An ambitious academic, clinical and industry research programme supported by a €5 million funding grant from Science Foundation Ireland, which will be leveraged with an additional €5 million from industry partners, was launched today in Trinity College Dublin to provide new insights in our understanding of Motor Neuron Disease (MND), also known as Amyotrophic Lateral Sclerosis (ALS). The programme will result in advanced data-driven prediction models for progression of the disease in patients and next-generation data analysis that facilitates clinical insights and treatment.
Precision ALS, which is led by two SFI Research Centres - ADAPT and FutureNeuro - involves world class Irish-based researchers in clinical science, data science and artificial intelligence (AI). The researchers will work in partnership with TRICALS, an independent consortium of leading ALS experts, patients and patient advocacy groups across Europe. National and international industry partners and charities including patient organisations are also actively participating.
Speaking at the launch, Tánaiste and Minister for Enterprise, Trade and Employment, Leo Varadkar T.D. said: “This project straddles clinical research and industry, and will combine the best of our technologies, the best of our ideas, and the best of our medical expertise with to potential to change lives for the better. It will develop tools that facilitate clinical trials based on precision-medicine, and has the potential to produce benefits for other rare conditions and diseases, supporting job creation and reducing drug costs.”
Precision ALS will provide an innovative and interactive platform for all clinical research in ALS across Europe, that will then harness AI to analyse large amounts of data. As the largest international multimodal dataset aimed at precision medicine for this condition, Precision ALS will address the issues with gathering new data at scale in a timely and cost effective-manner across multiple international sites in order to present that data in real time to clinical scientists.
At the launch event, Dr Linda Doyle, Provost of Trinity College Dublin, said: “The Precision ALS programme builds on a dynamic culture of research innovation here in Trinity. It highlights the synergies that exist between advanced technology and clinical research and the potential they have to advance not just our understanding of disease but also the treatment of it. This collaboration will train a cohort of highly skilled, industry-ready researchers, and generate new jobs in clinical and data science research. It will strengthen Ireland’s position as a global leader in MND research and AI. I wish all involved the very best.”
Director of the Precision ALS research programme and Professor of Neurology at Trinity College Dublin, Professor Orla Hardiman said: “Despite significant advances in pre-clinical models that help us understand the biology of disease in animals, the success of clinical trials has been disappointing. ALS is a disease that only affects humans, and there is increasing recognition of the need for a Precision Medicine approach towards drug development. We know now that ALS is heterogeneous, meaning that it has different causes and different patterns of progression. Large numbers are required to understand these differences. Using “big data” analyses, Precision ALS will provide an in-depth understanding of the factors that drive heterogeneity, and in doing so will for the first time allow us to target new and innovative treatments to specific patient subgroups.
ALS/MND causes progressive decline in movement, cognition and behaviour. Although uniformly terminal, life expectancy can vary from three months to many years from first symptom, and there are no effective treatments. Irish researchers, along with their European collaborations in ALS/MND, have shown that the disease is caused by variable combinations of faulty genes that likely interact with lifestyle and environment. Using big data analysis, Precision ALS will provide the technology to improve our understanding of how these factors impact the development of the disease. This in turn will inform which treatments will work for each individual, instead of a one-size-fits-all approach.
From a computational and data-science perspective Professor Vinny Wade, Director of the SFI ADAPT Centre for AI-Driven Digital Content Technology said: “Precision ALS brings together a perfect mix of data and technology research skills to trailblaze discoveries in tackling these devastating diseases. Our experience in researching these datasets for immediate interrogation using AI will help identify contributing factors and increase our power to discover changes linked to disease. Unlocking this data in an ethical way is the key to achieving the research mission and realising true ‘precision medicine’. This pioneering work will lead to transformational change for patients with a ripple effect that will positively impact society.”
Professor of Neurology and Chair of TRICALS, Leonard van den Berg, said: “For the last 10 years TRICALS partners have worked closely together to generate a large amount of data relating to ALS. We are delighted to be the strategic partner with ADAPT and FutureNeuro. This programme has the ambition to break new boundaries to develop targeted therapies, and to provide the right drug for the right patient at the right time. This has the potential to have a hugely positive impact on the lives of those with ALS.”
Precision ALS is a unique programme that brings together Clinicians, Computer Scientists, Information Engineers, Technologists, and Data Scientists. The researchers will work together with leading pharmaceutical, data science, clinical research, medical device organisations and the HSE to generate a sustainable precision medicine-based approach towards new drug development that will have many benefits including better clinical outcomes for patients and reducing the economic cost of these diseases.
On completion, Precision ALS will be a first-in-kind modular transferable pan-European ICT framework for ALS that can be easily adapted to other diseases that face similar precision medicine-related challenges.