Final ProgramCPSA 2011
Science and Technology Coming Together to Make a Difference
October 3 - 6, 2011
Bucks County Sheraton Hotel
Langhorne, PA
Poster Abstract #22
Using UPLC-QuanTOF technologies and chemically intelligent software tools for confident metabolite identification and biotransformation localization in discovery and development
1) Waters Corporation, Milford, Massachusetts, USA; 2) Waters Corporation, Manchester, United Kingdom
Increasingly rich datasets collected by HRMS instrumentation are rapidly becoming standard methodology in the drug development arena. Generating meaningful qualitative and quantitative information from the raw data is a complex process. Understanding, curating and reporting this information for use both within a drug metabolism group and externally to other departments is laborious. To ensure unbiased and thorough analysis, Met ID is becoming increasingly reliant on software tools to aid expert users in their analysis. Tools such as Metabolynx have gathered many parts of this process into a workflow that allows improved identification and characterization of the metabolites in a more comprehensive and efficient manner. Within this package, the utilization of chemical information of the parent compound aids assignment and understanding of the parent compound using advanced in silico tools. This identification, characterization and use of structural and metabolic prediction to aid assignment and reporting will be demonstrated using rat liver microsomal incubations of Nefazodone. These chemically intelligent structural assignment tools are used to automate the structural assignment of the parent. Recently, these tools have been further applied to the localization of the site of the biotransformation for all of the identified metabolites through automated structural interpretation and visualization of the datasets. Once the metabolites have been characterized, additional predictive tools are available to the researcher. Improved integration with Meteor (Lhasa Inc) will be demonstrated, showing the ability to export the interpreted dataset directly from Metabolynx and further validate the pathways using thorough literature based, mechanistic understanding and filtering of plausible biotransformation structural possibilities. Continued software tool enhancements ultimately enhance and unlock the capabilities of HRMS instrumentation and allow scientists to make more confident analyses.
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