The former head of Johnson & Johnson’s ($JNJ) initiative to develop stratified drugs for Alzheimer’s disease is trying to crowdfund the development of computer simulations of brain disorders. Magali Haas is seeking $299,900 for the project, which builds on a multiple sclerosis prediction model created by her nonprofit, Orion Bionetworks.

Haas began raising the money through crowdfunding site Indiegogo earlier this month. At the time of this writing, the campaign has attracted $5,354. Whatever cash is raised–regardless of whether the campaign falls short of its $299,900 target–will go toward the development of Orion MS 2.0, a scaling-up and expansion of the nonprofit’s first venture into MS modeling. Orion MS 1.0 used cash from J&J’s Janssen and data on 9,000 patients from Brigham and Women’s Hospital, PatientsLikeMe and Accelerated Cure Project to build a computer model of MS.

For version 2.0, Orion Bionetworks wants to gather data using biosensors and other methods from 1,000 people in PatientsLikeMe’s network, while also expanding the array of computational methods it uses to crunch the data. Whatever Orion Bionetworks can raise through Indiegogo is unlikely to fully fund its ambitions, but the organization thinks the cash can help it tap more traditional sources of financing. The plan is to add more members to the alliance, continue writing grant proposals and land a funding partnership.

Read the full article here.

Visit the fundraising campaign here.

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Click here for panel video

What if we started diagnosing brain disorders based on physiological measures as opposed to the behavioral measures that are currently in use now? This is the provocative question that kicked off the five-person panel discussion at the sixth annual Partnering for Cures, moderated by Kafui Dzirasa of Duke University Medical Center.

When someone presents in the emergency room with chest pain, an electrocardiogram (EKG or ECG) will most likely be used to assess the electrical activity of that person’s heart, and information about the heart’s function will be gleaned from that test – in essence, a physiological measure. When asked about opportunities to begin diagnosing brain disorders based on physiological factors,Magali Haas of Orion Bionetworks made it clear that in order for that to happen, one has to start defining brain disorders based on the underlying molecular biology that defines them. Deborah Dunsire of FORUM Pharmaceuticals echoed Haas’ sentiment and went further to describe how such information could affect drug development for brain disorders by stating that “…the great advantage of having that information would be to be able to target the drug more specifically to specific altercations and connect that physiological driver to the altercation that changes it.”

However, before we can even get to that degree of specificity within brain disorder therapeutics, we have to address the gaps in our understanding of the biology of the brain. Allan Jones of the Allen Institute for Brain Science described how work undertaken at the Allen Institute is working toward understanding brain architecture, at both the cellular and functional level. Jones gave the startling example that the average brain has about 85 billion neurons (a type of brain cell). We don’t really know how many types of neurons there are within that group or how those neuronal types function within a circuit in a normal human brain and in a diseased human brain. Dzirasa pointed out that this sort of initiative will require a different type of scientific approach, which Jones has referred to as “big science” – science being done in an orchestrated way, on a larger scale, with crisp and clear objectives. Jones’ idea of “big science” draws similar parallels to systems biology-integrated approaches to addressing brain disorders, which was a theme throughout the panel discussion.

Further emerging from the conversation was the idea that we need to build new frameworks to ask different types of questions. Meryl Comer of The Geoffrey Beene Foundation Alzheimer’s Initiative and WomenAgainstAlzheimer’s ran with that idea, stating that we need to “change the type of energy” surrounding our approach to brain disorders. Her organization launches innovation challenges to tackle big issues; she feels that by mobilizing and empowering “a new type of investigator,” such as citizen scientists and caregivers, we can inform the science and approach disease-modifying therapies faster.

Moving onto the question of treatment versus prevention, Reisa Sperling of Brigham and Women’s Hospital and Harvard Medical School made it clear that detecting early brain changes that lead to brain disorders, namely Alzheimer’s disease (AD), is imperative. Now that the technology exists to detect amyloid plaques and tangles (one of the main changes that happens in an AD-affected brain) in living people, it has been found that more than one-third of adults over the age of 65 has evidence of these plaques and tangles. However, as Sperling pointed out, questions still remain about whether those folks will indeed get AD, and more importantly, whether we can do something about it. Haas suggested that we need to build prediction tools that integrate multiple nodes of information, such as functional brain imaging, blood work, and cerebrospinal fluid sampling to tackle those questions.

