Capgemini UK and Huntington’s Disease Association unlock improved understanding of Huntington’s disease progression

At Capgemini, we look to apply technology to help solve societal challenges. This includes using modelling techniques to unlock valuable new insights from complex data sets that can, for example, improve understanding of how medical conditions progress.

Our UK Head of Digital Inclusion, Sally Caughey, spoke with Dave Dungate, Head of Solution Innovation, about how the team at Capgemini Engineering is working to improve understanding of Huntington’s disease, in collaboration with the charity Huntington’s Disease Association.

Why was the project needed?

Huntington’s disease is a neurodegenerative genetic disorder characterised by involuntary movements, cognitive decline and behavioural changes that evolve over time. Around 10,000 people across the UK are affected by the disease, typically experiencing significant decline in functional capacity when they are between 30 and 50 years old. Sufferers are likely to have full-time jobs and families to support. This means that one of the ways a diagnosis impacts their close family members is financially – as families may need to reduce working hours and other commitments to care for loved ones.

Currently, Huntington’s disease is an incurable, terminal illness and efforts are underway to research treatments. Once a therapy is identified, it must be approved by the National Institute for Health and Care Excellence (NICE) for the treatment to be provided by the UK’s National Health Service (NHS). When making this decision, NICE consider the effectiveness of the treatment as well as supporting independent economic evaluations that weigh the costs against benefits to the individual and society.

A supporting economic evaluation did not exist for Huntington’s disease. Nor did a model that maps the different stages of cognitive and motor decline experienced by individuals. To date, doctors rely on a different way of measuring disease progression, called Shoulson-Fahn stages. To assign individuals to a ‘stage’, information is analysed about their ability to perform certain activities at a snapshot in time.

As this method does not consider an individual’s wider medical history and can be affected by other factors in the patient’s life, it means that they can technically show improvement in symptoms if they perform an activity better at a later date. However, this improvement would be unrelated to the underlying Huntington’s disease, which is currently untreatable. Having a model that outlines the different stages of cognitive and motor decline could assist with better insight into a patient’s disease progression, as well as help charities communicate to potential funders of therapies the positive impact potential interventions could have.

What did you do?

Huntington’s Disease Association (HDA), a charity that supports people in England and Wales affected by Huntington’s disease, was eager to start solving these knowledge gaps and, in 2020, began collaborating with my team. We were able to offer expertise in modelling to help HDA gain greater insight, leveraging an available database containing histories of around 15,000 patients with Huntington’s disease.

At the start of the project, we discussed the charity’s needs. Exploration of the available data and literature helped us identify how best to use data modelling techniques to advance understanding of the disease as well as to support funding cases for potential treatments.

Equipped with this insight, we started developing the model, working closely with HDA’s world-leading experts to ensure accurate understanding and interpretation of the anonymised medical data. Combining HDA’s clinical and medical knowledge with Capgemini’s data insight capabilities has now resulted in a model that delivers against the charities’ objectives. Throughout 2022, my team have been training and refining the model, which is now complete as of October.

What are the results?

The new model now allows HDA to chart the impact of Huntington’s disease on patients’ socio-economic status and quality of life – making it possible to show how investments in therapies that slow the progression of the disease have wider benefits for individuals, their families and communities. A few examples of socio-economic factors mapped by the model are the impact on partners, loss of earnings and related contribution to GDP, state benefits, and nursing care and treatment costs.

Moreover, the new insights revealed by the model have been deemed as advancing scientific understanding of how cognitive, motor and functional decline progresses due to the disease by experts at HDA. We are currently collaborating on ways to share these findings with the wider medical community.

It has been brilliant joining forces with the experts at HDA. We’ve developed a highly collaborative way of working and the project has been fascinating for everyone involved – from a technical perspective as well as because of the meaningful, wider implications of the work. It’s been a privilege to work on the research.