Published on October 27, 2009 at 4:32 AM
Reportlinker.com announces that a new market research report is available in its catalogue: Reportlinker Adds Data Mining in Drug Development and Translational Medicine
The biopharmaceutical industry is grappling not only with sheer data volume but with the ability of researchers to extract information through identification and contextual analysis of those data that are relevant to a particular set of investigations. This report examines:
- Techniques, technology, and software used in life science data mining
- Data mining for early preclinical safety assessments
- Data mining in clinical trials
- Data mining in pharmacovigilance
- Business models and solutions in drug development bioinformatics
The mountain of data generated and stored is growing ever-higher. The information content of life science data is multidimensional and not readily accessible by merely looking at the output. Unless such data can be put into proper context and interpreted-i.e., mined-their value is only in their potential. Data Mining in Drug Development and Translational Medicine examines data mining challenges and approaches in pharmaceutical R&D.
The pharmaceutical industry has made decisive moves to improve the predictiveness of early-stage drug safety testing. These efforts generate large amounts of data, in which the clue to safety-related, potential "red flags" can be buried. In this context we examine options for mining types of text data, "pathway mining" for pathway-related effects of a compound, and the multidimensional output of high-content screening methods. Also examined are approaches to mining data generated in preclinical trials for identification of toxicity signatures.
SOURCE Reportlinker