Title: ImageDx CRC & ImageDx Lung: A centralized, AI-based solution for tissue-based delivery of personalized medicine testing for the NHS.
Funder: Department of Health and Social Care

Abstract: Background The 43,000 NHS colorectal cancer (CRC) patients diagnosed yearly require microsatellite instability or mismatch repair testing (MSI/MMR), at a cost of between £4,085,000 and £8,385,000. Approximately 36,000 patients with non-small cell carcinoma (NSCLC) require PD-L1 testing, costing £7M. MSI results take an average of 14 days and PD-L1 delivery is difficult, being based on a pathologist’s subjective interpretation. There are geographical gaps across the UK in the delivery of these necessary tests. Aims Our proposal is based on two key pillars: 1. Bringing Artificial Intelligence to routine diagnostics, applied to: a) the basic H&E section, in MSI/MMR, replacing the current PCR/IHC approaches b) objective scoring of PD-L1 IHC. 2. Creating a centralized platform: a) for submission of in-silico images and b) delivery of such algorithms across the NHS. Work Plan We propose work packages to: a) develop and validate the AI algorithms (ImageDx Lung/Colon) on retrospective and prospective datasets. b) create a delivery platform (Sonrai/PMC Central Hub, SPCH) under ISO13485. c) achieve clinical validation and regulatory approval. This novel modality applying AI to diagnostics requires clear explanation to patients, and patient input will be decisive to delivery; a detailed PPI plan is put forward to capture this important contribution. Dissemination and Anticipated Outcomes Dissemination will happen in three phases: a) Northern Ireland. b) PathLAKE membership. c) NHS wide. Our approach will create direct annual savings across the NHS to the tune of £648,500 – £3,228,500. Indirect savings associated with anti-PDL1 therapy based on more accurate testing could impact 10% of the patients and on £35M of the budget on therapeutics. Following the NHS drive towards testing centralization, the SPCH will receive online scanned images and render results in 24-48 hours. This model of AI, tissue-based molecular diagnostic delivery will enable adoption of future AI- based testing in the NHS.

Lay abstract: Background Tests carried out by pathologists on cancer biopsy tissue help determine the best treatment options for patients. Annually in the UK there are: - 43,000 patients with colorectal cancer who require either a Microsatellite instability (MSI) or Mismatch repair (MMR) test to measure the ability of a cell to repair mistakes in DNA replication. - 36,000 with non-small cell lung cancer who require a PD-L1 test to measure the amount of PD-L1 on cancer cells. PD-L1 is a protein that helps keep immune cells from attacking non-harmful cells in the body. Normally, the immune system fights foreign substances like viruses and bacteria, and not your own healthy cells. Some cancer cells have high amounts of PD-L1. Rapid and accurate testing is critical, but: - Test results can be slow - MSI takes 14 days on average. - PD-L1 testing is difficult and inaccuracies may occur. - Tests are expensive and cost &pound;11.1m - &pound;15.5m per year to the NHS. - Not all areas can deliver tests. Aims To introduce Artificial Intelligence (AI) tools into testing to: - Accelerate testing. - Increase accuracy. - Reduce costs. - Enable testing across the NHS via a secure, centralised digital platform, in the cloud - Open the way to NHS adoption of this technique for colorectal, lung and other cancers. Work Plan We have already developed two prototype AI tools and plan to: - Increase their accuracy by training them on datasets. - Create a testing platform where users can upload biopsy images and use our tools - Obtain clinical validation and regulatory approval and promote NHS adoption. Patient and Public Involvement (PPI) We are aware the public may have concerns about the introduction of AI into cancer diagnostics, so patients will help develop information to enhance public understanding of the benefits of AI in this setting. We will ensure the diversity of PPI input (in line with INCLUDE guidance) by considering all underserved groups. An AI Lay Group, featuring members from a range of backgrounds, will provide feedback to the research team, facilitate publicity and organise a public event to showcase AI research. Dissemination Results will be shared, on a phased basis, with: - Health and Social Care in Northern Ireland. - UK NHS testing labs. - Scientific and academic communities. - Patients and the public through PPI - NHS-wide adoption. Outcomes - Faster and more accurate testing (results 24-48 hours). - Annual savings for the NHS of &pound;648k - &pound;3.2m. Indirect savings associated with more accurate PD-L1 testing would impact 10% of patients and on &pound;35m of the therapeutics budget. - A proven model of AI-based testing for adoption across the NHS.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: CANCER AND NEOPLASMS