# Dynamic energy budget approach to evaluate antibiotic effects on biofilms

## TL;DR

This paper introduces a dynamic energy budget model to simulate and analyze the effects of antibiotics on biofilm survival, capturing spatial distributions and resistance mechanisms to aid therapy development.

## Contribution

It presents a novel computational framework combining cell metabolism and concentration fields to predict biofilm responses to antibiotics.

## Key findings

- Higher survival rates near substratum with active cell-targeting antibiotics
- Increased polymer production with antibiotic treatment
- Model aligns qualitatively with experimental observations

## Abstract

Quantifying the action of antibiotics on biofilms is essential to devise therapies against chronic infections. Biofilms are bacterial communities attached to moist surfaces, sheltered from external aggressions by a polymeric matrix. Coupling a dynamic energy budget based description of cell metabolism to surrounding concentration fields, we are able to approximate survival curves measured for different antibiotics. We reproduce numerically stratified distributions of cell types within the biofilm and introduce ways to incorporate different resistance mechanisms. Qualitative predictions follow that are in agreement with experimental observations, such as higher survival rates of cells close to the substratum when employing antibiotics targeting active cells or enhanced polymer production when antibiotics are administered. The current computational model enables validation and hypothesis testing when developing therapies.