2026-03-12		Digital Twins and Dashboards for Personalized Drug Treatment Matthias König Patient Monitoring Roundtable (PMRT)
2026-02-02		libsbgnpy - A Python Library for Handling Systems Biology Graphical Notation (SBGN) Matthias König HARMONY2026 - Computational Modeling in Biology
2026-02-02		pymetadata: Python Utilities for Metadata, Semantic Annotation, and COMBINE archives Matthias König HARMONY2026 - Computational Modeling in Biology
2026-02-02		Standardizing Parameter Estimation Problems with PEtab 2 Matthias König, Frank T. Bergmann, Dilan Pathirana, Daniel Weindl, Sebastian Persson HARMONY2025 - Computational Modeling in Biology
2025-10-20		Reproducibility by Design: Data and Workflows for Pharmacokinetic Digital Twins Michelle Elias and Matthias König COMBINE2025 - Computational Modeling in Biology
2025-10-16		Reproducibility by Design: Data and Workflows for Pharmacokinetic Digital Twins Michelle Elias and Matthias König RDA 25th Plenary Meeting [part of International Data Week 2025] - Towards reproducible and transparent computational modelling in health and biomedical research
2025-10-14		Reproducibility of a Digital Twin of Glimepiride for Personalized and Stratified Diabetes Treatment Michelle Elias and Matthias König 18th International CellML Workshop
2025-09-10		Reproducibility of a Digital Twin of Glimepiride for Personalized and Stratified Diabetes Treatment Michelle Elias and Matthias König Institute for Theoretical Biology, Institute Seminar
2025-06-16		Reproducible Digital Twins for Studying the Effect of Disease on Pharmacokinetics Matthias König 17th International Conference on Systems Biology of Human Disease (SBHD2025)
2025-04-24		Digital Twins of the Liver in Pharmacokinetics Matthias König Camo Seminar, KIT Institute of Biomedical Engineering, Computational Cardiac Modeling
2025-04-17		Reproducible Digital Twins in Pharmacokinetics Matthias König 9th Disease Maps Community Meeting (DMCM2025)
2025-02-05		Reproducible digital twins for personalized drug pharmacokinetics Matthias König Disease Maps Meeting
2025-02-05		Reproducible digital twins for personalized liver function assessment Matthias König University of Darmstadt, Institute for Mechanics, Institute Seminar
2024-09-02		Reproducible digital twins for personalized liver function assessment Matthias König COMBINE 2024 Stuttgart
2023-10-10		Reproducible digital twins for personalized liver function assessment Matthias König e:Med Meeting 2023 on Systems Medicine
2023-10-10		Reproducible digital twins for personalized liver function assessment Matthias König Institute for Theoretical Biology Meeting
2023-09-22		Studying the impact of drug metabolism on the liver tissue: An integrated biomechanical modeling approach Matthias König, Steffen Gerhäusser, Luis Mandl, Lena Lambers, Uta Dahmen, Hans-Michael Tautenhahn, Tim Ricken X International Conference on Computational Bioengineering
2023-09-01		Digital twins for liver function & metabolic phenotyping Matthias König AstraZeneca seminar
2023-06-19		Advancing Liver Function Assessment: Personalized and Stratified Approaches with Standardized Computational Models and Data Matthias König Workshop on Computational Models in Biology and Medicine 2023
2023-05-22		Digital twins for liver function & metabolic phenotyping Matthias König Workshop on Modelling in Biology and Medicine
2022-07-22		Developing computational models with SBML - sbmlutils & cy3sbml Matthias König CRBM Network Modeling Virtual Symposium

2026-05-04		Modelling of Patient-Specific Liver Vasculature and Sorafenib Pharmacokinetics in Hepatocellular Carcinoma Mohamed Albadry1,2, Matthias König3,4, Fangcong Li1, Karl-Heinz Herrmann5, Wan-Ting Zhao5, Weiwei Wei1,6, Joanna Kosacka1,7, Xin Pei1, FengMing Xu1,8,9, Mohamed I. A Hassan1, Michael Kiehntopf10, Amelie Lupp11, Michael Böttcher12, Jasna Neumann12, Sebastian Höpfl13, Nicole Radde13,14, Olaf Dirsch15, Utz Settmacher1,6, Jürgen R. Reichenbach3, Hans-Michael Tautenhahn1,16, Uta Dahmen1 1Experimental Transplantation Surgery, Department of General, Visceral and Vascular Surgery, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany; 2Department of Pathology, Faculty of Veterinary Medicine, Menoufia University, Shebin El Kom, Egypt; 3Institute of Structural Mechanics and Dynamics