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Articles by K He
Total Records ( 4 ) for K He
  K He , X Li , J Zhou , X. W Deng , H Zhao and J. Luo
 

Summary:NTAP is designed to analyze ChIP-chip data generated by the NimbleGen tiling array platform and to accomplish various pattern recognition tasks that are useful especially for epigenetic studies. The modular design of NTAP makes the data processing highly customizable. Users can either use NTAP to perform the full process of NimbleGen tiling array data analysis, or choose post-processing modules in NTAP to analyze pre-processed epigenetic data generated by other platforms. The output of NTAP can be saved in standard GFF format files and visualized in GBrowse.

  S. W Grimm , H. J Einolf , S. D Hall , K He , H. K Lim , K. H. J Ling , C Lu , A. A Nomeir , E Seibert , K. W Skordos , G. R Tonn , R Van Horn , R. W Wang , Y. N Wong , T. J Yang and R. S. Obach
 

Time-dependent inhibition (TDI) of cytochrome P450 (P450) enzymes caused by new molecular entities (NMEs) is of concern because such compounds can be responsible for clinically relevant drug-drug interactions (DDI). Although the biochemistry underlying mechanism-based inactivation (MBI) of P450 enzymes has been generally understood for several years, significant advances have been made only in the past few years regarding how in vitro time-dependent inhibition data can be used to understand and predict clinical DDI. In this article, a team of scientists from 16 pharmaceutical research organizations that are member companies of the Pharmaceutical Research and Manufacturers of America offer a discussion of the phenomenon of TDI with emphasis on the laboratory methods used in its measurement. Results of an anonymous survey regarding pharmaceutical industry practices and strategies around TDI are reported. Specific topics that still possess a high degree of uncertainty are raised, such as parameter estimates needed to make predictions of DDI magnitude from in vitro inactivation parameters. A description of follow-up mechanistic experiments that can be done to characterize TDI are described. A consensus recommendation regarding common practices to address TDI is included, the salient points of which include the use of a tiered approach wherein abbreviated assays are first used to determine whether NMEs demonstrate TDI or not, followed by more thorough inactivation studies for those that do to define the parameters needed for prediction of DDI.

  S. W Grimm , H. J Einolf , S. D Hall , K He , H. K Lim , K. H. J Ling , C Lu , A. A Nomeir , E Seibert , K. W Skordos , G. R Tonn , R Van Horn , R. W Wang , Y. N Wong , T. J Yang and R. S. Obach
 

Time-dependent inhibition (TDI) of cytochrome P450 (P450) enzymes caused by new molecular entities (NMEs) is of concern because such compounds can be responsible for clinically relevant drug-drug interactions (DDI). Although the biochemistry underlying mechanism-based inactivation (MBI) of P450 enzymes has been generally understood for several years, significant advances have been made only in the past few years regarding how in vitro time-dependent inhibition data can be used to understand and predict clinical DDI. In this article, a team of scientists from 16 pharmaceutical research organizations that are member companies of the Pharmaceutical Research and Manufacturers of America offer a discussion of the phenomenon of TDI with emphasis on the laboratory methods used in its measurement. Results of an anonymous survey regarding pharmaceutical industry practices and strategies around TDI are reported. Specific topics that still possess a high degree of uncertainty are raised, such as parameter estimates needed to make predictions of DDI magnitude from in vitro inactivation parameters. A description of follow-up mechanistic experiments that can be done to characterize TDI are described. A consensus recommendation regarding common practices to address TDI is included, the salient points of which include the use of a tiered approach wherein abbreviated assays are first used to determine whether NMEs demonstrate TDI or not, followed by more thorough inactivation studies for those that do to define the parameters needed for prediction of DDI.

 
 
 
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