In 2003, a group of scientists and executives from the NIH, the FDA, the drug and medical-imaging industries, universities and nonprofit groups joined in a project that had no precedent: a collaborative effort to find the biological markers that show the progression of Alzheimer’s disease in the human brain. The collaboration is already serving as a model for similar efforts against Parkinson’s disease.

August 12, 2010 by Gina Kolata

In 2003, a group of scientists and executives from the National Institutes of Health, the Food and Drug Administration, the drug and medical-imaging industries, universities and nonprofit groups joined in a project that experts say had no precedent: a collaborative effort to find the biological markers that show the progression of Alzheimer’s disease in the human brain.

Now, the effort is bearing fruit with a wealth of recent scientific papers on the early diagnosis of Alzheimer’s using methods like PET scans and tests of spinal fluid. More than 100 studies are under way to test drugs that might slow or stop the disease.

And the collaboration is already serving as a model for similar efforts against Parkinson’s disease. A $40 million project to look for biomarkers for Parkinson’s, sponsored by the Michael J. Fox Foundation, plans to enroll 600 study subjects in the United States and Europe.

The work on Alzheimer’s “is the precedent,” said Holly Barkhymer, a spokeswoman for the foundation. “We’re really excited.”

The key to the Alzheimer’s project was an agreement as ambitious as its goal: not just to raise money, not just to do research on a vast scale, but also to share all the data, making every single finding public immediately, available to anyone with a computer anywhere in the world.

full online article

Organized by Michael Weiner, Center for Imaging of Neurodegenerative Diseases (CIND), UCSF, and Olga Brazhnik, NCRR

Oct. 12,  2010, 08:35 – 10:45

Hilton Rockville, MD
1750 Rockville Pike
Rockville, MD 20852

Organized by Michael Weiner, Center for Imaging of Neurodegenerative Diseases (CIND), UCSF, and Olga Brazhnik, NCRR

• Jim Ostel, National Library of Medicine, Data sharing from the NLM perspective
• Nuna Bandera, UCSD CCMS, Sharing of molecular data
• Arthur Toga, UCLA LONI, Sharing of imaging and clinical data
• Deepak Singh, Amazon Web Services, Cloud computing
• Nick Anderson, University of Washington, Data sharing by the CTSAs
• Panel discussion with audience interaction (Speakers + Leslie Loew, UCHC).
• Distribution of questionnaire to everyone in the audience. Purpose is to understand the views of the audience concerning data sharing, particularly what role Research Resources, the BTRCs, and the CTSAs should take concerning data sharing. Questionaire will be 1 page, and will be scored by staff during the conference. Results announced before the end of the conference.

Biomedical Technology Research Centers create critical, often unique technology and methods at the forefront of their respective fields, and apply them to a broad range of basic, translational and clinical research. This is accomplished through a synergistic interaction of technical and biomedical expertise, both within the centers and through intensive collaborations with other leading laboratories. The P41 Principal Investigator Meeting provides an opportunity once a year for the leaders of the BTRCs to interact with each other and with the National Center for Research Resources (NCRR) and National Institute of Biomedical Imaging and Bioengineering (NIBIB) leadership.

VIEW THE AGENDA

REGISTRATION

The transfer of scientific data has emerged as a significant challenge, as datasets continue to grow in size and demand for open access sharing increases. Current methods for file transfer do not scale well for large files and can cause long transfer times. In this study we present BioTorrents, a website that allows open access sharing of scientific data…

Morgan G. I. Langille^*, Jonathan A. Eisen

Genome Center, University of California Davis, Davis, California, United States of America

Large amounts of data are being generated annually on the connection between the sequence, structure and function of proteins. However, much experimental data are never deposited in databases and is thus ‘lost’ in journal publications or in PhD theses. At the same time theoretical scientists are in need of large amounts of experimental data for benchmarking and calibrating.

Damien Farrell, Fergal O’Meara, Michael Johnston, John Bradley, Chresten R. Søndergaard, Nikolaj Georgi, Helen Webb, Barbara Mary Tynan-Connolly, Una Bjarnadottir, Tommy Carstensen and Jens Erik Nielsen*

Centre for Synthesis and Chemical Biology, School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland

*To whom correspondence should be addressed. Tel: +353 1 716 6724; Fax: +353 1 716 6898; Email: jens.nielsen@ucd.ie

Received June 9, 2010. Revised July 15, 2010. Accepted July 30, 2010.