in Aerospace Engineering, University of Stuttgart, Stuttgart, Germany; 4Institute for Biology, Faculty of Life Science, Humboldt-Universität zu Berlin, Berlin, Germany; 5Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany; 6Department of General, Visceral and Vascular Surgery, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany; 7Department of Neurology, University of Leipzig, Leipzig, Germany; 8Department of Infectious Diseases, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou 310006, China; 9Else Kröner Graduate School for Medical Students “JSAM”, Jena University Hospital, Jena, Germany; 10Department of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany; 11Institute of Pharmacology and Toxicology, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany; 12MVZ Medizinische Labore Dessau Kassel GmbH, Bauhüttenstraße 6, 06847, Dessau-Roßlau, Germany; 13Institute for Systems Theory and Automatic Control, Faculty of Engineering Design, Production Engineering and Automotive Engineering, University of Stuttgart, Stuttgart, Germany; 14Institute for Stochastics and Applications, University of Stuttgart, Stuttgart, Germany; 15BG Klinikum Unfallkrankenhaus Berlin, Institute of Pathology, Berlin, Germany; 16Department of Visceral, Transplantation, Thoracic and Vascular Surgery, University of Leipzig Medical Center, Leipzig, Germany SBMC 2026: 10th Conference on Systems Biology of Mammalian Cells Background: Liver function relies on the balance between blood flow distribution and cellular resilience. While ischemia and perfusion are often studied separately, their combined contribution to multi-scale liver adaptation remains poorly understood. This study applies a systems-level approach to link macro-hemodynamics with cellular responses. Methods: Two complementary models were used to investigate distinct system drivers. (1) In vivo, portal vein ligation (PVL) generated intra-organ perfusion gradients. Regional adaptation was assessed by MRI-based perfusion, volumetry, proliferation (Ki67), cytochrome P450 expression, and drug elimination kinetics. (2) Ex vivo, normothermic machine perfusion (NMP) was performed under standardized flow conditions to evaluate the impact of different ischemic durations, assessing bile production, HMGB1 release, and markers of cellular homeostasis. Results: PVL induced divergent regional responses: ligated lobes exhibited hypoperfusion, atrophy, and reduced proliferation, whereas non-ligated lobes showed hyperperfusion, hypertrophy, and increased proliferation. These structural changes were accompanied by distinct alterations in cytochrome P450 expression and corresponding differences in drug elimination. In NMP, functional recovery depended on ischemic burden despite comparable flow conditions. Moderate ischemia (30 min) was associated with adaptive response and preserved bile production, whereas severe ischemia (50 min) resulted in impaired function and increased HMGB1 release. Preliminary data suggest a link between these transitions and autophagic activity. Conclusion: Liver adaptation can be conceptualized along two interacting axes: a spatial axis driven by perfusion redistribution and a temporal axis defined by ischemic burden. Integrating these models provides a framework linking structural remodeling and functional resilience, with autophagy as a potential regulatory node. Keywords: liver, perfusion,
2025-02-21		Modelling of Patient-Specific Liver Vasculature and Sorafenib Pharmacokinetics in Hepatocellular Carcinoma Mariia Myshkina1, Etienne Jessen2, Dominik Schillinger2, Matthias König1,3 1 Department of Biology, Faculty of Life Sciences, Humboldt-Universität zu Berlin, Germany; 2 Institute for Mechanics, Computational Mechanics Group, Technical University of Darmstadt, Darmstadt, Germany; 3 Institute of Structural Mechanics and Dynamics in Aerospace Engineering, University of Stuttgart, Stuttgart, Germany EASL Liver Cancer Summit 2026 Background and Aims: Liver cancer is the second leading cause of cancer-related deaths. Despite the various therapeutic options for hepatocellular carcinoma (HCC) treatment, selecting patient-specific therapy remains challenging. A major challenge is predicting the distribution and heterogeneity of anti-cancer medication in the liver