Highlighting some of the barriers to tackling brain disorders, Jones pointed out that there is a cultural barrier in science of hoarding data, which needs to transition into more sharing and collaboration. To further that point, Haas believes that “we need to have a unified voice,” indicating that we may be too siloed in this space. She pointed out that there are more than 600 diseases of the brain, yet brain diseases are typically discussed as individual diseases, which may dilute advocates’ voices when they approach policymakers and funding agencies. Funding was another issue raised, as Sperling stated that “we need to make some major investment in the brain sciences… in basic research, translational, and clinical research within the next five years.”

In closing, Dzirasa asked the panel how we actually approach the existing barriers and push toward unlocking the mysteries of the human brain. Several ideas were advanced, from using public data to build prediction models, to funding from both the public and private sector, to data sharing. Among all the ideas, the whole panel underscored that collaboration is the key.

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Cutting Edge Genomic MS Research Earns Philip De Jager, MD, PhD, of Brigham and Women’s Hospital/Harvard, the 2014 Barancik Prize for Innovation in MS Research

October 23, 2014

About Multiple Sclerosis

Multiple sclerosis, an unpredictable, often disabling disease of the central nervous system, interrupts the flow of information within the brain, and between the brain and body. Symptoms range from numbness and tingling to blindness and paralysis. The progress, severity and specific symptoms of MS in any one person cannot yet be predicted, but advances in research and treatment are moving us closer to a world free of MS. Most people with MS are diagnosed between the ages of 20 and 50, with at least two to three times more women than men being diagnosed with the disease. MS affects more than 2.3 million people worldwide.

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Read the full report here: http://www.alzheimersanddementia.com/article/S1552-5260(14)02791-5/fulltext

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While many talk about a need to collaborate between different sectors of healthcare, Dr. Khalil has already been instrumental in several important alliances, including one with Orion Bionetworks, which focuses on transforming the study of brain disorders.

Click here to read the full article in PharmaVOICE July/August 2014.

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Computer analyses extract new insights from MS patient data

Since he was diagnosed with multiple sclerosis (MS) in 2007, Curtis Schreiner, a three-time U.S. Olympian in the biathlon, has pushed back against the encroaching physical limits. This winter, the former world-class athlete skied shortened 3-kilometer (2-mile) workouts. When cutting firewood on his rural upstate New York property, he operates a chain saw for only 1 hour. He cannot scramble up the climbing wall with his kids on the side of a house he built himself. His last attempt to hike a local mountain that he used to run up in less than 20 minutes ended in a slow survival shuffle back down.

Medical science can tell Schreiner surprisingly little about his future, despite more than a century of studies investigating postmortem brain tissue samples, mouse models, and molecular mechanisms, as well as clinical trials of dozens of therapies on thousands of patients. He deals with the uncertainties of his condition by staying as healthy as possible, taking drugs that he hopes will help, and comparing symptoms and medication side effects with other MSers on the online support network PatientsLikeMe.

Schreiner was one of 20 speakers at an April 4, 2014, meeting in Cambridge, Massachusetts, called “Bridging the brain disease knowledge gap through computational modeling and systems biology.” The wide-ranging meeting covered many issues and some early steps in deploying high-level computing power to better understand, predict, diagnose, and treat MS and other brain diseases. Participants addressed topics such as industry investment, integrated translational knowledge, big data as a shared resource, the systems biology approach, and patient networks.

Hosted by Orion Bionetworks, a Cambridge, Massachusetts-based nonprofit collaborative research organization, the meeting involved leaders from drug companies, academia, health care providers, the federal government, patient networks, and information technology and systems modeling companies. Participants in the first disease-modeling initiative, which is in MS, reported progress at the 1-year milestone. Speakers also addressed other disease areas, such as Alzheimer’s, Parkinson’s, amyotrophic lateral sclerosis, and psychiatric disorders.

