PDGrapher AI tool aims to speed up precision medicine development
AI model PDGrapher maps disease drivers in cells, potentially revolutionising cancer and Alzheimer’s treatment strategies.
Harvard Medical School researchers have developed an AI tool that could transform drug discovery by identifying multiple drivers of disease and suggesting treatments to restore cells to a healthy state.
The model, called PDGrapher, utilises graph neural networks to map the relationships between genes, proteins, and cellular pathways, thereby predicting the most effective targets for reversing disease. Unlike traditional approaches that focus on a single protein, it considers multiple factors at once.
Trained on datasets of diseased cells before and after treatment, PDGrapher correctly predicted known drug targets and identified new candidates supported by emerging research. The model ranked potential targets up to 35% higher and worked 25 times faster than comparable tools.
Researchers are now applying PDGrapher to complex diseases such as Parkinson’s, Alzheimer’s, and various cancers, where single-target therapies often fail. By identifying combinations of targets, the tool can help overcome drug resistance and expedite treatment design.
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