Artificial Intelligence and Multi-Omics Integration for Parkinson’s Disease Drug Development

Abstract

Recent advances underscore the potential of integrating multiomics, such as genomics, transcriptomics, proteomics, and metabolomics, and artificial intelligence to overcome limitations regarding early diagnosis and treatment of Parkinson's disease. Developing a comprehensive view of the complex molecular landscape of Parkinson's disease through artificial intelligence algorithms would enable the processing of extensive multiomics datasets. Applying these integrative technologies to Parkinson's disease research would improve early diagnosis, support personalized therapeutic strategies, and drug discovery. This review explores the transformative potential of integrating multiomics and artificial intelligence in Parkinson's disease, outlining a framework to advance diagnosis, treatment, and drug development in neurodegenerative diseases.