Cross-posted from Risk Sense
This week’s Risk Bites video takes a roller-coaster ride through some of the hottest topics in risk science.
Admittedly this is a somewhat personal list, and rather constrained by being compressed into a two and a half minute video for a broad audience. But it does touch on some of the more exciting frontier areas in reducing health risk and improving well-being through research and its application.
Here are the five topics that ended up being highlighted:
Despite pockets of cynicism over the hype surrounding “big data”, the generation and innovative use of massive amounts of data are transforming how health risks are identified and addressed. With new approaches to data curation, correlation, manipulation and visualization, seemingly disconnected and impenetrable datasets are becoming increasingly valuable tools for shedding new insights into what might cause harm, and how to avoid or reduce it. This is a trend that has been growing for some years, but is now rapidly gaining momentum.
Just four examples of how “big data” is already pushing the boundaries of risk science include:
- High throughput toxicity screening, where rapid, multiple toxicity assays are changing how the potential hazards of new and existing substances are evaluated;
- “Omics”, where genomics, proteomics, metabolomics, exposomics and similar fields are shedding new light on the complex biology at the human-environment interface and how this impacts on health and well-being;
- Risk prediction through the integrated analysis of related datasets; and
- Designing new chemicals, materials and products to be as safe as possible, by using sophisticated risk data analysis to push risk management up the innovation pipeline.
CLOUD HEALTH, or C-HEALTH
Hot on the tails of mobile-health, the convergence of small inexpensive sensors, widespread use of smart phones and cloud computing, is poised to revolutionize how risk-relevant data is collected, processed and used to make decisions. Sensors already built into smart phones are already being used to collect basic information on environmental factors that could impact on health – and increasingly sophisticated add-on sensors are becoming more and more available. On their own, these data aren’t that valuable. But with cloud computing it is becoming possible to process and analyze risk-related data from thousands or millions of users – and then provide contributors with personal, near real-time information on potential risks and avoidance strategies. We’re not there yet – but C-Health is on the way!
The idea of responsible innovation has been around for some time. The idea is to reduce the potential for future adverse health and environmental impacts by integrating risk management and avoidance strategies into the technology innovation process. And with new technologies emerging at an increasing rate, the social and economic importance of responsible innovation has never been greater. In fields ranging from advanced manufacturing, sophisticated materials and synthetic biology, to 3D printing and remote charging, there is an increasing push to ensure that technological development is informed by the science of risk. And it isn’t only to ensure actual risks are avoided – societal and economic success through responsible innovation also depends on addressing perceived risks.
The psychology and sociology of how individuals and groups make risk-relevant decisions, and the subsequent consequences of these decisions, is a critical component of the science of risk. Just because it is social science rather than natural science does not diminish its importance. In fact, without a sophisticated understanding of how empirical data on hazard, exposure and risk translate into human understanding and action, risk assessment and the science behind it is pretty worthless. But why call this frontier “headology” – which is a made-up word from satirical author Terry Pratchett? Apart from being a little tongue in cheek, I wanted to get away from some of the baggage associated with terms like “risk communication” and “social science”. But whatever you call it, in today’s increasingly connected world, understanding the human element linking data and action on risk is becoming increasingly important.
This is a bit of a catch-all, but as the “simpler” challenges associated with health risks are resolved (and I use the word “simple” with caution) we are being faced with an ever-growing array of more complex challenges. These include:
- Exploring and understanding the importance of non-linearity in dose-response relationships – especially at low doses;
- Getting a better handle on the health-relevance of low level exposures to some substances – especially over long time periods;
- Better understanding the science behind exposure to synthetic chemicals with hormone-like properties; and
- Understanding that nature and significance of epigenetic interactions – both within a generation and across generations.
These and similar areas arise from complex interactions between our bodies and the environment we live in – and create for ourselves. The list could be a lot longer, but the bottom line is that some of the knottiest and most significant challenges in risk science involve understanding the positive and adverse impacts of interactions that are not yet well understood.
There are other areas that could have easily made this list – and in all cases these are areas that will continue to remain important well beyond 2013. So feel free to expand on the list in the comments below. And have a great 2013!