Large amounts of data are being generated annually on the connection between the sequence, structure and function of proteins using site-directed mutagenesis, protein design and directed evolution techniques. These data provide the fundamental building blocks for our understanding of protein function, molecular biology and living organisms in general. However, much experimental data are never deposited in databases and is thus ‘lost’ in journal publications or in PhD theses. At the same time theoretical scientists are in need of large amounts of experimental data for benchmarking and calibrating novel predictive algorithms, and theoretical progress is therefore often hampered by the lack of suitable data to validate or disprove a theoretical assumption. We present PEAT (Protein Engineering Analysis Tool), an application that integrates data deposition, storage and analysis for researchers carrying out protein engineering projects or biophysical characterization of proteins. PEAT contains modules for DNA sequence manipulation, primer design, fitting of biophysical characterization data (enzyme kinetics, circular dichroism spectroscopy, NMR titration data, etc.), and facilitates sharing of experimental data and analyses for a typical university-based research group. PEAT is freely available to academic researchers at <http://enzyme.ucd.ie/PEAT>.

Results are presented from the Data Curation Profiles project research, on who is willing to share what data with whom and when. Emerging from scientists’ discussions on sharing are several dimensions suggestive of the variation in both what it means ‘to share’ and how these processes are carried out. This research indicates that data curation services will need to accommodate a wide range….

Data Sharing, Small Science, and Institutional Repositories. Philosophical Transactions of the Royal Society A, 368(1926), 4023-4038, (2010).

Melissa H. Cragin, Carole L. Palmer, Jacob R. Carlson and Michael Witt

Results are presented from the Data Curation Profiles project research, on who is willing to share what data with whom and when. Emerging from scientists’ discussions on sharing are several dimensions suggestive of the variation in both what it means ‘to share’ and how these processes are carried out. This research indicates that data curation services will need to accommodate a wide range of subdisciplinary data characteristics and sharing practices. As part of a larger set of strategies emerging across academic institutions, institutional repositories (IRs) will contribute to the stewardship and mobilization of scientific research data for e-Research and learning. There will be particular types of data that can be managed well in an IR context when characteristics and practices are well understood. Findings from this study elucidate scientists’ views on ‘sharable’ forms of data—the particular representation that they view as most valued for reuse by others within their own research areas—and the anticipated duration for such reuse. Reported sharing incidents that provide insights into barriers to sharing and related concerns on data misuse are included.

Download the pdf version of this paper

Contemporary bioscience sometimes demands vast sample sizes and there is often then no choice but to synthesize data across several studies and to undertake an appropriate pooled analysis. This same need is also faced in health-services and socio-economic research. When a pooled analysis is required, analytic efficiency and flexibility are often best served by combining the individual-level data….

DataSHIELD: resolving a conflict in contemporary bioscience—performing a pooled analysis of individual-level data without sharing the data

Michael Wolfson¹, Susan E Wallace^2,3, Nicholas Masca⁴, Geoff Rowe¹, Nuala A Sheehan⁴, Vincent Ferretti^3,5, Philippe LaFlamme^3,6, Martin D Tobin⁴, John Macleod⁷, Julian Little^3,8, Isabel Fortier^3,8,9, Bartha M Knoppers^2,3 and Paul R Burton^3,4,8,10,*

¹Statistics Canada, Ottawa, Ontario, Canada, ²Centre of Genomics and Policy, Faculty of Medicine, Department of Human Genetics, McGill University, Montreal, Quebec, Canada, ³Public Population Project in Genomics (P3G), Montreal, Quebec, Canada, ⁴Departments of Health Sciences and Genetics, University of Leicester, Leicester, UK, ⁵Ontario Institute for Cancer Research, MaRS Centre, Toronto, Ontario, Canada, ⁶McGill University and Génome Québec Innovation Centre, Montreal, Quebec, Canada, ⁷Department of Social Medicine, University of Bristol, Bristol, UK, ⁸Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, ⁹Department de Médecine Sociale et Préventive, Université de Montréal, Montreal, Quebec, Canada and ¹⁰Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada

*Corresponding author. Departments of Health Sciences and Genetics, University of Leicester, Adrian Building, University Road, Leicester LE1 7RH, UK. E-mail: pb51@le.ac.uk

Background – Contemporary bioscience sometimes demands vast sample sizes and there is often then no choice but to synthesize data across several studies and to undertake an appropriate pooled analysis. This same need is also faced in health-services and socio-economic research. When a pooled analysis is required, analytic efficiency and flexibility are often best served by combining the individual-level data from all sources and analysing them as a single large data set. But ethico-legal constraints, including the wording of consent forms and privacy legislation, often prohibit or discourage the sharing of individual-level data, particularly across national or other jurisdictional boundaries. This leads to a fundamental conflict in competing public goods: individual-level analysis is desirable from a scientific perspective, but is prevented by ethico-legal considerations that are entirely valid.

