Title: MyDiabetes IQ; safety and efficacy testing of a diagnosis and precision medicine tool for diabetes management.
Funder: Department of Health and Social Care

Abstract: Background Diabetes affects ~10% of the world’s population and rising, with treatment costs ~15% of NHS budget; mainly spent treating preventable complications. Precision medicine approaches through clinician-focused computer decision-support could transform care. MyDiabetesIQ (MDIQ) is a Technology-Readiness-Level (TRL) 6, minimum-viable-product predictive analytics-linked clinician interface tool containing ~70 machine learning models developed by MyWay Digital Health (MWDH) Ltd. MDIQ predicts: i) glycaemic/ metabolic response to type 2 diabetes pharmacological treatments, ii) diagnosis of rare diabetes subtypes, and iii) risk of acute/ chronic diabetes complications. Aims/ Objectives This MWDH project, supported by academic, NHS and PPI experts, aligns with the AI code of conduct/NICE evidence requirements, and aims to: - Evaluate usability/engagement and safety of MDIQ (online questionnaires, qualitative interviews, system logs, navigation data) - Assess impact of MDIQ on clinical workflow (prescribing/diagnostic data) - Measure clinical outcomes (including HbA1C) to inform next-step clinical trials - Set up a quality management system (QMS), ISO 13485 - Submit MDIQ class 2 CE Marking/ UKCA application - Incorporate patient/public feedback - Exploit/disseminate commercial/research outputs Plan Workpackages (July 2021-July 2023) cover set-up, testing, regulation, PPI involvement, IP and commercialisation. Testing will firstly use simulated data/clinic scenarios enabling clinician feedback (until data saturation) on MDIQ usability/accuracy of outputs (M2-5). If MDIQ is deemed safe, stage 2 testing will proceed in 5 NHS Manchester sites (M11-18); MDIQ predictive outputs will be checked by clinical validators in advance of clinician MDIQ use during patient consultations/referral reviews. Research outputs will support regulatory requirements. Impact/Dissemination This project aims to deliver safer, more effective/efficient diabetes care through an innovative market-ready management tool (MDIQ), and significant new know-how, exploited through commercialisation, publications, conferences, social media/partnership networks. This project supports zero-carbon (reduced in-person care attendances) and reduces inequalities through more personalised treatments and AI-driven risk-focused triage supporting deprived and ethnic minority groups.

Lay abstract: Background: Diabetes affects about 10% of the world and numbers are increasing. As well as affecting quality of life, treating diabetes costs around 15% of the NHS budget; mainly treating diabetes complications like heart attacks and foot ulcers. Better diabetes management would prevent most complications. 75% of people with diabetes are cared for by their GP and practice nurse who want to provide the best possible treatments and advice, but may have limited specialist diabetes knowledge. MyDiabetesIQ (MDIQ) is an online tool accessed through a website that supports clinicians. It uses artificial intelligence, also called AI or computer-based decision making. MDIQ collects information from many sources including GP/hospital records and patients, such as blood glucose readings or symptoms. MDIQ analyses this information to give clinicians specific advice on the best diagnosis, the best medications and the best way to avoid future complications. What is this research hoping to achieve? Researchers want to find out if clinicians like using MDIQ, find it useful and whether it is safe and leads to better decisions. In particular, whether MDIQ can: 1. Predict an individual s response to a particular drug, so the most appropriate drug can be prescribed. 2. Predict whether a person has a more unusual or different cause for their diabetes which might require different treatment. 3. Predict which complications (like heart attacks or foot ulcers) someone with diabetes may get - early treatment can prevent them happening. What will the research look like? MDIQ will be tested by researchers at the Universities of Dundee/Manchester. NHS clinicians (diabetes specialists) will give feedback on the advice given by MDIQ using dummy data , then using data from real people with diabetes attending clinics in 4 GP practices in Manchester. They will check that decisions made by MDIQ are sensible and safe, before advice is released to the GP practice for use. GP practices will feedback on any concerns, and how user-friendly the system is. This testing will support requirements set by the National institute for Clinical Excellence and the Medical Health Regulatory Authorities. How will people with diabetes and the public be involved in this research? Patients and the public have supported development of MDIQ through national public privacy panel review (data access), through workshops (gathering people s needs and views on AI systems), and have supported testing of early versions of the website. Researchers will continue to involve public, including people with diabetes in workshops/on the project steering group. How will people find out the results of this research? Researchers will publish/disseminate findings in peer-reviewed publications and through professional networks such as diabetes conferences, technology forums, public facing networks (e.g. Diabetes UK/ research for the future ), the MWDH company website and wider social media.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: METABOLIC AND ENDOCRINE