Diagnosing Disease with Shopping Data

The aim:

To create a framework for "Personal Data Donation" by investigating the issues surrounding individuals "donating" personal transactional data to public health research projects.

The question:

How can personal transactional data be collected and analysed for the purposes of health research in a way that is acceptable to society, works for infectious and chronic disease, and can be successfully implemented in a clinical setting?

Overview:

This PhD is connected to a wider project by partners ALSPAC at Bristol University(2020) and the Alan Turing Institute(2020): "donating personal transactional data for research: investigating the public acceptability of using commercial transactional data in public health research".

Personal commercial transactional data is the information stored when an exchange occurs between an individual and a business, including customer shopping data. This research will connect loyalty card data (customer shopping information held by a retailer), to Covid-19 incidents and to information from women with ovarian cancer. Connecting these datasets will be used to investigate whether shopping data can be used to get women with ovarian cancer diagnosed earlier, and/or if it can help in informing public health decisions in a pandemic.

A collection of studies will be done to iteratively create machine learning (ML) models (a method of programming computers to learn from data) whose predictions could help in the earlier diagnosis of ovarian cancer and/or the understanding of ILI (Influenza Like Illnesses) outbreaks.

The methodology to be used is mixed methods collecting and analysing both qualitative data, and quantitative data for integrated interpretation. The studies will be used to inform the models schema creation, feature engineering, to understand, and validate its outputs and any interpretations made from these. The iterative design will allow for adjustments to the model for successful implementation in a clinical setting.

The survival rate for ovarian cancer is low, with no UK national screening programme women are predominantly diagnosed in the late stages (Cancer Research UK 2020), and the world is currently experiencing a pandemic of Covid-19 (WHO 2020). Creating a framework tool, using this research, will help medical researchers assess, and access, the potential of using shopping data to investigate disease.

We will collaborate with over 40 partners drawn from across FMCG and Food; Creative Industries; Health and Wellbeing; Smart Mobility; Finance; Enabling technologies; and Policy, Law and Society. These will benefit from engagement with our CDT through the following established mechanisms:

- Training multi-disciplinary leaders. Our partners will benefit from being able to recruit highly skilled individuals who are able to work across technologies, methods and sectors and in multi-disciplinary teams. We will deliver at least 65 skilled PhD graduates into the Digital Economy.

- Internships. Each Horizon student undertakes at least one industry internship or exchange at an external partner. These internships have a benefit to the student in developing their appreciation of the relevance of their PhD to the external societal and industrial context, and have a benefit to the external partner through engagement with our students and their multidisciplinary skill sets combined with an ability to help innovate new ideas and approaches with minimal long-term risk. Internships are a compulsory part of our programme, taking place in the summer of the first year. We will deliver at least 65 internships with partners.

- Industry-led challenge projects. Each student participates in an industry-led group project in their second year. Our partners benefit from being able to commission focused research projects to help them answer a challenge that they could not normally fund from their core resources. We will deliver at least 15 such projects (3 a year) throughout the lifetime of the CDT.

- Industry-relevant PhD projects. Each student delivers a PhD thesis project in collaboration with at least one external partner who benefits from being able to engage in longer-term and deeper research that they would not normally be able to undertake, especially for those who do not have their own dedicated R&D labs. We will deliver at least 65 such PhDs over the lifetime of this CDT renewal.

- Public engagement. All students receive training in public engagement and learn to communicate their findings through press releases, media coverage.

This proposal introduces two new impact channels in order to further the impact of our students' work and help widen our network of partners.

- The Horizon Impact Fund. Final year students can apply for support to undertake short impact projects. This benefits industry partners, public and third sector partners, academic partners and the wider public benefit from targeted activities that deepen the impact of individual students' PhD work. This will support activities such as developing plans for spin-outs and commercialization; establishing an IP position; preparing and documenting open-source software or datasets; and developing tourable public experiences.

- ORBIT as an impact partner for RRI. Students will embed findings and methods for Responsible Research Innovation into the national training programme that is delivered by ORBIT, the Observatory for Responsible Research and Innovation in ICT (www.orbit-rri.org). Through our direct partnership with ORBIT all Horizon CDT students will be encouraged to write up their experience of RRI as contributions to ORBIT so as to ensure that their PhD research will not only gain visibility but also inform future RRI training and education. PhD projects that are predominantly in the area of RRI are expected to contribute to new training modules, online tools or other ORBIT services.