Abandoned by industry

In aggregate, neurological and psychiatric disorders account for the largest disease burden worldwide, said Steven Hyman, M.D., director of the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, where the meeting was held. Disability plays a major role in global brain disease dominance, including conditions that strike early in life, such as MS and neuropsychiatric disorders, and the rising number of older people with dementia.

“You would think the pharmaceutical industry would be licking their lips and coming full throttle at the disorders,” Hyman said. But “since 2010, most companies have been disinvesting in brain disorders.” Brain disease is a difficult area because of the complexity of cell types; inaccessibility of the human brain for study; and the lack of plausible and validated drug targets, he said. Other problems include irreproducible results and animal studies that don’t translate to human disease.

Hyman and others enumerated many reasons that one solution to these difficulties may involve high-quality data paired with advanced computer modeling. Simulations can transform human data into an in silica model system that may overcome the inability of reductionist science to cure brain diseases.

Many of the participants view these patient-level data and the tools to analyze them as a necessary scientific and regulatory baseline upon which individual proprietary efforts can be built. As a shared resource, data and modeling platforms can increase the incentive and reduce the risk for any one company by identifying biomarkers, stratifying diseases, building confidence in therapeutic targets, and simulating clinical trials.

“We don’t have to own everything,” said Husseini Manji, M.D., global therapeutic head for neuroscience at Janssen Research and Development. “We need to advance science so everyone can take advantage of it.”

“Drowning in information but starved for knowledge”

Some answers may be lurking in existing data, waiting for someone to make the software connections and ask the right questions. “We’re drowning in information but starved for knowledge,” said Orion founder and CEO Magali Haas, M.D., Ph.D.

New data will be required for the most ambitious goals of modeling and predicting brain disease the way meteorologists can forecast storms. Several speakers called for setting up studies that collect extensive and reliable longitudinal data from big groups of people, akin to the Framingham Heart Study—only bigger. Funding would likely need to come from private companies or philanthropic sources.

“You will need large amounts of data in the beginning,” said Zaven Khachaturian, Ph.D., president of the Campaign to Prevent Alzheimer’s Disease by 2020 and founder of the extramural research programs on Neurobiology of Aging and Alzheimer supported by the National Institutes of Health.

Systems modeling may first help researchers find biomarkers for dementia and other brain diseases before debilitating symptoms appear (yellow line and orange arrows), and then run mock clinical trial scenarios to design a more efficient clinical study to test new therapies. Image courtesy of Zaven Khachaturian.

 

A systems modeling approach may result in new treatment paradigms, Khachaturian said. Traditionally, therapies either try to replace a missing molecule or to correct a single aberration. Brain diseases may be the result of the failure of multiple factors. Probing the neurobiology at a systems level may elicit unexpected relationships that can be perturbed to reset the system to a more functional state, much the way analyses of trader behavior can predict the behavior of the entire stock market. A challenge for modeling will come in the digital translation from one level of reduction to another, such as moving between molecular networks and functional disability.

Disease models may help explain how drugs that work actually have a therapeutic effect, likely through some combination of intended target and off-target mechanisms, said Keith Elliston, Ph.D., consulting scientific director for Orion. With the anticipated ability to track and incorporate more data from patient networks, others expect to find new ways of defining brain disease, as well as some common disease mechanisms underlying different conditions.

One major preparatory step is to find and understand existing data. Maryann Martone, Ph.D., described the Neuroscience Information Framework, a site she helped create that inventories and provides a search tool for hundreds of different kinds of data sets accessible on the Internet. The products of research are not just the scientific papers but also the data on which they rest. “People are grappling with the fact that machines provide access to a whole bunch of stuff,” she said, and that resulting data needs to be prepared for more widespread use on computers.

Early results in MS

Orion’s pilot project to understand the complex human experience of MS with powerful computers is at the early stage of assessing individual data sets. MS was chosen because it is one of the few brain diseases with data from long-term observational studies in people. “We need to take advantage of the data that is already out there,” Haas told MSDF after the meeting.