Methods – Data aggregation through anonymous summary-statistics from harmonized individual-level databases (DataSHIELD), provides a simple approach to analysing pooled data that circumvents this conflict. This is achieved via parallelized analysis and modern distributed computing and, in one key setting, takes advantage of the properties of the updating algorithm for generalized linear models (GLMs).

Results – The conceptual use of DataSHIELD is illustrated in two different settings.

Conclusions – As the study of the aetiological architecture of chronic diseases advances to encompass more complex causal pathways—e.g. to include the joint effects of genes, lifestyle and environment—sample size requirements will increase further and the analysis of pooled individual-level data will become ever more important. An aim of this conceptual article is to encourage others to address the challenges and opportunities that DataSHIELD presents, and to explore potential extensions, for example to its use when different data sources hold different data on the same individuals.

Keywords Pooling, analysis, meta-analysis, individual-level, study-level, generalized linear model, GLM, ethico-legal, ELSI, identification, disclosure, distributed computing, bioinformatics, information technology, IT

Accepted 27 May 2010

Download the pdf version of this paper

We are about to find out just how generous nature really is. On Tuesday, astronomers operating NASA’s Kepler spacecraft will release a list of about 350 stars newly suspected of harboring planets, including five systems with multiple candidate planets. That data could dramatically swell the inventory of alien worlds, which now stands at 461.

We are about to find out just how generous nature really is.

On Tuesday, astronomers operating NASA’s Kepler spacecraft will release a list of about 350 stars newly suspected of harboring planets, including five systems with multiple candidate planets. That data could dramatically swell the inventory of alien worlds, which now stands at 461, none of them habitable by the likes of us.

Astronomers everywhere, who have been waiting since Kepler’s launch in March 2009 to get their hands on this data, will be rushing to telescopes to examine these stars in the hopes of advancing the grand quest of finding Earthlike planets capable of harboring life out there.

But a lot of attention has been paid in astronomical circles over the past few months to what the Kepler team will not be saying. By agreement with NASA, the team is holding back data on its 400 brightest and best planet candidates, which the astronomers intend to observe themselves over a busy summer. (more)

A new database of more than 4,000 Alzheimer’s disease patients who have participated in 11 industry-sponsored clinical trials will be released today by the Coalition Against Major Diseases (CAMD). This is the first database of combined clinical trials to be openly shared by pharmaceutical companies and made available to qualified researchers around the world.

First Combined Pharmaceutical Trial Data on Neuro-degenerative Diseases; Shared Resource from Unique Public-Private Partnership Will Help Accelerate Alzheimer’s, Parkinson’s, and Other Brain Disease Research

WASHINGTON, June 11 /PRNewswire-USNewswire/ — A new database of more than 4,000 Alzheimer’s disease patients who have participated in 11 industry-sponsored clinical trials will be released today by the Coalition Against Major Diseases (CAMD).  This is the first database of combined clinical trials to be openly shared by pharmaceutical companies and made available to qualified researchers around the world.

It is also the first effort of its kind to create a voluntary industry data standard that will help accelerate new treatment research on brain disease, as patients with other related brain diseases are expected to be added.  The level of detail and scope of this database will enable researchers to more accurately predict the true course of Alzheimer’s, Parkinson’s, Huntington’s, and other neuro-degenerative diseases, thereby enabling the design of more efficient clinical trials.  Patient identifiers will not be included in the database, thereby ensuring patient privacy.

CAMD is a formal consortium of pharmaceutical companies, research foundations and patient advocacy/voluntary health associations, with advisors from government research and regulatory agencies including the U.S. Food and Drug Administration (FDA), the European Medicines Agency (EMA), the National Institute of Neurological Disorders and Stroke (NINDS), and the National Institute on Aging (NIA).  CAMD is led and managed by the non-profit Critical Path Institute (C-Path), which is funded by a cooperative agreement with the FDA and a matching grant from Science Foundation Arizona.

“The U.S. Food and Drug Administration has supported and actively participated in this innovative and unprecedented public-private partnership from its inception,” said Joshua Sharfstein, MD, Principal Deputy Commissioner, FDA.  ”The agency is strongly committed to CAMD and other regulatory science collaborations that can speed safe and effective treatments to the public.”

In addition to sharing data, the pharmaceutical members of CAMD have agreed to use the new common data standard established for Alzheimer’s disease by the standard-setting organization, CDISC, in their future submissions for drug approvals.  The Clinical Data Interchange Standards Consortium (CDISC) is a global, multidisciplinary, non-profit organization that has established standards to support the acquisition, exchange, submission, and archive of clinical research data and metadata.  CDISC standards are vendor-neutral, platform-independent, and freely available via the CDISC website.  This will add greater efficiencies to the FDA’s review process and make it possible for new products to reach the market more quickly and with greater assurances of safety and effectiveness.

