We have updated the Drug Name Recogniser Google Sheets™ plugin to cover molecular mass, chemical formula and SMILES strings.
Link to install the tool: https://fastdatascience.com/ai-in-pharma/drug-name-recogniser
Natural language processing
We have a Python library available which you can find on PyPI and on Github. It’s fully open source with MIT License.
You can install the Python library by typing in the command line:
pip install drug-named-entity-recognition
You can also try the library in your browser on Fast Data Science.
Fast Data Science provides NLP consulting for the pharma industries. Our flagship product is the Clinical Trial Risk Tool https://clinicaltrialrisk.org.
Looking for experts in Natural Language Processing? Post your job openings with us and find your ideal candidate today!
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You are probably familiar with traditional databases. For example, a teacher at a school will need to enter students’ grades into a system where they get stored, and at the end of the year the grades would need to be retrieved to create the report card for each student. Or an employee database might store employees’ home addresses, pay grades, start dates, and other crucial information. Traditionally, organisations use a structure called a relational database, where different types of data are stored in different tables, with links between them, and they can be queried using a special language called SQL.
A problem we’ve come across repeatedly is how AI can be used to estimate how much a project will cost, based on information known before the project begins, or soon after it starts. By “project” I mean a large project in any industry, including construction, pharmaceuticals, healthcare, IT, or transport, but this could equally apply to something like a kitchen renovation.
Senior lawyers should stop using generative AI to prepare their legal arguments! Or should they? A High Court judge in the UK has told senior lawyers off for their use of ChatGPT, because it invents citations to cases and laws that don’t exist!
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