Cyber Center

Bioinformatics Seminar

February 5 @ 4:30 PM - 5:30 PM - ME 1130

Date:  Tuesday, February 5, 2013
Time:  4:30 PM
Place: ME 1130

Speaker: Jake Chen; (IUPUI) Indiana University School of Informatics Purdue University Dept. of Computer & Information Science

Title: "Systems Pharmacology: are we ready for predicting new uses of old drugs?"

Abstract

Despite recent investment in genomics and personalized medicine technologies, drug discovery remains a proprietary, expensive, long, and speculative process, with low success rate of FDA approvals. A new drug discovery paradigm, "drug repositioning", has emerged in recent years, in an effort to address the challenge by systematically improving drugs' efficacy and toxicity profiles from existing pools of investigational drugs with proven pharmacological properties.

In our lab, we are interested in developing systems pharmacology resources and techniques to study both "on-target" and "off-target" effects of candidate drugs in drug repositioning. For systems pharmacology, I refer to the integrated application of systems biology and advanced informatics to modern pharmacology, which includes the development of network models that capture the complex relationships among genes, drug perturbens, diseases, and therapeutic/toxicological effects. I will highlight related work published in this area to identify research trends. Then, I will describe our recent efforts in this research direction, through examples that include: computational connectivity map development to predicting drug efficacy, gene set and pathway resource development, modeling of diseases using various network models, and prediction of drug's toxicity from network models. We believe research in this direction represent significant opportunities for translating bioinformatics!
  into breakthroughs in biomedical discoveries.

Associated Reading:

Li J, Zhu X, Chen JY (2009) Building Disease-Specific Drug-Protein Connectivity Maps from Molecular Interaction Networks and PubMed Abstracts. PLoS Comput Biol 5(7): e1000450. http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000450  

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