| Literature DB >> 31326236 |
Manish D Paranjpe1, Alice Taubes2, Marina Sirota3.
Abstract
Computational drug repurposing has the ability to remarkably reduce drug development time and cost in an era where these factors are prohibitively high. Several examples of successful repurposed drugs exist in fields such as oncology, diabetes, leprosy, inflammatory bowel disease, among others, however computational drug repurposing in neurodegenerative disease has presented several unique challenges stemming from the lack of validation methods and difficulty in studying heterogenous diseases of aging. Here, we examine existing approaches to computational drug repurposing, including molecular, clinical, and biophysical methods, and propose data sources and methods to advance computational drug repurposing in neurodegenerative disease using Alzheimer's disease as an example.Entities:
Keywords: Alzheimer’s disease; EHR; EMR; artificial intelligence; machine learning; transcriptomic analysis
Mesh:
Year: 2019 PMID: 31326236 PMCID: PMC6771436 DOI: 10.1016/j.tips.2019.06.003
Source DB: PubMed Journal: Trends Pharmacol Sci ISSN: 0165-6147 Impact factor: 14.819