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In order to assist the drug discovery/development process, pharmaceuticalcompanies often apply biomedical NER and linking techniques over internal andpublic corpora. Decades of study of the field of BioNLP has produced a plethoraof algorithms, systems and datasets. However, our experience has been that nosingle open source system meets all the requirements of a modern pharmaceuticalcompany. In this work, we describe these requirements according to ourexperience of the industry, and present Kazu, a highly extensible, scalableopen source framework designed to support BioNLP for the pharmaceutical sector.Kazu is a built around a computationally efficient version of the BERN2 NERmodel (TinyBERN2), and subsequently wraps several other BioNLP technologiesinto one coherent system. KAZU framework is open-sourced:https://github.com/AstraZeneca/KAZU

Biomedical NER for the Enterprise with Distillated BERN2 and the Kazu Framework