Neurotechnosocioeconomics is the study of the ways that neurotechnology has an impact on social and economic systems.

I'm currently talking with Chris Murray at the Harvard School of Public Health about researching and writing a report on the Global Economic Burden of Neurological Diseases and Psychiatric Illnesses. The report, which would be sponsored by the Neurotechnology Industry Organization, would seek to calculate the economic burden for specific illnesses including Alzheimer's disease, addiction, anxiety, attention disorders, depression, epilepsy, hearing loss, insomnia, chronic pain, Parkinson's, schizophrenia, stroke and a few other brain-related illnesses. The report would determine the total economic burden for both the US and world and would include future projections given a few different technological scenarios.

The goal of the report is to get credible data about the economic consequences of brain diseases so that NIO can use them in Congressional testimony to argue for increased funding of translational neurotechnology research, tax incentives for neurotech investment, and a host of other purposes in support of NIO's mission to accelerate the development of treatments and cures for brain diseases.

Only by "dollarizing" the impact of these illnesses will it become undeniably clear how profound a problem brain diseases represent to the world's economies, especially with our growing and aging populations. Clear, credible, and "dollarized" data will allow our legislators to make intelligent trade-offs when determining budget priorities.

A key question the report will need to answer is what do we mean by economic burden, and how do we calculate it? There are three components to this type of analysis:

1. Prevalence, disability, mortality and DALYs lost. This is the standard components of the global burden of disease. There are well established methodologies to undertake this.

2. Expenditure in health systems on interventions for neurological and psychiatric conditions. This information is much harder to find given present data and will likely require considerable data collation or collection efforts.

3. Lost economic output due to these conditions. The problem with these
calculations is that they are the results of either (1) times some constant (a little more complicated but you get the idea) or (2) require panel data. There is much more methodological debate about how to do this well relative to the other two.

It is here where neurotechnosocioeconomic analysis will come into play. Unlike other medical technologies that generally result in someone surviving or passing away (e.g. cancer, heart attack), many neurotechnologies (e.g. drugs for schizophrenia) improve the quality of life across a continuum of disability (e.g. some people will return to be high functioning members of society - no economic burden, while others improve sufficiently only to be less than totally disabled - high economic burden).

Thus, the economic impact of a neurotechnology is dependent upon the how advanced a particular treatment is for each disease. A cure could equate to a low long term economic burden (but perhaps a high short term cost depending on the price of the treatment), while a drug that improves the quality of life for six months (e.g. current treatments for Alzheimer's) would shave only a tiny amount of the economic burden - high economic cost. I think you get the point.

While I believe that we will obtain some very useable metrics about the near term economic burden (0-10 years) given some assumptions of neurotechnologies in the clinical pipeline, medium and long term estimates will need to be analyzed in a scenario framework with different technological assumptions.

So, what's this study going to cost?

Before I answer that, why don't we ask, "What is it worth?"

What if we could increase funding for brain related diseases by $1 billion over the next five years? What if we developed tax incentives that accelerated investment in small innovation neurotechnology companies resulting in an additional $1 billion dollars of venture investment flowing into private commercial neuroscience startups in the next five years?

For context on these numbers, according to NeuroInsights, annual government support for the neurosciences across all institutes at the NIH is around $5 billion while total venture investment in neurotech in 2005 rose to a little more $1.5 billion. In this light, it become clear that the billion dollar increases I am suggesting above are not of the realm of consideration, especially when annualized over five years.

With the economic burden of Alzheimer's disease alone in the United States surpassing $100 billion a year, the potential payoff of making the decision to increase funding and incentivize investment seems quite rational. Moreover, since my research estimates that the global economic burden far exceeds $1 trillion, I believe a convincing case can be made.

But none of this will happen unless we have "clear, credible, and dollarized" information available to legislators to help them make intelligent decisions. In short, we must dollarize in order to help us prioritize.

So, okay, what is this going to cost?

From Chris, "Finally, in terms of cost, if this were a new research study, the price tag would be in the 2 million range. If you want an analysis built on existing studies which will be much less satisfactory, the cost is clearly going to be much lower. It really will depend on what you want to use the study for."

All of this said, I am now in the process of raising $2 million for this study. It seems like a minor investment relative to the billions of dollars of additional investment in support of the development of treatments for brain-related illnesses. Please join me in this campaign.