May 6, 2011
CONTACT: Kim Menard
Penn's Center for Neurodegenerative Disease Research Collaborates on Integrative Informatics Partnership to Improve Alzheimer's Disease Monitoring
Penn's Center for Neurodegenerative Disease Research (CNDR) will partner with Johnson & Johnson Pharmaceutical Research and Development, L.L.C., (J&JPRD) to develop algorithms that can identify changes in biomarkers related to disease diagnosis and for monitoring disease progression.
The three-year project entitled "Neurodegenerative Informatics and Biosignature Program" will integrate CNDR's robust and interactive database of clinical, pathological and biomarker information on patients with neurodegenerative disease — especially Alzheimer's disease (AD) — with other public datasets for neurodegenerative disorders, such as the Alzheimer's Disease Neuroimaging Initiative (ADNI, www.adni-info.org/).
"This partnership allows us to pool our resources, build on our respective work and look at the data under a new light," said Li-San Wang, PhD, Assistant Professor of Pathology and Laboratory Medicine at the University of Pennsylvania School of Medicine, who will lead this project in collaboration with a team from Penn's CNDR. "We look forward to investigating new ways to mine the data for biomarker features that can help us track AD better and distinguish AD from other forms of dementia." The research team also includes Penn Medicine's John Q. Trojanowski, MD, PhD; Virginia M.-Y. Lee, PhD, MBA; Steven Arnold, MD; Vivianna Van Deerlin, PhD; Les Shaw, PhD; Christos Davatizikos, PhD; and Sharon Xie, PhD; and Young Baek.
J&JPRD will provide expertise in the integration, analysis, and mining of complex and heterogeneous discovery, translational, clinical, and health outcomes data. J&JPRD is funding the joint project.
The collaborative CNDR — J&JPRD team — with experts in neurology, imaging, biostatistics, genetics, biomedical informatics, data mining, and computational analytical methods — will use state-of-the-art data fusion approaches to integrate multiple datasets and apply machine learning approaches to characterize the behavior of markers of interest.
"This initiative will accelerate efforts to realize the goal of making personalized medicine a practical reality for AD," said Dr. Trojanowski, director of Penn's Alzheimer's Disease Core Center, who noted that this is particularly timely with the rise of 'desktop medicine,' which describes a shift towards identifying personalized disease risk factors and intervening to prevent disease. "We hope to swiftly improve diagnostic accuracy and individualize therapy effectively for our patients."
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