Historically, life sciences have been one of the first domains penetrated by machine translation and MT continues to be applied in this field with growing success. What is it that makes this domain lend itself well to MT? How can MT support different aspects of pharmaceutical translations? We will explore these topics in this blog post.
There are certain specialisms, or fields, where machine translation does not yield acceptable translation results. This would be anything that is highly creative, uses fluffy language full of ambiguities and plays on words and would normally be localised through transcreation or even require multilingual copywriting.
On the other hand, there are also domains that are susceptible to MT. Where language is well-structured and terminology rather standardised machine translation has a high chance of returning good quality translation results. That is very much the case with legal and life sciences sectors.
Complexity of pharmaceutical translations
The pressure of going global faster is not unique to the pharmaceutical world. It’s a struggle that many industries face and address with different measures. When we consider the complexity of releasing drugs into various markets around the world, including the need to carry out clinical trials in several countries and dealing with adverse event reports in different locations, anything that can help manage these processes is extremely valuable.
This increasingly means that machine translation use is not only the best option in some scenarios, but it often turns out to be the only sustainable option.
Monitoring safety of medicinal products
Life sciences are a delicate matter and the impact of any potential mistakes during drug testing or assessing side effects can be significant. Given the time pressure and the delicate nature of the matter, machine translation has been gaining popularity in a specific field of life sciences known as pharmacovigilance.
The European Medicines Agency, an EU body in charge of the evaluation and supervision of medicinal products, defines it as “the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other medicine-related problem”.
Any medication prior to being released to the market is carefully tested on a selected group of patients over a limited period of time. Once released, it is used by a much wider spectrum of users over a long period of time. It is in those circumstances that certain side effects might emerge.
The aim of any pharmacovigilance system is to continuously monitor the safety of all medicines throughout their use.
Machine translation in pharmacovigilance
Internal procedures along with complex regulatory requirements, both local and international, mean that organisations often need to act on reports of adverse events in a very short timeframe and that naturally presents a challenge. Especially, if we consider that these reports can be made in all possible languages.
When the number of adverse event reports grows, the amount of multilingual content that needs to be reviewed, assessed and addressed also grows. In 2018, more than 60% of such reports were non-English. When these processes would normally be resource-intensive and time-consuming machine translation, if applied with care and consideration, can take away a significant amount of pressure.
Machine translation engines can be trained or tailored in very narrow fields, and the more specific the training, the better results the engine is likely to return. MT can help with preliminary assessments of adverse effect reports and with categorising them; therefore helping pharmaceutical companies to comply with the relevant regulations.
While it doesn’t fully replace human tasks in the verification process, it assists humans allowing them to process reports faster and therefore ultimately provide better care for patients.
Life sciences are increasingly leveraging the power of machine translation. In the context of pharmacovigilance, machine translation helps pharmaceutical organisations to reduce any potential backlog of adverse event reports and as a result, contributes to serving patients better.