The Next Frontier in the Business of Science: Improving Mental Health

If a cure, and ultimately a prevention, for such disorders as schizophrenia, autism or Alzheimer's can be developed in our lifetime, it will save trillions of dollars in medical and patient-care costs and a lifetime of family heartaches.
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In the past few months several major news events have thrust the issue of mental illness front and center into the national conversation. As policy makers, community leaders and mental health experts search for answers, it's worth taking a step back to look at some of the related issues.

According to the Alzheimer's Association, it is estimated that 35 million people and their families worldwide are affected by dementia, a degenerative neurological disorder that costs more than $203 billion in health-care-related expenses each year. This number is projected to increase to $1.2 trillion by 2050 as the world's population ages. Primary school children are routinely prescribed Ritalin to treat ADD and ADHD, and autism is the fastest-growing developmental disability in the U.S., affecting one in 88 children. Schizophrenia, Asperger's syndrome, bipolar disorder, clinical depression, addiction and eating disorders are becoming more prevalent among adolescents. The inherent dangers many people with mental health disorders pose to themselves and to others through their irrational thoughts sadly and routinely make the nightly news.

The report produced for the World Economic Forum in 2011, "The Global Economic Burden of Non-communicable Diseases" (NCDs), cited that mental health disorders are the leading cause of disability-adjusted life years (DALYs) worldwide and account for 37 percent of healthy life years lost. Related global costs are expected to more than double by 2030, imposing an immense financial burden upon families, and society as a whole, that may not always be covered by medical insurance. In an attempt to address the realities of the social and economic impacts of mental disorders, the Obama administration recently unveiled a new website featuring consumer-friendly tools intended to help people understand the early warning signs of mental illness, how to talk about it, and where to get help.

When faced with such seemingly overwhelming challenges, we turn, as we always do, to science to provide answers, and in this case the spotlight is on the rapidly expanding field of neuroscience. It has even bridged the gap into pop culture thanks to TV's Big Bang Theory and the growing popularity of Amy, Sheldon's neuroscientist girlfriend. The push to understand complex mental disorders that can so easily upset the delicate balance of our free society is one of research's greatest challenges. As much as we think we know, we also realize how little we know, and the search for time and money is often just as elusive as the answers we seek.

Behind the scenes, those of us on the business end of science face challenges that can be equally complex, albeit in a different way. Just as in any other industry, the product of science research is only as good as the tools and resources available. Effective and efficient processes, the playbook by which any business functions and thrives, are crucial. Text-based search engines, as useful as they are, don't deliver the highly specialized information neuroscientists need. The challenge for the business of science is to develop tools that will solve domain-specific workflow problems and provide access to the sophisticated integrated content that neuroscientists demand. Dynamic researcher-centric networked content, driven by tools that create a smarter interactive experience, also enable vital collaboration within the scientific community, an essential element to ensuring the success of any research project.

Recognizing the need to address both the short- and long-term neuroscience challenges, Elsevier has prioritized its commitment to supporting this vital work by developing customized vertical domain search tools to look for crucial information. The aim is to allow users to engage with content on a "vertical axis" through richer and more task-oriented views.

After interviewing hundreds of neuroscientists in five countries, we worked with our global researcher advisory board to identify the three most important search and discovery tasks facing neuroscientists:

  • Finding foundational information

  • Understanding what is known about brain region connectivity in the literature
  • Finding experiments similar to the one employed in the user's own research
  • Most neuroscientists employ high-level search terms that focus on the topic of study. For example, "hippocampus learning memory stress" would typically be used by scientists studying the effect of stress on learning and memory and the role of the hippocampus in that process. But what researchers really need are papers describing results of experiments with specific characteristics, such as studying certain neurotransmitters, certain receptors, a certain experimental model or methodology, a specific strain of mouse, and/or perhaps gender-specific mice.

    Finding a paper with the "right" methods is a tedious process involving extensive close reading, with success somewhat dependent upon a certain element of luck, a wasteful and inefficient process that neuroscientists can ill afford.

    The first Elsevier ScienceDirect Vertical Experience (SDVE) initiative focuses on creating and improving neuroscience methods, ontologies and rules for extracting and indexing methods sections of articles in 100 Elsevier neuroscience journals. As a result, we have built up a recommendation and comparison system that allows readers to see "Similar Methods" to the ones described in the article they are reading. The search process targets key factors in the experiments described in the article, such as what organism is being used, what brain regions are being studied, what disease model is the focus of the study and what methodologies are being employed.

    We present these factors and the option to see more papers with similar methods where the researcher is most likely to need them: next to the methods section in the article. The results page is essentially a sortable comparison table modeled on a spreadsheet where researchers can filter and limit the results based on the categories we have indexed. Using these features, it takes seconds to narrow down to a set of papers that might previously have taken hours of close reading.

    If time is money in the board room, it is even more so in a neuroscience lab, and the meter is surely running. The race is on to find the causes, treatments, and ultimately cures for a whole host of mental disorders. According to the NIH report "Estimates of Funding for Various Research, Condition, and Disease Categories" (RCDC), funding for mental health and neuroscience research is expected to reach some $13.6 million in 2014, a rise of about 10 percent from 2009. While the debate over allocating funding for research against other national needs goes on, it is worth noting that rather than cost we should be considering its intrinsic value.

    If a cure, and ultimately a prevention, for such disorders as schizophrenia, autism or Alzheimer's can be developed in our lifetime, it will save trillions of dollars in medical and patient-care costs and a lifetime of family heartaches.

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