Multimodal Transformers and Their Applications in Drug Target Discovery for Aging and Age-Related Diseases

Abstract Given the unprecedented rate of global aging, advancing aging research and drug discovery to support healthy and productive longevity is a pressing socioeconomic need. Holistic models of human and population aging that account for biomedical background, environmental context, and lifestyle...

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Veröffentlicht in:The journals of gerontology. Series A, Biological sciences and medical sciences Jg. 79; H. 9
Hauptverfasser: Steurer, Barbara, Vanhaelen, Quentin, Zhavoronkov, Alex
Format: Journal Article
Sprache:Englisch
Veröffentlicht: US Oxford University Press 01.09.2024
Schlagworte:
Aging - physiology
Artificial Intelligence
Drug Discovery - methods
Humans
Longevity - drug effects
Machine Learning
Neural Networks, Computer
Healthspan
Longevity
Artificial intelligence
Machine learning
ISSN:1079-5006, 1758-535X, 1758-535X
Online-Zugang:Volltext
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Zusammenfassung:Abstract Given the unprecedented rate of global aging, advancing aging research and drug discovery to support healthy and productive longevity is a pressing socioeconomic need. Holistic models of human and population aging that account for biomedical background, environmental context, and lifestyle choices are fundamental to address these needs, but integration of diverse data sources and large data sets into comprehensive models is challenging using traditional approaches. Recent advances in artificial intelligence and machine learning, and specifically multimodal transformer-based neural networks, have enabled the development of highly capable systems that can generalize across multiple data types. As such, multimodal transformers can generate systemic models of aging that can predict health status and disease risks, identify drivers, or breaks of physiological aging, and aid in target discovery against age-related disease. The unprecedented capacity of transformers to extract and integrate information from large and diverse data modalities, combined with the ever-increasing availability of biological and medical data, has the potential to revolutionize healthcare, promoting healthy longevity and mitigating the societal and economic impacts of global aging.
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ISSN:1079-5006
1758-535X
1758-535X
DOI:10.1093/gerona/glae006