CCI PhD Student Timothy Schultz Wins Fellowship for Proposal to Track Trends in Alzheimer’s Disease Treatment

A thesis proposal by Drexel University College of Computing & Informatics (CCI) information studies doctoral student Timothy Schultz was recently selected for the iFellows Doctoral Fellowship Program—a $50,000 award (over two years) given to iSchool doctoral students to pursue independent dissertation research that supports the goals of the Coherence at Scale Program.

Coherence at Scale is a broad-based program aimed at coordinating and aggregating national-scale digital projects in order to promote the development of new technology environments to support advanced scholarship across disciplines. The Coherence at Scale Program is led by the Council on Library and Information Resources (CLIR) and Vanderbilt University.

His proposal, titled “Visualizing Clinical Trial Design Trends by Mapping the Alzheimer’s Disease Trial Space,” was one of five to receive the fellowship (from a pool submitted from 59 iSchools across the world). The proposal describes data collection and tracking methods with the ultimate goal of providing “researchers better understandings of the historical evolution of complex therapeutic spaces, such as Alzheimer’s Disease, and where promising treatment approaches may exist.” (See abstract below.)

Schultz’ research interests include developing data mining tools, visualizations and methodologies for translational research, particularly within the Alzheimer's disease therapeutic area, and for accelerating the discovery and subsequent application of novel scientific findings for pharmaceutical research.

The iFellows Program is made possible by an award from The Andrew W. Mellon Foundation received in 2014 by the University of Pittsburgh’s School of Information Sciences.

Abstract: Visualizing Clinical Trial Design Trends by Mapping the Alzheimer’s Disease Trial Space

The last few years have seen major shifts in how clinical trial data is being managed and shared. In November of 2013, President Obama introduced a “Big Data” initiative in which three innovative pharmaceutical companies agreed to collaborate for the purpose of extending the usability and functionality of ClinicalTrials.gov – the definitive albeit much maligned repository for clinical trial protocols. While ClinicalTrials.gov was initially intended to fulfill the needs of regulatory transparency, the searching and retrieval of plain-text documents leaves much to be desired. The goal is to unlock the information found within these documents to further elucidate the historical evolution of key therapeutic spaces, such as Alzheimer’s Disease. In short, I am proposing a novel method of extracting high-level themes within large corpora of ontologically annotated clinical trial protocols through a graph-based factorization framework, and integrating these themes with real clinical observation data obtained through the Alzheimer’s Disease Neuroimaging Initiative (ADNI). In doing so, I am proposing to model the temporal dynamics of these themes over time and identify factors which influence their success. I propose that this can be used to provide researchers better understandings of the historical evolution of complex therapeutic spaces, such as Alzheimer’s Disease, and where promising treatment approaches may exist.

Committee:

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