Repurposing medications for treatment of age-related macular degeneration: Insights from novel approaches to data mining.
John MoirSarthak AggarwalDimitra SkondraPublished in: Experimental biology and medicine (Maywood, N.J.) (2023)
The economic and visual burdens associated with age-related macular degeneration (AMD) are expected to significantly increase in the coming years. As of now, interventions to delay or prevent AMD are limited. Hence, there is an urgent and unmet need to expand our therapeutic tools for AMD in a manner, that is, both efficient and cost-effective. In this review, we consider the idea of drug repurposing, in which existing medications with other indications can be re-imagined for treating AMD. We detail the results of several population-level studies that have shown associations between several candidates and decreased risk of AMD development or progression. Such candidates include the more extensively studied metformin and statins, in addition to recently identified candidates fluoxetine and l- DOPA (levodopa) that show promise. We then briefly explore results from an advanced bioinformatics study, which provides further evidence that existing medications are associated with AMD risk genes. Many of these candidates warrant further study in prospective, clinical trials, where their potential causal relationships with AMD can be thoroughly assessed.
Keyphrases
- age related macular degeneration
- clinical trial
- cardiovascular disease
- randomized controlled trial
- big data
- physical activity
- emergency department
- parkinson disease
- gene expression
- type diabetes
- machine learning
- risk assessment
- study protocol
- transcription factor
- electronic health record
- artificial intelligence
- phase iii
- data analysis