NLP Use Case Database
Project Charter
This collaborative project was launched to create a bottom-up qualitative Natural Language Processing (NLP) Use Case Database, to allow NLP practitioners in pharma companies to share successes and failures with their peers.
The Challenge
Natural Language Processing offers great promise to improve efficiency and understanding of relationships and extract meaning from vast amounts of unstructured text. Pharma companies apply NLP methods in hopes of automation and insight generation. NLP experts have been investing significant resources in developing tools to address multiple business cases throughout the pharma industry in domains as varied as R&D, pharmacovigilance, and manufacturing.
With the advent of Large Language Models the overall level of investment in NLP is at the all-time high, as well as the hype that surrounds the technology. But just as with other information technology projects the returns on investments in NLP are not always up to one’s expectations.
The objective of this project is to document the successes and failures in NLP development, discuss these projects in a candid and collaborative manner, and to derive lessons learned that may be broadly applicable. We include case studies from within the Pistoia Alliance project portfolio and from the solutions implemented by our member companies. We believe that the resulting set of bet practices in NLP and LLM pharma use cases will benefit our community.
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