Computer simulations as a tool to identify the safety of drugs

Computational models are powerful tools in the development of new drugs. This project will develop new tools to identify side effects of drugs.
Master

Cardiac simulations are growing to become important tools in the development and testing of drugs by the pharmacological industry. One of the main applications is the use of biophysical models of cardiac cells to estimate the risk of serious side effects such as cardiac arrhythmias. The goal of this project is to develop algorithms and methods to integrate experimental data of drug interactions into computational models of the heart. These models will be used to study the mechanisms of development of arrhythmia; more specifically, we aim at identifying what is the minimum level of complexity that a model needs to reproduce the side effects of well-studied drugs.

Goal

Develop computational methods to classify the risk of drugs based on experimental data published by regulatory agencies.

Learning outcome

  • The candidate will gain experience in biophysical modeling and simulation.
  • Especially with respect to how to integrate biological data into mathematical models.

Qualifications

  • Strong programming skills (Python).
  • Basic understanding of Ordinary Differential Equations Systems (ODEs).
  • Experience with biophysical models is preferable, but not a requirement.
  • An interest in learning how to model cardiac electrophysiology.

Supervisors

  • Bernardo Lino de Oliveira
  • Glenn Terje Lines

References

www.sciencedirect.com/science/article/pii/S245231001730001X?via%3Dihub
ieeexplore.ieee.org/document/7552472/