Internship Project
Biology and Neuroscience

Computational Modeling of Drug Detoxification – A Systems Medicine Approach

Institution
Humboldt-Universität zu Berlin
Subject Area
Systems Medicine of the Liver, Pharmacology
Availability
Position filled in 2023.

 
Internship Modality:
On-site internship in Berlin
Project Supervisor(s)
Dr. Matthias König
Academic Level
Advanced undergraduate students (from third year) 
Master's students 
Ph.D. students 
Language
English, German (optional)
Further Information
Project Type
Academic Research
Project Content
The liver is the main organ involved in the clearance of most drugs, e.g., acetaminophen. The function of the liver can be evaluated using information about the clearance of test drugs (pharmacokinetics data) in combination with computational models describing the absorption, distribution, metabolism, and elimination (ADME) of these substances in the human body. Within this lab project a physiologically based model of the elimination of an example drug in the human body will be established based on existing literature data. Such a model allows us to simulate in silico the pharmacokinetics of the example drugs and evaluate hypotheses, for instance, on drug-drug interactions or alterations in drug metabolism in disease or with age. The project will focus on acetylsalicylic acid or omeprazole (but other drugs could be used). The project is a computational project requiring basic programming skills, no wet lab work will be performed.
Tasks for Interns
  • Literature research and review
  • Digitization of datasets for computational modeling
  • Build a physiologically based pharmacokinetic model of the test drug (ordinary differential equations)
  • Parameter fitting
  • Model simulation and analysis (dose-dependency, parameter sensitivity)
  • Application to relevant medical questions (e.g., drug-drug interactions, sex differences, ...)
Academic Level
Advanced undergraduate students (from third year) 
Master's students 
Ph.D. students 
Requirements
  • Programming skills (Python);
  • Excel/LibreOffice;
  • STEM background.
Expected Preparation
Python course/preparation
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For more information on the Humboldt Internship Program or the project, please contact the program coordinator.