Welcome to the GitHub space of Matthias König and the König Lab, where we integrate Systems Medicine and Systems Biology to unravel the complexities of drug metabolism and liver function.

By combining computational modeling, data science, bioinformatics, and machine learning, we bridge biology, medicine, and clinical data to enable predictive, personalized healthcare solutions.

• 📈 Predictive Biomedical Modeling
  Focused on the liver and kidneys, we develop mechanistic models to predict system behaviors under various physiological and pathological conditions.

• 🧍‍♂️ Digital Twins Development
  We build physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models—virtual representations of individuals—to simulate and understand drug response variability.

• 🧪 Reproducibility & Open Research
  Transparent, traceable, and collaborative science is central to our mission. We promote open-source tools, versioned workflows, and reproducible computational pipelines.

• 📂 FAIR Data & Workflows
  We rigorously apply FAIR principles—Findable, Accessible, Interoperable, and Reusable—to all our data, tools, and workflows.

A central focus of our work is the creation of predictive digital twins—virtual patient models tailored to individual physiology. These models help:

• Understand inter-individual variability in drug response.
• Support precision dosing strategies.
• Explore the impact of lifestyle and disease on drug metabolism and treatment outcomes.

Explore our publications, projects, and repositories to dive deeper into our research and contributions.

🔗 Contact & Collaboration
Interested in collaborating or learning more? Get in touch via our lab website or check out the ongoing research right here on GitHub.