Metadata-Version: 2.1
Name: druglinker
Version: 0.1.1
Summary: Simple drug linking
Home-page: https://github.com/fgh95/DrugLinker
Author: Ferran Gonzalez Hernandez
Author-email: ucbpfgo@ucl.ac.uk
License: MIT
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: pandas (==1.0.3)

# DrugLinker

This package is a simple python module to obtain all unique drug identifiers that match a given input string.
It does it by matching the input term with DrugBank open-data vocabulary : https://www.drugbank.ca/releases/latest#open-data. 
It is useful to process candidate drug tokens after drug named-entity recognition (NER) or to directly match sentences after tokenization.

To install the package simply run the following in a bash shell:

```
pip install druglinker==0.1.1
```

Example of use in a python environment: 

```
from druglinker import dbsearch
dbsearch.get_ids("amox")
# output: ["DB01060"]
dbsearch.get_ids("amoxicillin")
# output: ["DB01060"]
dbsearch.get_ids("vancomycin")
# output: ["DB00512"]

# Simple sentence tagging:

text = "20mg of midazolam were administered intravenously"
for term in text.split():
    ids = dbsearch.get_ids(term)
    if ids:
        print(term)
        print(ids)

# output:
# midazolam
# ['DB00683']
```

For instance you can now easily find further information about the drug identifier detected (e.g. DB00683) at 
https://www.drugbank.ca/drugs/DB00683