The team started with an MS natural history study at Brigham and Women’s Hospital in Boston that has followed more than 2000 patients for more than 5 years. Called theComprehensive Longitudinal Investigation of Multiple Sclerosis at Brigham and Women’s Hospital, the study collects multiple data points at patient visits, such as the neurological exam, blood samples, and MRIs. To build a model from which they could infer causal relationships, the key data had to be captured from every patient at every time point, which is a challenge inherent to traditional cohort studies. Digital experts call the resulting data “coherent,” a good thing. However, data from only 300 patients were complete enough for the analysis, with DNA, imaging, and clinical end points at each time point. Only 100 patients also had matching RNA data.

Orion partner GNS Healthcare used 100-year-old math and high-performance computers to extract the relationships between hundreds of thousands of variables. They found 57 molecular pathways associated with clinical endpoints, such as walking ability. Only three of the pathways had previously been associated with MS. The new MS pathways have previously been associated with neurogenesis, neurotransmission, neurodegeneration, and synaptic plasticity, Haas told MSDF.

Orion is raising money to expand the modeling study. The team wants to replicate the findings in another data set, conduct further testing in mouse models, capture more biological variables, such as the intestinal microbiome, and give wearable activity trackers and biosensors to patients to capture more details about how patients are able to get around. Ultimately, they want to sort out what is causal and what is reactive in the circuitry of the system, said Iya Khalil, Ph.D., executive vice president and co-founder of GNS Healthcare.

Patient reports tell a story

In another part of the pilot program, Orion funded PatientsLikeMe (PLM) to analyze theirMS community, which now numbers more than 36,000. “Our MS community is the largest in the world,” said Jamie Heywood, co-founder and chair of PLM. People volunteer information about their symptoms and medication effects and fill out surveys about their disabilities. “We have more data on the impact of Provigil in MS than was used to approve the drug,” Heywood said. Provigil (modafinil) is approved by the U.S. Food and Drug Administration to reduce excessive sleepiness in people with narcolepsy, obstructive sleep apnea, and shift-work disorder, but is also prescribed off-label to treat some types of fatigue in MS.

PLM has developed and tested a patient-reported outcome measure called the MS Rating Scale. “Here’s a disease that changes on a daily basis,” Haas said. “Some people wake up and feel great. By the end of the day they feel sick. Some have the opposite experience. Or they can go weeks without feeling anything wrong, and then they’re out for a week. That kind of waxing and waning tells you what’s relevant about the disease. It’s an incredibly rich way to tackle the phenomics,” she said, referring to disease symptoms. “It’s more powerful than observational clinical trials that only capture data on a monthly or yearly basis.”

The analysis funded by Orion probed the worsening dysfunction in MS over time. Instead of one symptom, such as a weak right leg, getting worse over time, the prevailing pattern was increasing disability from additional symptoms, such as also developing fuzzy vision and weakness in the right arm.

Biobanks with a new social contract

A third analysis is underway with the tissue repository at the Accelerated Cure Project (the nonprofit home of MSDF). Blood samples from more than 3200 people with MS, people with other demyelinating diseases, and controls are collected in the voluntary tissue repository, along with 50 pages of demographic, environmental, and clinical data for each participant. ACP provides the samples and information to researchers with the stipulation that they will return their data results with the anonymized identifiers, enriching the available data with every study.

“ACP is a way of building a biobank with a new social contract,” Heywood said. “If you take the samples, you’ve got to give back the data.”

The goal of the ACP analysis is to mine the rich repository database for clusters of gene expression and symptoms patterns that may define subgroups of disease, said Hollie Schmidt, ACP vice president of scientific operations. The results are expected in several months.

All the models are subject to a 1-year embargo before they are made publicly available, as an incentive to Orion collaborators, Haas said.

“There are over 600 disorders of the brain, but there is not one single cure,” Haas told MSDF. She and her collaborators look to cancer biology as a new paradigm for brain disease. Cancers are being redefined and treated by their molecular pathways. She and others believe they will find common mechanisms underlying different brain disorders, as well as new ways to reclassify and treat brain diseases now clustered under one diagnosis.

