Engineering in Medicine and Biology Society

IT Building, Room #255
IUPUI School of Informatics
535 W. Michigan St.
Indianapolis, IN 46202

Proving that a drug that has seen human patients also works in another indication adds clear value for patients. The question for informatics is can these predictions be made systematically with precision. We will discuss two recent methods that add to this debate. The first one uses genetics associations (from Genome Wide Association Studies – GWAS) to find new indications for drugs some of which are being validated experimentally. The second one frames the side effects of drugs as pharmacological effects, relies on the observation that many drugs that treat a disease have similar side effects, and then predicts other drugs with similar side effects as potential treatments for the disease. In addition, we will discuss other techniques that use text mining, compound-based methods such as connectivity map, electronic health records, and other public data. We think the field of drug repositioning will continue to be an showcase for informatics techniques in medicine.

Pankaj Agarwal is the Director, Systematic Drug Repositioning, Computational Biology at GlaxoSmithKline. He obtained a B. Tech. in Computer Science & Engineering from IIT, Delhi. His Ph.D. is in Computer Science from the Courant Institute, New York University. His thesis was on "Cell-based Computer Models in Developmental Biology". Pankaj did a postdoc in Bioinformatics at the Washington University, St. Louis, MO. He was one of the founding members and directors of the International Society for Computational Biology (ISCB). Since 1996, he has been at GlaxoSmithKline, and has led on a number of projects to mine biological data in to demonstrate informatics value for the pharmaceutical industry. He leads the Systematic Drug Repositioning group at GSK and his research is focused on computational methods for discovering the right disease indication for drugs.

During the last two decades tandem mass spectrometry has become method of choice in high throughput proteomics seeking answers for important questions in life sciences concerning human health and environmental challenges. The most applied method allowing the highest throughput measuring by number of acquired spectra is high-resolution precursor spectra followed with low-resolution fragmentation spectra to obtain peptide or protein sequence information. In this talk we will illustrate and demonstrate the need for true high-resolution tandem mass spectrometry to address the complexity of proteomics samples.

N. Tolic is a research scientist at Environmental Molecular Science Laboratory’s Instrument Development Laboratory. His training is in mathematics and computer science applied to all aspects of software development and data analysis for mass spectrometry based proteomics. N.Tolic is currently involved in developing data analysis pipeline for top-down proteomics and localization and characterization of post-translational modifications in high resolution tandem mass spectra.