Modeling Overview

Introduction:

In the begining, our goal was to chelate iron in the duodenum, using bacteria that would flush through the duodenum and produce the siderophores. The aim was to predict the sufficient quantity of produced siderophores to reduce the iron intestinal absorption. We first had in mind a flush strategy, meaning we prioritized an approach where the bacteria would start their iron sensing and siderophore production before entering the duodenum. This qualitative Flush treatment model showed us that it is theoratically possible to significantly reduce the patient's iron absorption.

The conclusions were promising, encouraging and comforting regarding our strategy choice. Right afterwards, the aim was to detail the delay of siderophore production for a given bacterial production through an Enterobactin production model. This approach gave us more detail about timings. Unfortunately, the conclusions were in contradiction with the qualitative model because the delay is to big to be compatible with a flush strategy. This conclusion greatly influenced the biological part, especially in the design of the capsule. Because the iron absorption is split among the duodenum (60%) and the jejunum (40%), we decided to enhance growth in the proximal area of the jejunum. This is also why we chose to deliver a sticky gel with our bacteria and optimize its growth.

As a final part in the modeling, we also wanted to know how much siderophore can be produced and how we can improve this. We answered this with a Flux model, a flux balance analysis approach.

Models using ODEs:

Flush treatment	Enterobactin production
Disease model Final model	Sensor model Inverter model Final model

Models using other methods:

Flux model	Population scale
Flux model	Population scale

Tools:

When working on a scientific project, it is always good to properly define and clarify the tools we are going to use. These pages contain the theorical background for our models:

Programming methods	Logistic functions	Chemical reasoning