Here we propose a novel approach to the prediction of pharmacokinetic properties, called pkCSM, which relies on graph-based signatures. These encode distance patterns between atoms and …

2015年4月10日 · We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. …

Here, we introduce Deep-PK, a deep learning-based PK and toxicity prediction, analysis and optimisation platform. We applied Graph Neural Networks and graph-based signatures as a …

Given an input molecule, two main sources of information are used to train and test machine learning-based predictors: compound general properties (including molecular properties, …

2015年5月14日 · We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. …

2015年4月22日 · 我们开发了一种新方法 (pkCSM)，它使用基于图形的签名来开发用于药物开发的中心 ADMET 特性的预测模型。 pkCSM 的性能与当前方法一样好或更好。 一个可免费访问的 …

pkCSM: predicting small-molecule pharmacokinetic properties using graph-based signatures Douglas E. V. Pires*, Tom L. Blundell and David B. Ascher

2015年4月21日 · Abstract: Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these …

2015年4月22日 · We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. …

2015年4月10日 · Prediction and Optimization of Pharmacokinetic and Toxicity Properties of the Ligand. The use of the comprehensive analysis system pkCSM is demonstrated to allow early …