Literature DB >> 24965785

How far should we go? Perspective of drug-drug interaction studies in drug development.

Hiroyuki Kusuhara1.   

Abstract

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Year:  2014        PMID： 24965785     DOI： 10.2133/dmpk.dmpk-14-pf-903

Source DB:  PubMed          Journal:  Drug Metab Pharmacokinet        ISSN： 1347-4367            Impact factor:   3.614


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  5 in total

1.  BioChemDDI: Predicting Drug-Drug Interactions by Fusing Biochemical and Structural Information through a Self-Attention Mechanism.

Authors:  Zhong-Hao Ren; Chang-Qing Yu; Li-Ping Li; Zhu-Hong You; Jie Pan; Yong-Jian Guan; Lu-Xiang Guo
Journal:  Biology (Basel)       Date:  2022-05-16

2.  Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data.

Authors:  Wen Zhang; Yanlin Chen; Feng Liu; Fei Luo; Gang Tian; Xiaohong Li
Journal:  BMC Bioinformatics       Date:  2017-01-05       Impact factor: 3.169

3.  CNN-DDI: a learning-based method for predicting drug-drug interactions using convolution neural networks.

Authors:  Chengcheng Zhang; Yao Lu; Tianyi Zang
Journal:  BMC Bioinformatics       Date:  2022-03-07       Impact factor: 3.169

4.  Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining.

Authors:  Khader Shameer; M Mercedes Perez-Rodriguez; Roy Bachar; Li Li; Amy Johnson; Kipp W Johnson; Benjamin S Glicksberg; Milo R Smith; Ben Readhead; Joseph Scarpa; Jebakumar Jebakaran; Patricia Kovatch; Sabina Lim; Wayne Goodman; David L Reich; Andrew Kasarskis; Nicholas P Tatonetti; Joel T Dudley
Journal:  BMC Med Inform Decis Mak       Date:  2018-09-14       Impact factor: 2.796

5.  Drug-Drug Interaction Predicting by Neural Network Using Integrated Similarity.

Authors:  Narjes Rohani; Changiz Eslahchi
Journal:  Sci Rep       Date:  2019-09-20       Impact factor: 4.379
  5 in total

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