MISSION

Orion Bionetworks is a nonprofit corporation dedicated to accelerating the discovery of next-generation diagnostics, treatments, and cures for brain disorders by harnessing the power of high-performance computing and data analytics to discover and develop predictive disease models from integrated biomarker, biosensor and phenotypic data.

Orion operates as a Public-Private Partnership Cooperative Alliance.  Orion organizes a network of partners who each contribute complementary and synergistic data, capabilities, or expertise to support a common roadmap for building predictive brain disease models.

Orion was founded in July 2012 and is based in Cambridge, MA, with alliance partners across North America and Europe. Orion’s vision is to apply this cooperative, multidisciplinary approach to many brain disorders, beginning with its flagship program for Multiple Sclerosis (MS).

Big Problems that Need Answers

Brain health is the leading personal and socioeconomic challenge of our age, demanding a disruption in how we treat and diagnose disease and create opportunities for prevention and cures.

Globally, 2 Billion individuals are directly affected by brain disorders with a catastrophic personal and societal cost exceeding $2 Trillion USD. These disorders, which number in excess of 600 diagnosable conditions, include neurologic conditions (such as multiple sclerosis and dementia), psychiatric conditions (such as schizophrenia and depression), substance abuse disorders, pain and brain injury.

The World Health Organization attributes 38% of the total years lost to death and disability to brain disorders, a figure well ahead of the next-closest and higher-profile diseases of cancer(12.7%) and cardiovascular disease(11.8%).

As our population ages, the likelihood and burden of brain disease increases, making this the quintessential challenge of our age.

Critical Need

We do not know the causes and mechanisms of most of these 600 disorders and consequently have inadequate treatments, no definitive diagnostics and no cures.

Without this knowledge we cannot predict disease onset, objectively diagnose patients, identify worthwhile targets for therapeutic intervention, assess benefit, or deliver optimized care.

To move forward, we need to rethink how we study brain disease, how
we define it, how we identify new targets, and how we advance precision medicine approaches. We need to do science at scale and embrace the complexity of disease. 

The Power of Prediction

Long before Hurricane Sandy made landfall on the Atlantic coast in October 2012, meteorologists had predicted its course and its likely impact. Although the storm caused enormous damage, the early warnings allowed people to prepare or evacuate areas that were directly in its path.

The development of computer simulations of weather has transformed our ability to track and predict the severity of “perfect storms” like Hurricane Sandy. The success of these simulations is based on their ability to piece together many different kinds of data – including air pressure and temperature, water temperature, wind speed 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.

We are at a unique crossroads in history (the Information Age) where this promise of computer technology is intersecting with emerging medical technologies that can capture diverse biological information, from gene activity and brain function to the presence of telltale proteins in the blood. Combining powerful computing with this wealth of information can help us understand the complex biology that underlies most brain disorders.

Our initiative starts with rich data. Our healthcare partners conduct studies that collect broad and deep biological and patient data from people with brain disorders over time. In parallel, our patient community partners use online and mobile platforms to gather complementary data on the impact of the disease on patients in the real world and in real time.

Through powerful computer programs, we can take what was once a fragmented picture of disease—many different types of data studied separately—and begin to explore how everything fits together. Then we use these programs to build predictive models, or simulations, of brain disorders as in our flagship program for multiple sclerosis (MS).

The prediction models can then help us:

• FIND biomarkers for new diagnostics,
• IDENTIFY molecular pathways for new therapeutic treatments,
• PREDICT the course of an individual based on their unique profile
• GENERATE best practice models for healthcare delivery