Over the past decade, there has been increasing interest in being able to understand what the future will look like when it comes to scientific and technological emergences. Indeed, these advances are the foundations that will underpin future innovations in health care, drug manufacturing and biotechnology, as well as broader industries like information technology and defense.


Traditionally, the only way to get a glimpse of this future has been to talk to experts. One might go to a conference and conduct interviews, or they would build relationships with labs and ask researchers what they think is going to be hot.


With the current pace of global research output (4,000 academic papers published daily, 1.5 million per year), this approach just simply does not scale. Science has become so big that it is impossible to create a global picture of progress based on these types of ad hoc interviews. No individual has a broad enough knowledge of the entirety of science, and there are just too many concepts under research to collect experts to continuously approach and interview.


Thanks to a technology called Horizon Scanning, that’s about to change. Originally developed by SRI International for the U.S. Government’s $60 million IARPA FUSE project, Horizon Scanning uses a combination of advanced natural language processing, machine learning and text analytics to detect scientific and technical emergences that are still years away from materializing. The technology is being brought to market for the first time by Canadian start-up Meta, effectively giving biomedical companies a computational crystal ball than can project into the future and understand what the landscape of emerging topics, people and technologies will be.


Based on analysis conducted by SRI in 2013, Meta’s Horizon Scanning technology identified a set of terms that were among the fastest rising concepts and technologies in biomedicine, in reference to all other activity during that period. Each term was assigned a "prominence score’, which, based on the technology’s analysis, identified its predicted rate of incline. Scores of 0.3 or greater meant a high probability that the term would at least double in activity over the three-year period. Based on this information, the following predictions were made for 2016:


1. A deeper understanding of the function of the human genome, particularly around long noncoding RNAs (IncRNAs).

Following the initial sequencing of the human genome in 2001, researchers speculated that most of the genome was largely non-functional. However, recent studies have revealed something very different. A paper published this year in Nature Medicine by Maite Huarte revealed that IncRNAs, a diverse class of transcribed RNA molecules found inside a cell, may act as biomarkers to diagnose cancer. In 2016, we will see long non-coding RNAs being brought up again and again as crucial information pieces at the heart of the human genome. This could play a major role in diagnosing and treating several types of cancer – particularly lung and urological cancer.

Predicted Prominence (IncRNA): 0.544


2. Deubiquitinating enzymes (DUBs) as potential therapeutic targets.

In January 2015, the U.S. FDA approved two major drugs for the treatment of advanced Parkinson’s Disease – DUOPA from AbbVie, and Rytary from Impax Laboratories. These approvals effectively ended an eight-year drought in therapeutic progress around the disease. In 2016 this progress will continue, particularly around the context of deubiquitinating enzymes (DUBs). DUBs are a large group of proteases that cleave ubiquitin from proteins, and can counteract the beneficial effect of the Parkin protein. As more research is done around DUBs, specifically around their potential contribution to the treatment of Parkinson’s Disease, we will see even more waves of clinical progress over the next few years.

Predicted Prominence (DUBs): 0.478


3. More answers regarding the role that Von Hippel-Lindau proteins (pVHLs) can play in preventing metastatic tumors.

Von Hippel-Lindau proteins (pVHLs) are key proteins associated with Von Hippel-Lindau Disease, as well as certain cancers including renal cell carcinoma. pVHLs also regulate HIF proteins, which are responsible for sensing oxygen. Through this regulation, pVHLs can affect not only the formation of blood vessels, but also the formation and development of red blood cells. In 2016, we will see more investigation into the role that pVHLs can play in targeting the blood vessel formations, especially those essential for the formation of some metastatic tumors. Additionally, we will see pVHLs mentioned more and more as potential targets for the treatment chronic inflammation and chronic anemia – two conditions that will only become more prevalent as the aging population continues to grow.


Predicted Prominence (pVHL): 0.491


4. A decline in shRNAs and DNA microarrays.

As science and technology continue to blend, certain research topics will see less of the spotlight in 2016 and beyond. CRISPR has emerged as the method of choice in genetic engineering and as the new hope for gene therapy, which means less research effort will be spent on small hairpin RNAs (shRNAs).


Predicted Prominence (shRNA): 0.274


Additionally, DNA microarrays, which were at the peak of popularity only a few years ago, will continue to decline in prevalence throughout 2016, thanks to increasing affordability of new, more effective, technologies like RNA sequencing.


Predicted Prominence (rna-seq): 0.491


5. CRISPR will continue to rise in 2016 and beyond, and so will zinc-finger nucleases.

CRISPR, a powerful gene-editing technology dubbed by Nature as “the biggest game-changer to hit the field of biology since PCR” was first detected by Meta’s Horizon Scanning technology in 2010. By the end of 2015, it had been included in 2,434 research articles, and named Science Magazine’s 2015 Breakthrough of the Year. CRISPR’s dominance will continue in 2016, as more and more academic labs and drug companies embrace this technology and use it to edit animal genomes.


Predicted Prominence (CRISPR): 0.504


Interestingly, we are still seeing zinc-finger nucleases (ZFNs) on the rise, despite them being more complex to generate and use than CRISPR.


Predicted Prominence (ZFNs): 0.536

Top image credit: Patrick Hoesly