McFarlane, R., Galvin, M., Heverin, M. et al. (19 more authors) (2023) PRECISION ALS—an integrated pan European patient data platform for ALS. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 24 (5-6). pp. 389-393. ISSN 2167-8421
Abstract
Amyotrophic Lateral Sclerosis (ALS) is an incurable neurodegenerative condition. Despite significant advances in pre-clinical models that enhance understanding of disease pathobiology, translation of candidate drugs to effective human therapies has been disappointing. There is increasing recognition of the need for a precision medicine approach toward drug development, as many failures in translation can be attributed in part to disease heterogeneity in humans. PRECISION-ALS is an academic industry collaboration between clinicians, Computer Scientists, Information engineers, technologists, data scientists and industry partners that will address the key clinical, computational, data science and technology associated research questions to generate a sustainable precision medicine based approach toward new drug development. Using extant and prospectively collected population based clinical data across nine European sites, PRECISION-ALS provides a General Data Protection Regulation (GDPR) compliant framework that seamlessly collects, processes and analyses research-quality multimodal and multi-sourced clinical, patient and caregiver journey, digitally acquired data through remote monitoring, imaging, neuro-electric-signaling, genomic and biomarker datasets using machine learning and artificial intelligence. PRECISION-ALS represents a first-in-kind modular transferable pan-European ICT framework for ALS that can be easily adapted to other regions that face similar precision medicine related challenges in multimodal data collection and analysis.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
Keywords: | Precision medicine; amyotrophic lateral sclerosis; data science; scientific collaboration; Humans; Amyotrophic Lateral Sclerosis; Artificial Intelligence; Biomarkers; Machine Learning |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 30 Nov 2023 15:47 |
Last Modified: | 30 Nov 2023 15:47 |
Status: | Published |
Publisher: | Informa UK Limited |
Refereed: | Yes |
Identification Number: | 10.1080/21678421.2023.2215838 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:205769 |
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