First-of-a-kind AI project detects early-stage lung cancer

By Jo Makosinski | Published: 20-Dec-2022

Clinithink and AstraZeneca partnership pinpoints potential cancer from clinical notes

Clinithink has partnered with AstraZeneca Oncology UK to find patients with lung cancer at an early stage where treatment can be more effective.  

The project, announced this week, hopes to demonstrate potential savings based on this novel AI approach, as well as identify benefits for patients in being treated earlier in the disease process, hopefully increasing the number of people who are cured. 

And it aims to flag patients who could benefit from lung disease screening, leading to earlier diagnosis of the disease – and potentially improving patient outcomes and reducing costs for the NHS.

The cost of lung cancer to the UK economy is significant, and there are higher costs associated with treating patients at a later stage.

Early detection

Lung cancer is the UK’s second-most-common cancer, and each year almost 35,000 people die from the disease.

But survival rates at one year drop drastically from 90% if the disease is diagnosed at the earliest stage, to just 20% if the disease is diagnosed at the most-advanced stage.

Using AI-based technology, the first stage of the project is a retrospective analysis of patients’ unstructured electronic medical records that will test whether it is possible and cost-effective to use the AI technology – machine learning (ML) and natural language processing (NLP) – to identify both symptomatic and asymptomatic patients who are in early stages of the disease.

Focusing specifically on early detection of lung cancer, our partnership with Clinithink is a great example of an external partnership with the common goal of improving UK cancer outcomes

The outputs will then be used to develop predictive models that flag high-risk individuals at a much-earlier, more-treatable stage of disease, improving survival rates and driving down the intensity of treatment needed. 

The partnership coincides with the announcement from The UK National Screening Committee, which in September recommended that the UK should implement a national lung cancer screening programme.

A collaborative approach

The collaboration, which is being funded by AstraZeneca, will support the goals of this programme by helping to identify those patients under the age of 55 who would otherwise have been ineligible for the nationwide screening.  

Dr Satoshi Hori, oncology medical affairs head at AstraZeneca Oncology UK, said: “Addressing healthcare ecosystem challenges to enable earlier detection and diagnosis of cancer is one of our UK oncology missions.

“Focusing specifically on early detection of lung cancer, our partnership with Clinithink is a great example of an external partnership with the common goal of improving UK cancer outcomes.” 

Harnessing and understanding unstructured medical data creates enormous opportunities to transform the treatment of disease, reduce NHS costs, and improve population health

“The project will test whether it is possible to predict which individuals might have lung cancer, while they are still at the early stages of the disease process.” 

Harnessing data

Chris Tackaberry, co-founder and chief executive of Clinithink, added: “Harnessing and understanding unstructured medical data creates enormous opportunities to transform the treatment of disease, reduce NHS costs, and improve population health.  

“Our technology, CLiX unlock, can process millions of detailed medical records in hours – a process which would take years if completed manually – to deliver valuable clinical insights.  

“We hope to use the insights uncovered in this real-world evidence study to develop predictive models that will flag high-risk individuals at a much-earlier, more-treatable stage of disease – when neither they nor their GP know they have lung cancer, or even suspect it.” 

The first phase of the project will include a health economic evaluation to ensure the pilot is cost effective and scalable. If successful, the team will develop a prospective model in mid-2023 to prove the validity of the approach in the real world.  

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