MODELS FOR COLLABORATIONS AND COMPUTATIONAL BIOLOGY - Collaborative Computational Technologies for Biomedical Research - page 46

Quintiles and at the National Institute of Diabetes and Digestive and Kidney
Diseases (NIDDK). Among the project's results was evidence that adiponectin
is a robust predictor of glycemic response to PPAR agonists in type II diabetes
patients and that adiponectin has potential utility across the spectrum of
glucose tolerance. Despite the challenges overcome by this project, the most
important lesson learned is that cross-company precompetitive collaboration
is a feasible robust approach to biomarker qualifi cation [4] . Additionally — and
equally important—this project served as a positive demonstration that cross-
company collaboration is a feasible and powerful approach to biomarker
qualifi cation. For more detail see www.biomarkersconsortium.org.

3.4.3 Alzheimer ' s Disease Neuroimaging Initiative

Launched on October 1, 2004, the Alzheimer's Disease Neuroimaging Initiative
(ADNI) is the NIH's largest public-private partnership focused on brain
research and designed to gather and analyze thousands of brain scans, genetic
profi les, and biomarkers in blood and cerebrospinal fl uid (CSF).
This large-scale initiative was initially designed as a fi ve - year research
project aimed at defi ning biomarkers for use in clinical trials to determine the
best way to measure treatment effects of Alzheimer's disease (AD), but the
goal has been expanded to using biomarkers to identify AD at a predementia
stage. ADNI involves scientists at 59 research centers, 54 in the United States
and 5 in Canada. There are over 800 participants comprised of 200 with AD,
400 with mild cognitive impairment (MCI), and 200 with normal cognition.
The success of this initial study has led to the launch of a phase 2 of ADNI in
the spring of 2010.
The overall goal of ADNI is to defi ne the rate of progress of mild cognitive
impairment and AD, to develop improved methods for clinical trials in this
area, and to provide a large database which will improve design of treatment
trials. A secondary, long-term expectation is that the results of this project will
provide information and methods which will help lead to effective treatments
for AD, leading to effective prevention.
The ADNI project was originally funded by the government for $60 million,
with $40 million from the National Institute on Aging (NIA) and National
Institute of Bioimaging and Bioengineering (NIBIB), which was leveraged
with $20 million from the pharmaceutical industry and several foundations.
A hallmark of ADNI is that there is public access of the clinical and imaging
data through the ADNI website and a parallel website at the Laboratory of
Neuroimaging, making this a true “precompetitive” consortium.
A second important aspect of ADNI is it is governed by a steering commit-
tee comprised of the principal investigators (PIs), all funded core leaders, all
site PIs, representatives of the NIH and FDA, and representatives of the com-
panies contributing funding (observers only). Together with the Executive
Committee and the Industry Scientifi c Advisory Board, these bodies ensure
that the ADNI project adheres to the study design and methodology laid out