Why NLP Is the Key to Interpreting Unstructured Data in Pharma Drug Discovery

Natural Language Processing is a field of AI, which draws disciplines from computational linguistics and computer science to help machines infer the grammatical relations, semiotic annotations, and sentiment analysis of a clause in order to better understand human language.

Within the healthcare sphere, NLP can be applied in a variety of situations, from reducing preventable deaths as a result of medical errors, to identifying clinical pathologies. For NLP in the Pharma industry, this can mean assessing the market potential of a new drug, as well as targeting patient populations more accurately for existing drugs. NLP is much faster than human processing and can standardize mass amounts of both qualitative and quantitative unstructured data quickly into usable information with actionable insights.

There is a wealth of real-world data from the healthcare and pharmaceutical industries.

Gathering information from traditional techniques such as focus groups, interviews, and questionnaires is a financial burden and time-consuming for pharmaceutical companies. NLP provides new ways to address even larger population sizes through the complex analysis of online posts and reviews from patients. Using real-world and up-to-date information from sources like social media and forums also helps companies identify and respond to any concerns or developments, as NLP filters through the unstructured data to produce clear breakdowns of information.

Contributed Commentary by Sundeep Reddy Saireddygari July 19, 2021 |

Read the source article at bio-itworld.com
2021-07-19 09:00:00