unal Ghosh is CEO of Inscopix, Inc., a neuroscience startup based in Palo Alto, California, developing end-to-end solutions for understanding the brain in action. This op-ed is part of a series provided by the World Economic Forum Technology Pioneers, class of 2015.  Ghosh contributed this article to Live Science’s Expert Voices: Op-Ed & Insights.

The human brain is the force behind civilization and culture. From the great works of literature and art, to spaceships that visit distant planets, to complex economic theories, all are embodiments of the extraordinary capacity of the human brain. The quest to understand how the brain works has fascinated and perplexed humankind for centuries. After all, the brain, with its 86 billion neurons and 100 trillion connections, is the most complex entity in the known universe.

This quest also has a purpose beyond curiosity: to alleviate the human suffering inflicted by brain disorders. While the global economic cost of brain disorders stands at $2.5 trillion and is projected to rapidly escalate in the coming decades, the development of therapeutics has been at a virtual standstill for the past 20 years.

To develop therapies for the brain, scientists must understand it

Almost 66 percent of all molecules that hold potential as a neurological treatment fail after entering phase III clinical trials, the phase that entails drug testing on patients to assess efficacy and safety. This is simply because the compounds are not effective.

Despite intense efforts, not a single drug can reverse the symptoms of Alzheimer’s disease , much less cure the disorder. This is especially worrisome as the world’s population ages.

Similarly, for the millions of people across the world who suffer from neuropsychiatric disorders such as schizophrenia and PTSD: Causes, Treatment & Symptoms (PTSD), treatments are only partially effective. The root cause for lack of robust therapeutic advances boils down to one factor: ignorance about how the brain works.

Governments across the world have recognized this problem, and launched efforts to better understand the brain in both health and in disease. Most notable among these efforts are the United States’ BRAIN Initiative, the European Union’s Human Brain Project and Japan’s Brain/MINDS Project. The central focus of such efforts is to decode the language of the brain; this is a language embedded in patterns of electrical and chemical signals that neuronal ensembles use for information processing.

Decoding these patterns in the healthy brain, and understanding how they go awry in brain disorders, will have profound implications for the development of next-generation brain therapeutics, be they small molecules, biologics or tiny, implantable devices that send electrical signals to correct (re-tune) aberrant brain-circuit activity.

Brain science needs a strong neuro industry

Like the Apollo Missions or the Human Genome Project, decoding the language of the brain will require new technologies. Specifically, it will require technologies to measure, manipulate and interpret electrical and chemical signals in the brain with exquisite precision, and on a broad scale.

This calls for not only collaboration amongst neuroscientists, engineers and data scientists, but also unprecedented cooperation among three major stakeholders: governments, research universities and the neurotechnology industry.

Today, governments organize and finance these “big neuroscience” initiatives, while research universities innovate new disruptive technologies and use them to conduct groundbreaking brain research. Unfortunately, the role of the neuroscience/neurotechnology industry, and of business in general, in this 21st-century grand challenge has remained ambiguous and poorly defined.

Nitin Nohria, the dean of Harvard Business School, once remarked, “There is no problem facing society and humanity today that can be solved unless business plays a vital role.”

I strongly agree. Both small, entrepreneurial ventures and large, established companies interested in commercializing innovative neurotechnologies and advancing brain science can play the unique role of integrating and accelerating the efforts of governments and research universities.

Disruptive technological innovation, while absolutely necessary, is completely insufficient to break new ground in brain research. Technological innovation must be accompanied by robust and rapid dissemination to significantly advance fundamental brain research and catalyze new approaches for developing new treatments. This is the unique and crucial role that only business can play. Companies such as SpaceX for space travel and Illumina for genomics serve as excellent analogues of what the companies that inhabit the 21st century neuroscience/neurotechnology space could do to revolutionize brain science and mental health.

What stands in the way?

There are two major barriers that preclude widespread dissemination of new disruptive technologies: iterative refinement and cost. The 21st century neurotechnology industry can help overcome both barriers.

Iterative technology refinement can involve taking a prototype developed in a university lab and commercializing it, and/or repeatedly improving a product for usability and enhanced capability (such as imaging at higher resolution, or at higher speed). Today, many disruptive neurotechnologies languish in the laboratories in which they were invented. Even if they are ready for “prime time,” they are not designed for manufacturability and scalability, are not optimized for usability, and are certainly not integrated as part of ready-to-use solutions for solving specific research questions. Technology innovators at universities are not incentivized to conduct iterative refinement or integration. And they should not be.

Translating disruptive neurotechnologies from a university lab into scalable, end-to-end solutions for brain-science researchers, and progressively improving those solutions, is what industry is best positioned and incentivized to do. The neurotechnology industry can apply industrial engineering principles, and play a pivotal and valuable role in migration of technology from the innovators’ laboratories into the broader field.

To reduce the costs associated with new, revolutionary technologies, the neurotechnology sector has a lot to learn from the cellphone industry. New state-of-the art neurotechnologies, especially instrumentation, are often expensive, and are limited to a few elite and wealthy laboratories and research institutions. There is thus an urgent need to level the playing field by democratizing access to new neurotechnologies to a wider spectrum of researchers.

The neurotechnology industry must seriously consider the “technology as service” concept and the subscription-based revenue-generation mechanisms that have been central to the near universalization of cellphones in fewer than two decades. Supplanting the traditional “purchase and ownership” with creative subscription-based mechanisms makes additional sense in this era of rapid and iterative neurotechnology development. Imagine a world where every brain researcher or neuroscience lab has access to not just one or two sophisticated brain-imaging systems, but dozens. Further imagine that the researchers could periodically swap their systems for the latest-generation versions. And imagine if all this were possible for a reasonable monthly subscription fee.

These are but two concrete ideas of how entrepreneurial ventures and industry can transform fields even as esoteric as brain research. Fortunately, there are excellent precedents to follow in other complex fields such as space travel and genomics. The quest to understand the human brain will be a defining feature of the 21st century. Now is the time for the neuroscience and neurotechnology industries to rise to the occasion.

Hear more from Inscopix in this video. Read more from the Technology Pioneers on their Live Science landing page. Follow all of the Expert Voices issues and debates — and become part of the discussion — on Facebook, Twitter and Google+. The views expressed are those of the author and do not necessarily reflect the views of the publisher. This version of the article was originally published on Live Science.