Niccolò Pancino (University of Siena)

When: May 18th, 2022 – 11:00 – 11:45 AM

Where: Google meet link

Description

DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations
Drug combination therapy has become an increasingly promising method in the treatment of cancer. However, the number of possible drug combinations is so huge that it is hard to screen synergistic drug combinations through wet-lab experiments. Therefore, computational screening has become an important way to prioritize drug combinations. Graph neural network has recently shown remarkable performance in the prediction of compound–protein interactions, but it has not been applied to the screening of drug combinations.
In this paper, a deep learning model based on graph neural network and attention mechanism is proposed, to identify drug combinations that can effectively inhibit the viability of specific cancer cells: DeepDDS (Deep Learning for Drug–Drug Synergy prediction). The model is then compared with classical machine learning methods and other deep learning-based methods, achieving better performance.