Biomedical Research Technology Transfer Applications (BRTT)

The overarching goal of research funded by our Ohio Board of Regents Biomedical Technology Tranfer (BRTT) grants is to develop applications that will tranfer from an academic setting to make a signifcant contribution to private sector scientific research, in areas including data acquisition, analysis, and management.

Some of our current and past application areas are listed below:

1. Demonstrate clinical grid infrastructure by integrating data systems that bring together clinical information, information from high throughput molecular studies, information from several radiological imaging modalities, and digital microscopy data from studies carried out by project principal investigators. Contributions from project PIs Wolfgang Sadee, Haifeng Wu, Charis Eng, and Ramana Davuluri will be combined with results from studies carried out by other targeted investigators such as OSU investigators Michael Knopp and Jay Zweier.
2. Develop Biomedical Informatics Synthesis Platform (BISP). BISP is a client/server application that will use web and grid service middleware. BISP will have the following functionality:
   • Allow users to browse attributes defined in each project database.
   • Allow users to view metadata used to define each attribute, controlled vocabulary terms associated with each attribute, and links to relevant controlled vocabulary dictionaries and references.
   • Provide support for virtual data center designers to define a view of the federated database that can be used to support a given study. Such views may require the specification of transformations that create a new attribute in the virtual database from several attributes in several project databases. For instance, "progression of atherosclerotic disease" will be synthesized from several attributes including cardiac catheterization studies, history of myocardial infarction, nuclear medicine studies etc.
   • The data center designer needs to be able to annotate how data center variables were designed. BISP will support addition of attributes to a study and will support redefinition of previously defined variables.
   • BISP will allow project database managers to specify authentication procedures and access privilege levels for virtual organizations and their members. BISP also will provide logging of system access transactions.
   • BISP will support definition of triggers on virtual study center attributes.
   • Ability to import controlled vocabulary from well defined bioinformatic data models (e.g. BSML) in conjunction with publicly defined data derived from the Human Genome project.
   • Provide front end to computational services as needed for clinical research studies (such as BLAST, PCR primer selection, multiple alignment). The timing of the implementation of this computational services interface will be driven by the requirements of the clinical studies involved with the project.
3. Develop or adapt client software to support visualization and both automated and manual annotation of biomedical images.
4. Develop web service/grid service based middleware to allow virtual data warehouses to be instantiated on arbitrary platforms. This middleware will allow specification of rules that define when attribute values are to be obtained from project databases or from third party sources. Examples of third party sources include controlled vocabulary definitions, patient data from referring clinics, and gene expression and proteomic data from external basic research labs.
5. Implement a grid database testbed that couples databases, storage systems and clusters located at the OSU medical center, the Ohio Supercomputer Center and Rescentris. This will include the OSU PACS, the Information Warehouse, the Seimens Electronic Medical Record, the GCRC database, project based gene expression, proteomic and genetic databases, the Biomedical Informatics Research Cluster, along with the Ohio Supercomputer Center clusters and storage systems. Construct and implement the Biomedical Informatics Research Cluster; this will be a cluster-based system that will be used to coordinate testbed computational and storage resources.
6. Carry out research studies that target tobacco related diseases. Studies will involve integration of clinical information, high throughput molecular data and image data. Direct project funding will be allocated for studies led by Dr. Wu, Dr. Sadee, Dr. Eng, and Dr. Davuluri. The project will also provide support for clinical studies carried out by Dr. Knopp and Dr. Zweier. Over the course of the project, we will identify additional clinical studies; the additional studies will be chosen based on their ability to drive development of software features that will be important to include in a general purpose clinical research infrastructure.

Project Researchers

Joel Saltz, M.D., Ph.D. (Principal Investigator)
Umit Catalyurek, Ph.D. (Co-Principal Investigator)
Tahsin Kurc, Ph.D. (Co-Principal Investigator)
Shannon Hastings, M.S. (Lead Researcher)
Stephen Langella, M.S. (Lead Researcher)
Scott Oster, M.S. (Lead Researcher)
Tony Pan, M.S. (Lead Researcher)
Hojjat Adeli, Ph.D. (Investigator)
Adel Mikhail, Ph.D. (Investigator)
Donald Stredney, Ph.D. (Investigator)

Project Funding Participation

A Comprehensive Program for the Prevention, Detection, and Treatment of Lung Cancer
Biomedical Informatics Synthesis Platform

Project Publications