Skip to content

A Shiny web app that compares the molecular components of common beta-lactam antibiotics to clinicians in antibiotic selection for patients with previous history of reactions.

License

Notifications You must be signed in to change notification settings

liamlah/PenicillinX

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

52 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

PenicillinX

A Python Shiny web app that compares the molecular components of common $\beta$-lactam antibiotics with the goal to assist clinicians with antibiotic selection for patients with previous history of reactions.

Usage

The clinician selects two or more antibiotics based on previous reactions reported by a patient. PenicillinX assesses and highlights common structures between the antibiotics. With this method it may be possible to determine the structure responsible for a particular patient's previous reactions, and therefore allow the clinician to determine antibiotics that could be administered with a lower risk of reactions.

Warning:

This program is currently in development and MUST NOT be used in any clinical decision-making under any circumstance. Validation of the program's outputs against existing empirical data is ongoing, and a number of bugs are currently present during molecular substructure comparisons.

Testing

If you wish to give feedback, you can test a live version of the app here.

Dependencies and sources

  • Molecular structures were found using Reaxys. Their structures and substructures are stored using the SMILES format.
  • PenicillinX relies heavily on the RDKit open source Cheminformatics package for Python.
  • The Shiny for Python framework was used to build PenicillinX, including Shiny R for the early iterations of the program.

Licence

PenicillinX is licenced under the GPLv3. See the LICENCE file for more details.

About

A Shiny web app that compares the molecular components of common beta-lactam antibiotics to clinicians in antibiotic selection for patients with previous history of reactions.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published