The role of natural language processing in advancing disease research 

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In any area of disease research, a deep understanding of recent and future trends surrounding a particular condition is crucial to the drug discovery process. But with the volume of scientific literature increasing all the time, it is difficult to manually sift through all the existing information and correlate data in such a way to produce meaningful direction. This predicament can lead to the misallocation of resources on research in areas that are less likely to yield promising treatments.

By analyzing all literature related to a specific condition or disease, researchers can better identify which areas will likely lead to a breakthrough. Natural language processing (NLP) uses a combination of linguistics, artificial intelligence, and computer science to understand text in the same way as people. Researchers can use NLP in trend analysis to determine the rate at whic…

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Prioritizing translational research is changing drug development for patients and doctors, for good

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Twelve years. That’s the average amount of time it takes for a viable therapeutic to make it from the research stage to approval for market. In that time, 2.4 million Americans will suffer the effects of severe acute pancreatitis, many of which can be long-lasting and debilitating. Roughly 240,000 of these patients will die as a result of the illness. This is from just one potentially treatable disease.

With more Americans falling ill to preventable diseases each year, the pressure has never been greater for researchers and developers to find ways to create higher-quality therapeutics in less time to save and improve lives. Surprisingly, the way forward is not to change the approval process but to improve the research and development methods applied at each pipeline stage.

The logjam isn’t the approval process — it’s the methods

At first glance, it is easy to assume …

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