The archive of live-streamed meeting is available at the Orion YouTube channel (7 hours).

Key open questions

• What are the underlying mechanisms that drive relapse in MS? Does the microbiome interact with hormonal and inflammatory pathways in MS to play a role in relapse or disease progression?
• What are the underlying mechanisms and pathways driving disease progression and neurodegeneration in MS?
• Can researchers understand MS comorbidities, such as fatigue, mood, and sleep, in the context of the models?

Disclosures and sources of funding

Orion is funded by Janssen Pharmaceuticals, Thomson Reuters, PatientsLikeMe, GNS Healthcare, and private donors. Keith Elliston is CEO of the tranSMART Foundation, a nonprofit, open-source foundation; consultant to both Orion and GNS Healthcare; and co-founder of PSertain Technologies, a cancer diagnostic technology company, and Virtual Rx, a virtual pharma startup company. Magali Haas, Hollie Schmidt, and Zaven Khachaturian report no conflicts of interest. Accelerated Cure Project is the publisher of MSDF.

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Long before Hurricane Sandy made landfall on the US Atlantic coast last October, meteorologists had predicted its course and likely impacts. Although the storm caused enormous damage, the early warnings allowed people to prepare or evacuate areas that were directly in its path. If the storm had caught coastal residents completely by surprise, there is no doubt that the death toll and devastation would have been far worse.

The development of computer simulations of weather has transformed our ability to predict the severity of “perfect storms” like Sandy. The accuracy of these predictions is based on the simulations’ ability to piece together many different kinds of data—including air pressure and temperature, water temperature, wind speeds, and ocean currents—into a faithful model of the extremely complex phenomenon that is weather. Within the last decade, computer simulations have similarly revolutionized the fields of mechanical design, finance, ecology, and aerospace operations, among many others.

Brain disorders like multiple sclerosis (MS) are “perfect storms” too. They should, therefore, be amenable to similar computer simulations. In MS, genetics, environment, and hundreds of other factors come together to elicit the immune system attack on neurons of the brain and spinal cord, which are hallmarks for the disease. The issue is that we don’t yet understand how all these factors integrate to form a consensus map and a comprehensive picture of the disease. Thus, despite the impressive efforts of global academic research centers and patient advocacy groups to gather data from people with MS, we still have a very limited understanding of how MS works, who will develop it, or what it might do next. Trying to predict the course of MS—or any complex disease—based on a few kinds of disconnected data is like trying to track a hurricane by measuring air temperature and wind speed alone.

How can we get there?

We are now at a unique crossroads in biomedical research history. Advanced technologies such as gene sequencers and functional and volumetric MRI have given us access to an unprecedented amount of biological information. Mobile technologies now enable patient engagement and deep profiling of the disease experience. Biosensor nanotechnologies can give us real-time readouts on environment. Meanwhile, the revolution in high-performance computing has provided us with the ability to make sense of all this information and turn it into predictive disease models—disease maps we can actually use.

At the same time, scientists everywhere are embracing a more open, collaborative approach to research that transcends the walls of individual laboratories and builds connections across disciplines, geographies and industries. Like forecasting weather, the solution for predicting the storm of MS is the establishment of a global, virtual network of sensors and experts that feed information to supercomputers and computer modelers to enable the interpretation of complex data at the speed of thought. Earlier this year, we at Orion Bionetworks launched a cooperative research alliance committed to transforming the study of brain disorders such as MS and accelerating the discovery of new diagnostics, treatments, and cures. The success of this enterprise depends on building a growing community—or network—of organizations that will contribute to every aspect of the research. New partnerships and community-building efforts in the pharmaceutical and biopharmaceutical industry provide data and funding support, while collaborators who specialize in building sophisticated computer models of brain disorders offer technology and expertise. Information technology partners help create access, plus integrate and handle enormous volumes of data. Patient advocacy partners provide long-term data from people with MS, as well as help define long-term research goals. Lastly, partners in academic and government laboratories will help validate our simulations and generate new data to improve the predictive power of this approach.

