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Is semantic technology the AI sweet spot for pharma?

Barley Laing, UK managing director at Melissa explains why a new type of artificial intelligence could help solve problems for pharma researchers.

Published: | 3 min read

Barley Laing, UK managing director at Melissa explains why a new type of artificial intelligence could help solve problems for pharma researchers.

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 Artificial intelligence (AI) has been trumpeted by many in the pharmaceutical industry as the magic bullet to the issues they face in drug discovery and other research. However, expectations need to be tempered because although it’s easy to get excited by the potential of AI it’s important not to get too carried away with the reality of what’s possible today – at least at low cost and at virtually no risk. 

The standout value that AI can currently provide to the pharmaceutical industry is in removing the bottlenecks around data identification, extraction, quality, harmonisation and integration. These are all issues that have plagued the pharmaceutical industry for a long time. And in an age of digitisation where researchers are increasingly facing a proliferation in the types and variations of data, including drug doses and molecular structures in many forms, such as text, numbers and images; it’s AI that can play a vital role in helping to make sense of it all.

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