Cha Y, Kagalwala MN, Ross J. Navigating the Frontiers of Machine Learning in Neurodegenerative Disease Therapeutics.
Pharmaceuticals (Basel) 2024;
17:158. [PMID:
38399373 PMCID:
PMC10891920 DOI:
10.3390/ph17020158]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 01/16/2024] [Accepted: 01/23/2024] [Indexed: 02/25/2024] Open
Abstract
Recent advances in machine learning hold tremendous potential for enhancing the way we develop new medicines. Over the years, machine learning has been adopted in nearly all facets of drug discovery, including patient stratification, lead discovery, biomarker development, and clinical trial design. In this review, we will discuss the latest developments linking machine learning and CNS drug discovery. While machine learning has aided our understanding of chronic diseases like Alzheimer's disease and Parkinson's disease, only modest effective therapies currently exist. We highlight promising new efforts led by academia and emerging biotech companies to leverage machine learning for exploring new therapies. These approaches aim to not only accelerate drug development but to improve the detection and treatment of neurodegenerative diseases.
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