An Automated Biomarker Discovery Platform based on In Vitro Pharmacology Raw Data
Jia Xue, Henry Li, Sheng Guo
Discovery and validation of biomarkers from baseline and pharmcodynamic in vitro data is vital in oncology drug development. This process, however, is complex and labor intensive, with few robust tools readily available for automated computation discovery.
We’re developing an automated biomarker discovery platform for in vitro preclinical pharmacology studies. A variety of machine learning algorithms and statistical methods will be combined with an integrated suite of software facilities for data manipulation, calculation, and graphical display.
Read this Poster to Discover:
- That our new automated biomarker discovery platform will provide a new solution for precision biomarker discovery in preclinical oncology and immuno-oncology studies
- How our user-friendly platform will efficiently manage raw data uploads, data conversions, drug efficacy overview, and biomarker discovery analysis as well as data report generation
- Example datasets showing 83% prediction accuracy for selecting signature genes and 100% prediction accuracy for identifying differentially activated pathways