Internship Project

Computational Modeling of Drug Detoxification – A Systems Medicine Approach

Humboldt-Universität zu Berlin
Institute for Theoretical Biology
Subject Area
Systems Medicine of the Liver, Pharmacology, Digital Twins, Precision Medicine
 06 May – 26 July
 20 May – 09 August 
 03 June – 23 August 
 01 July – 20 September 

Internship Modality:
On-site internship in Berlin

The application is closed, and all positions have been filled.
Applications for 2025 will open in October 2024.
Project Supervisor(s)
Dr. Matthias König (
Academic Level
Advanced undergraduate students (from second year) 
Master's students 
Ph.D. students 
Further Information
Project Type
Academic Research
Project Content
Our body's inherent systems, particularly the liver and kidneys, play a critical role in the clearance of countless drugs. The function of these organs can be assessed using information on the clearance of test drugs (pharmacokinetic data) combined with computational models describing the absorption, distribution, metabolism and excretion (ADME) of these substances in the human body. This computational venture delves into these inner workings, focusing primarily on pharmacokinetics - the movement of drugs through the body. Interns will have the exciting opportunity to build a physiologically based model of drug elimination using existing literature data. This innovative model will be a powerful tool to simulate drug pharmacokinetics in silico, allowing hypotheses to be made about drug interactions, changes in metabolism due to disease or age, and more.

Why join us?
  • Unique experience: Not every day you get to combine computational modelling with pharmaceutical science to influence the future of drug development. 
  • Real-world application: Use your model to answer real-world medical questions, such as drug interactions or variations in drug response across different demographics.
  • No wet lab: While our project is deeply scientific, it's entirely computational. No wet lab work means you can fully immerse yourself in the world of digital modelling. 

More information:
Tasks for Interns
  • Literature Research: Delve into the literature, extract and review pertinent information.
  • Data Management: Digitize and curate essential data sets to pave the way for computational modeling. 
  • Model building: Design a state-of-the-art PBPK model of a test drug using ordinary differential equations.
  • Model Refinement: Fine-tune your model parameters through optimization.
  • Deep Dive Analysis: Perform in-depth model simulations to explore elements such as dose dependence and parameter sensitivity. 
  • Medical Relevance: Use your model to provide insight into medical issues, from drug interactions to sex differences in drug metabolism. 
Academic Level
Advanced undergraduate students (from second year) 
Master's students 
Ph.D. students 
  • Programming skills (Python);
  • Excel/LibreOffice;
  • STEM background.
Expected Preparation
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For more information on the Humboldt Internship Program or the project, please contact the program coordinator.