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Drug Discovery and Drug Identification using AI

机译:使用AI进行药物发现和药物鉴定

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The paper deals with identifying and creating new drugs using AI technique. We are implementing a process using Intel Open VINO toolkit for identification of drugs. With this detection technique we can identify the reactants which are added as drugs and automates the entire flow. We are using Intel OpenVINOtoolkit with custom object detection technique to train the model using the faster Region Based Convolutional Neural Network (R-CNN)method with labeled drugs (organic compounds) which act as Reactants. Using this approach, the entire drug discovery process of clinical trial for the process can be reduced to very small time of 3-4 months (which generally takes 10-12 years) and we can generate simulated drugs to see the behavior and implementation becomes faster. We are also creating a customized dataset of drugs or molecules which are used for identifying the drugs. We are using the Canonical SMILES for the molecules so we will map SMILES with organic compounds being detected.
机译:本文涉及使用AI技术识别和创建新药。我们正在使用Intel Open VINO工具包实施一种用于识别药物的过程。通过这种检测技术,我们可以识别作为药物添加的反应物,并使整个流程自动化。我们正在将Intel OpenVINOtoolkit与自定义对象检测技术结合使用,以更快的基于区域的卷积神经网络(R-CNN)方法与作为反应物的标记药物(有机化合物)一起训练模型。使用这种方法,整个临床试验的药物发现过程可以减少到3-4个月的极短时间(通常需要10-12年),并且我们可以生成模拟药物以观察其行为和实施变得更快。我们还将创建用于识别药物的药物或分子的定制数据集。我们对分子使用规范的SMILES,因此我们将绘制SMILES与检测到的有机化合物的图。

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