\The foundation of such a network is the assembly of many different types of data—from gene activity to daily symptoms and response to medicines—from people with disorders like MS to determine how they are connected. After integrating the data, we build computer simulations that will allow clinicians and researchers to predict how disorders like MS will affect an individual. Our first MS simulation has already generated insights into novel MS-associated genes already known to be important in other CNS disorders. We are now launching pathway analysis studies to interpret what functional role these genes may have. Much as weather models allow the mitigation of storm damage, we hope to improve how we care for people with MS, and making the search for new therapies less expensive and more productive. It’s time to embrace the full potential of technology and scientific collaboration. By forming communities dedicated to using supercomputing and big data to understand MS and other brain disorders, we can achieve what’s been done with weather prediction, and then some. Unlike the weather, which we cannot change, we may be able to use these powerful new disease research tools not only to predict the approach of the perfect storm, but possibly to stop it entirely.

Magali Haas is the founder and CEO of Orion Bionetworks. Read The Scientist Article Here

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Alliance to develop predictive disease models will advance and speed the development of new MS
treatments
PHILADELPHIA, October 22, 2013 – The Intellectual Property & Science business of Thomson Reuters, the
world’s leading provider of intelligent information for businesses and professionals, today announced a
collaboration with Orion Bionetworks to further the understanding of multiple sclerosis (MS) and advance the
development of new therapies by generating predictive models of patient stratification and drug targets.

Orion Bionetworks is an alliance of leading organizations in patient care, computational modeling,
translational research, and patient advocacy dedicated to transforming the study of brain disorders and
accelerating the discovery of new therapies and the search for cures. In this project focused on advancing
the understanding of the underlying biology of MS, the members of the alliance will combine their expertise
and assets including biomarkers, disease system biology, high performance computing information
technology and big data analytics to integrate and interpret clinical, molecular, imaging and real-world patient
data to develop new predictive models for the disease.

“We are pleased to welcome Thomson Reuters, which brings unique modeling capabilities that will help
advance our shared goal of accelerating the search for cures for MS,” said Magali Haas, founder and chief
executive officer of Orion Bionetworks. “This collaboration further underscores the importance of building a
robust computational modeling community with diverse expertise and assets to help realize the promise of
predictive modeling in disease research.”

Thomson Reuters Life Sciences Professional Services researchers use MetaBase, the company’s flagship,
manually curated database of protein interactions, biological pathways, disease biomarkers and medicinal
chemistry, along with its unique collection of MS specific pathway maps and biomarkers, to construct
predictive models that identify molecular subtypes, biomarkers, associated mechanisms and novel drug
targets.

Thomson Reuters will provide Orion Bionetworks with the results of the modeling through access to the new
MetaBase MS pathways and networks via the Thomson Reuters MetaCore platform, an integrated software
suite for functional data analysis. The models will also be made available to the Alliance through tranSMART,
an open source data sharing and analytics platform.

“We are pleased to be collaborating with Orion Bionetworks on this initiative and providing both our research
expertise and the most authoritative content on biological pathways and molecular interactions,” said Joe
Donahue, senior vice president, Thomson Reuters Life Sciences. “Their cooperative research model brings
together academic groups, non-profit institutions and commercial companies to focus on specific diseases,
with the promise of developing new therapies faster.”

Thomson Reuters Life Sciences Professional Services is a multi-disciplinary team of molecular biologists,
bioinformaticians, medicinal chemists and data scientists. Learn more about Thomson Reuters Life Sciences
Professional Services.

Orion Bionetworks
Orion Bionetworks is a multi-institution cooperative non-profit alliance that is unlocking the power of shared
data and predictive modeling to help transform our understanding of diseases such as multiple sclerosis
(MS) and accelerate the search for cures. Alliance partners include leading organizations in patient care,

computational modeling, translational research, and patient advocacy: Accelerated Cure Project for Multiple
Sclerosis, the Institute for Neurosciences at Brigham and Women’s Hospital, GNS Healthcare, MetaCell,
PatientsLikeMe, Rancho Biosciences, and Thomson Reuters. For more information, go to
www.orionbionetworks.org.

