Issue #27 – Use case: Neural MT for the Life Sciences

27 Feb19

Author: Dr. John Tinsley, CEO @ Iconic

Neural MT has had quite a significant impact on how global enterprises are looking at translation automation to improve existing workflows. Above and beyond that, however, organisations are considering how machine translation can transform key areas of their business.

The reasons for this are clear – when adapted effectively for a particular use case, Neural MT can produce significantly better, more reliable results. Many enterprises dipped their toes into the world of MT in the past, found it inadequate, and the concept was abandoned. Now, it’s being revisited and adopted at scale, and the results are just that – transformative.

A prime example of this is the life sciences. Pressure to go global faster, get drugs to market around the world, run clinical trials in multiple countries, and assess adverse event reports, means that Neural MT is increasingly not just the best option, it’s the only option. In this article, we take a look at one particular use case in the field of life sciences where Neural MT is gaining a lot of traction: pharmacovigilance.

Use case: Pharmacovigilance

Pharmacovigilance, also
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