药品
药物反应
精密医学
医学
临床试验
抗药性
计算机科学
机器学习
药理学
内科学
生物
微生物学
病理
作者
P. Selvi Rajendran,M. Sivannarayna
标识
DOI:10.1109/icsmdi57622.2023.00078
摘要
Precision medicine is based on curing diseases based on a patient's genetic profile, lifestyle, and environmental factors. This method improves clinical trial success rates and speed up drug regulatory approval. Predicting tumour vulnerability to specific anti-cancer therapy is critical for the successful implementation of precision medicine. Drug combinations have been shown to be very effective in cancer treatment to lower the drug resistance and improve the therapeutic effectiveness. The experiments carried out in all these therapeutic combinations have become expensive and time-consuming as a result of the increasing number of anti-cancer drugs. Large-scale drug response testing on cancer cell lines might help to understand the way drugs react with cancer cells. This study proposes a multi head graph attention network to perform drug response prediction.
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