Thomson Reuters
Thomson Reuters is the world’s leading source of intelligent information for businesses and professionals.
We combine industry expertise with innovative technology to deliver critical information to leading decision
makers in the financial and risk, legal, tax and accounting, intellectual property and science and media
markets, powered by the world’s most trusted news organization. With headquarters in New York and major
operations in London and Eagan, Minn., Thomson Reuters employs approximately 60,000 people and
operates in over 100 countries. Thomson Reuters shares are listed on the Toronto and New York Stock
Exchanges. For more information, go to www.thomsonreuters.com

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(PRWEB) July 02, 2013

Accelerated Cure Project (ACP) for Multiple Sclerosis, a national non-profit organization focused on promoting research to find a cure for MS, has engaged Rancho BioSciences to curate a large clinical and experimental dataset as part of its commitment to the Orion Bionetworks’ mission of building computational models of MS disease progression.

ACP, a founding member of the Orion Bionetworks Alliance, maintains the ACP Repository, a set of more than 3,000 clinical Case Report Forms, and associated blood samples, from people with multiple sclerosis, selected demyelinating diseases, and unaffected controls. ACP promotes the use of these resources by qualified research organizations (both academic and for-profit) with the proviso that research results obtained from these samples be returned to ACP for dissemination to, and utilization by, other researchers working to address the needs of the sample population. In alignment with its mission, ACP has agreed to make these datasets available to members of the Orion Bionetworks Alliance in order to facilitate the formation of valid computational models of disease progression.

Robert McBurney, CEO of ACP notes, “Subsets of the ACP BioRepository samples have been utilized in more than 70 research studies around the world. The datasets returned to the repository database from experiments performed on these samples are widely diverse, and range from GWAS and gene expression data to the results of high-throughput antibody, and metabolite measurements. We have incredibly rich and deep information on subsets of our samples, but the task of curating and integrating all these varied types of experimental and clinical data in a unified warehouse for analysis was daunting. Rancho BioSciences provides the expertise and resources we require on site.”

“Rancho BioSciences is thrilled to join in this effort,” says Julie Bryant, founder and CEO of Rancho BioSciences. “ACP has generated a powerful weapon in the fight against MS, and our expertise in data curation and inside knowledge of tranSMART will bring this resource to bear sooner and with more impact than would otherwise have been possible. In the field of computational modeling, good seed and test data is an essential resource; ACP and Rancho BioSciences working together can provide that.”

About Rancho BioSciences
Rancho BioSciences is a fee for service life science company leveraging open source tools and public domain data in Pharma, non-profit foundations and academia.

We have a team of experienced PhD scientists around the world that deliver high quality work on time and on budget. Our goal is to help the life science community build better tools and take advantage of a wealth of scientific data by supporting and developing open source platforms.

For more information about Rancho BioSciences, please visit us online at ranchobiosciences.com.

About Accelerated Cure Project for MS (ACP)
ACP is a nonprofit organization whose mission is to accelerate research efforts to improve the quality of life for people with multiple sclerosis (MS), to cure the disease and, ultimately, prevent it. The organization promotes scientific collaboration and accelerates research by rapidly and cost-effectively providing researchers with data and biospecimens they need to explore novel research ideas that can lead to better care for people with MS. Its strategic initiatives include:

•     The OPT-UP Program: A large-scale, real-world treatment outcomes clinical study and collaborative research program to optimize treatment of MS and understand progressive disability;
•     The ACP Repository: A collection of highly characterized biosamples and data from over 3,000 subjects, available to any scientists conducting research that can positively impact people with MS; and,
•     The Multiple Sclerosis Discovery Forum: An online community connecting, educating and challenging researchers (http://www.msdiscovery.org).

The organization’s innovative approach enables MS research to advance rapidly and catalyzes collaborative efforts toward a significant impact on this devastating disease. Its resources have supported 70 research studies worldwide and generated almost 300 million returned data points for collaborative data mining and disease modeling.

View the article here.

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