“This unprecedented data sharing is game-changing for companies that are developing new therapies for neuro-degenerative diseases,” said Raymond Woosley, MD, PhD, President and CEO of Critical Path Institute (C-Path).  ”Scientists around the world will be able to analyze this new combined data from pharmaceutical companies, add their own data, and consequently better understand the course of these diseases.”

Mark McClellan, MD, PhD, who launched FDA’s Critical Path Initiative during his tenure as FDA Commissioner, also noted the need for better evidence.  ”Too many treatments fail in the last stages of research, wasting millions of dollars and years of research time.  To get to faster, more efficient development of safe and effective treatments, we must have a better understanding of diseases at the molecular level.  The CAMD database is a promising step in this process for neurodegenerative diseases,” said Dr. McClellan, who is now the director of the Engelberg Center for Health Care Reform and Leonard D. Schaeffer Chair in Health Policy Studies at the Brookings Institution.

Roughly 6.5 million people in the U.S. are afflicted with Alzheimer’s and Parkinson’s diseases, with costs reaching as much as $175 billion annually. Worldwide there are already an estimated 30 million people with dementia alone.  By 2050, the number will rise to over 100 million. Halting or slowing the progression of these diseases will prevent untold suffering and save tens of billions of dollars every year.

“Data sharing is the backbone of several CAMD projects designed to identify patients who might develop brain diseases, i.e., before symptoms are apparent,” said Marc Cantillon, MD, Director of C-Path’s Coalition Against Major Diseases.  ”Our goal is to develop tools to prevent or slow these diseases so patients can maintain independence and quality of life.”

The CAMD database will allow researchers to design more efficient clinical trials that have the maximum chance of demonstrating if a new treatment is truly safe and effective.  In addition, the coalition is identifying biomarkers that identify patients in the very early stages of Alzheimer’s disease and Parkinson’s disease.

According to Maria Isaac, MASc, MD, PhD, Scientific Administrator, Scientific Advice, Human Medicines Special Areas Sector of the European Medicines Agency (EMA), “Within the context of the Innovative Medicines Initiative (IMI) in Europe, the EMA is committed to similar goals as C-Path’s consortia, i.e., to help biopharmaceutical drug development, for the benefits of patients.  The Agency is especially interested in reviewing CAMD’s Alzheimer’s biomarkers and disease progression models.”

Frank Casty, MD, VP Technical Evaluations, AstraZeneca Pharmaceuticals LP, and Co-Director of CAMD said, “AstraZeneca strongly believes that a healthier world must come from collaboration, in making better, deeper connections with all our stakeholders, and sharing skills and ideas to meet a common goal – improved health.”

CAMD Members: Abbott, Alliance for Aging Research, Alzheimer’s Association, Alzheimer’s Foundation of America, AstraZeneca Pharmaceuticals LP, Bristol-Myers Squibb Company, CHDI Foundation Inc, Eli Lilly and Company, F. Hoffmann-La Roche Ltd, Forest Research Institute, Genentech Inc., GlaxoSmithKline, Johnson & Johnson, National Health Council, Novartis Pharmaceuticals Corporation, Parkinson’s Action Network, Parkinson’s Disease Foundation, Pfizer, Inc., and sanofi-aventis US Inc.

About CAMD: CAMD members fully share pre-competitive data and knowledge that will more efficiently and safely speed development of new therapies and preventions for Alzheimer’s, Parkinson’s, Huntington’s, and other debilitating neuro-degenerative diseases.  CAMD’s overall objective is to help scientists identify clinical and laboratory characteristics of patients who are pre-symptomatic and most likely to benefit from new therapies.  For more information on CAMD and the database, visit http://www.c-path.org/CAMD.cfm.

About Critical Path Institute (C-Path): An independent, non-profit organization, C-Path’s mission is to serve as the impartial facilitator of collaborative efforts among scientists from government, academia, patient advocacy organizations, and the private sector to support the U.S. Food and Drug Administration’s regulatory science initiatives.  This involves creating faster, safer, and smarter pathways for innovative new drugs, diagnostics, and devices that will significantly improve public health.  Established in 2005, C-Path is headquartered in Tucson, Arizona, with offices in Phoenix, Arizona, and Rockville, Maryland.  Visit www.c-path.org for more information.

SOURCE Coalition Against Major Diseases

Back to top RELATED LINKS
http://www.c-path.org/CAMD.cfm