Registry / ai-ml / drug-named-entity-recognition

drug-named-entity-recognition

library2.0.9pypypi✓ verified 81d ago

Drug Named Entity Recognition (NER) library to identify and resolve drug names in text, with entity linking to RxNorm and other drug databases. The current version is 2.0.9, supporting Python >=3.6. It provides pre-trained models for drug name extraction and normalization. The library is actively maintained with occasional releases.

ai-ml

pip install drug-named-entity-recognition

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · DRUG-NAMED-ENTITY-

drug-named-entity-recognition

ai-mlpythonv2.0.9

Install

2.1s avg

Import

—

Disk

21MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v2.0.9 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.000s · 22.6MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 2.1s · import 0.000s · 23MB

21MB installed

● package 21MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

drugs_finder

✓ from drug_named_entity_recognition import drugs_finder

✗ from drug_named_entity_recognition import DrugNER

find_drugs

✓ from drug_named_entity_recognition import find_drugs

✗ from drug_named_entity_recognition import DrugNER

molecular_properties

✓ from drug_named_entity_recognition import molecular_properties

✗ from drug_named_entity_recognition import DrugNER

Initialize DrugNER and extract drug entities from a text string.

from drug_named_entity_recognition import DrugNER drug_ner = DrugNER() text = "Patient was given 500mg of Paracetamol and 10mg of Diazepam." entities = drug_ner.find_entities(text) print(entities) # Example output: [{'name': 'paracetamol', 'rxnorm': '161', 'start': 24, 'end': 35, ...}, ...]

Debug

Known issues

gotchaThe first run downloads a large model (~2GB). Ensure sufficient disk space and a stable internet connection. The model is cached afterwards.

fix

Pre-download the model using: `pip install drug-named-entity-recognition && python -c \"from drug_named_entity_recognition import DrugNER; DrugNER()\"`

affects: all

breakingIn version 2.0, the API changed from `DrugNER().get_entities(text)` to `DrugNER().find_entities(text)`. Old code will break.

fix

Use `find_entities()` instead of `get_entities()`.

affects: 2.0+

deprecatedThe `DrugNER` constructor no longer accepts a `model_size` argument in 2.0.0+ (was `'small'`, `'medium'`, `'large'`).

fix

Remove the `model_size` argument. The model is now fixed.

affects: 2.0+

Upgrade

Version history

2.0.9latest on PyPI · released Jul 15, 2025

Audit

Dependencies

scispacyrequiredRequired for loading the biomedical NLP pipeline (en_core_sci_sm) used for drug entity recognition.

spacyrequiredCore NLP library dependency. Version must be compatible with scispacy.

Agent activity

19 hits · last 30 days

node

OpenAI (training)

Amazon

Resources

githubhttps://github.com/fastdatascience/drug_named_entity_recognition ↗

packagehttps://pypi.org/project/drug-named-entity-recognition/ ↗

homepagehttps://fastdatascience.com/drug-named-entity-recognition-python-library ↗

docshttps://fastdatascience.com/drug-named-entity-recognition-python-library/ ↗