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Abstract ▼ AI-Helper

Identifying the toxicity of a compound or candidate drug in the course of drug development is an essential step. However, it is costly to experimentally verify that all candidate drugs are toxic. In recent years, computer simulation has been used to first determine the toxicity of candidate drugs, a...

Identifying the toxicity of a compound or candidate drug in the course of drug development is an essential step. However, it is costly to experimentally verify that all candidate drugs are toxic. In recent years, computer simulation has been used to first determine the toxicity of candidate drugs, and then to experiment with others to lower costs. However, there are cases where different simulation results show different toxicity prediction results. In this paper, we propose a method for predicting drug toxicity more reliably in candidate drug selection for new drug development. The proposed method performs learning about whether toxicity is based on the information given in the model based on the known physical / chemical structure, and predicts the toxicity of the candidate drug using the learned result.

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