Researchers at the Oxford Drug Discovery Institute are leveraging artificial intelligence-powered databases to accelerate the search for Alzheimer’s treatments. By utilizing AI and knowledge graphs, scientists can analyze vast amounts of biomedical data nearly ten times faster than traditional methods, allowing them to prioritize genes and proteins that could lead to new drug discoveries.
The team, led by Chief Scientific Officer Emma Mead, has identified 54 immune-related genes from a genome-wide association study as potential targets for further research. Selecting effective targets for Alzheimer’s is challenging due to the many genetic and environmental factors influencing the disease. To streamline the process, the researchers turned to knowledge graphs, a database technology initially popularized by Google, which maps relationships between different data points. These tools help scientists quickly understand the properties of genes and proteins by pulling information from sources such as PubMed, scientific journals, and internal datasets.
Knowledge graphs are increasingly used in various industries, from digital retail to AI development, by connecting large amounts of information in a structured format. Companies like Graphwise specialize in building these databases, which can be integrated with AI models to enhance data analysis. In healthcare, this technology helps researchers trace specific genetic information back to original sources, ensuring accuracy and efficiency in identifying promising drug targets.
By working with Graphwise, Oxford researchers significantly reduced the time needed to analyze 54 genes from weeks to just days. This improvement allows them to focus on experimental validation, determining whether selected targets influence brain cells and whether they can be developed into viable treatments.
The rapid growth of biomedical data has made AI-powered tools essential for modern research. According to Mead, without these technologies, scientists risk being overwhelmed by the vast amount of information available. AI and knowledge graphs are proving to be valuable assets in advancing Alzheimer’s research, offering hope for faster drug development and improved treatments in the future.
