About PathLAKE

PathLAKE will deliver high-impact exemplar projects reflecting today's demand for AI-driven diagnostics to increase efficiency in pathology reporting and improve patient outcomes through advanced diagnostics and selection of patients for personalised medicine.

The PathLAKE‘s consortium comprises some of the nation’s leading digital and computational innovators from NHS and academia. Through the digitisation of five major NHS laboratories and the formation of a computational pathology hub, it will drive AI innovation in pathology for the UK and create the world’s largest depository of annotated digital whole slide images. PathLAKE will ensure that the UK is in prime position to leverage the full value of NHS pathology data to drive economic growth in health related AI.

PathLAKE will play a leading role in the development, validation and implementation of AI in cellular pathology. It will be an invaluable resource for researchers and UK industry, enabling a step change in the understanding of disease and the provision of patient healthcare

What We Offer

Access to pathologists
Access to pathologists
Access to data scientists
Access to data scientists
Education & Training
Education & Training
Data lake access
Data lake access
Exemplar Projects
Breast
Cancer
Breast cancer exemplar project led by the Nottingham and Warwick groups aims to develop an innovative prognostic algorithm for early stage breast cancer patients. To achieve our objectives, we will use the power of image analysis and artificial intelligence (AI) to extract several features from the digitalised images to create a risk score for patients' stratification. The developed algorithm will provide a cost and time effective tool to predict the disease outcome and will aid in patients' management decisions.
Prostate
Cancer
Prostate cancer exemplar led by Professor Clare Verrill from Oxford has two objectives: 1. Improving workflow efficiency for reporting of prostate biopsies using AI delivering NHS efficiency gains and faster diagnoses. 2.Using AI to improve the recognition of which prostate cancers will behave in an aggressive fashion, leading to better selection of patients for radical treatment and new insights into cancer biology and prognosis.
Personalised
Medicine
Immunotherapy biomarker exemplar led by Professor Manuel Salto Tellez working with the Northern Ireland Biobank (NIB) will develop algorithms for improved identification of patients that will benefit from personalised medicine. Identification of these patients is key to delivering improved care for cancer patients.
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Automated
biopsy analysis
Automated reporting of tissue biopsies will be made possible by innovative algorithms developed by Professor David Snead and Professor Nasir Rajpoot. They aim to deliver the world’s first fully automated cellular pathology reporting tool allowing valuable pathologist time to be diverted to challenging cases where their expertise is most needed. This will provide high volume rapid analysis of large sections of the pathologist’s workload and help to deliver more rapid results to clinic improving patient management.