These interactive graphics demonstrate extensive and minimal 3D reconstruction of prostate cancer. The models were created with digitised H&E stained tissue sections and configured into spatial context...

Launch 3D graphics
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Utilize Big Data

The Big Data produced in the DoMore! project will be the basis needed for us to identify and establish robust generic biomarkers for cancer prognosis and prediction.

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In silico pathology

In silico pathology will be the focus for all work packages in this project. Our goal is for these methods to be of such great value to the health service that their benefits will far outweigh the investments required in digital pathology.

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Project workflows

The data that will be used in the DoMore! project has been accumulated over the last decade, at the four medical partners institutions (UCL, OUH, SiV and Oxford).

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Clinical Decision Support Tool

There is research published on new prognostic markers on a monthly basis, but few are ever taken into clinical practice, as it is difficult for clinicians to know how to use several prognostic markers together. The DoMore! project will develop a support tool for prognostication in prostate-, colorectal- and lung cancer.

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Results

We expect a number of different project results; increased efficiency in pathology, methods and markers to aid the clinician to give better and more personalized treatment to cancer patients, patents and publications, products (algorithms, applications, services, data) and spin-off companies.

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Societal impact

By addressing the diagnostic and prognostic challenges posed by heterogeneity in cancer, and inter- and intra-observer variance in the field of pathology, we may improve prognostication and thereby patient treatment.

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