due to factors such as liver anatomy, vascular topology, perfusion and tumour location. In this study, we applied a recently published algorithm [1] to generate vessel trees within a defined liver volume and modelled the spatio-temporal pharmacokinetics of the multi-kinase inhibitor sorafenib (NEXAVAR®) within the liver. Our objectives were: (i) to generate physiologically realistic arterial, portal, venous, and biliary vessel trees in a given liver volume; (ii) to develop a mechanistic pharmacokinetic model for substance transport in these trees; (iii) to couple this model with a physiologically based pharmacokinetic (PBPK) model of sorafenib; and (iv) to simulate drug concentration dynamics within the liver. Methods: Substance transport along the vessel and biliary trees was modelled using ordinary differential equations. Each terminal segment of the trees was associated with a terminal liver volume, representing the hepatic tissue supplied by individual terminal arterial, portal, venous, and biliary segments. In each terminal volume, the local sorafenib metabolism and biliary excretion were modelled. Model performance was evaluated using published pharmacokinetic data. Results: The algorithm successfully generated physiologically realistic, non-intersecting arterial, portal, venous, and biliary trees within the liver volume. The surrogate mechanistic–PBPK model reproduced published pharmacokinetic data for sorafenib and enabled spatially resolved predictions of drug concentrations along the vascular and biliary trees and within liver tissue. Simulations revealed that the time to reach maximum sorafenib concentration in liver tissue was directly related to proximity to the start of inflow trees and inversely to proximity to the end of outflow trees. These results underscore the influence of the liver anatomy, its vascularisation topology and target location on intrahepatic drug exposure, suggesting that individualised dosing strategies could enhance therapeutic response in HCC. Conclusion: The established workflow for simulating the spatial distribution and heterogeneity of anti-cancer medication in a given liver anatomy can provide important information for individual HCC treatment planning. References [1] Jessen E, Steinbach MC, Debbaut C, Schillinger D (2022). Rigorous mathematical optimization of synthetic hepatic vascular trees. Journal of The Royal Society Interface 19:20220087. doi: 10.1098/rsif.2022.0087 [2] Okibedi Frances, & König, Matthias. (2023). Physiologically based pharmacokinetic (PBPK) model of sorafenib. Zenodo. https://doi.org/10.5281/zenodo.10432855 Keywords: pharmacokinetics, sorafenib, vessel trees,
2025-07-07		A Physiologically Based Pharmacokinetic and Pharmacodynamic Model of Lixisenatide Olivia Yau2, Matthias König1 1Humboldt-Universität zu Berlin, Institute for Theoretical Biology, Berlin, Germany, 2University of Toronto, Dept. of Pharmacology and Toxicology, Toronto, Canada HIC conference 2025, Humboldt Internship Program Day, Berlin, 7 July 2025 This project leverages an open pharmacokinetics database, along with established data curation and model simulation protocols, to develop a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model for the GLP-1 receptor agonist lixisenatide. Since type 2 diabetes mellitus (T2DM) is often accompanied by liver and renal impairments, obesity, and cardiovascular disease, this study aims to assess how these factors influence drug behavior. By developing a PBPK/PD model, we aim to establish a tool to support personalized medicine of T2DM management. Keywords: pharmacokinetics, pharmacodynamics, lixisenatide, GLP-1 agonists,
2025-07-07		A Physiologically Based Pharmacokinetic Model of Dulaglutide Kim Minjun2, Matthias König1 1Humboldt-Universität zu Berlin, Institute for Theoretical Biology, Berlin, Germany, 2National University of Singapore, Singapore HIC conference 2025, Humboldt Internship Program Day, Berlin, 7 July 2025 This Humboldt Internship project develops a physiologically based pharmacokinetic (PBPK) model of dulaglutide, a GLP-1 receptor agonist. The objective of this project is to enhance our understanding of dose-dependency of systemic exposure to dulaglutide, and the different underlying causes of intraindividual variability in efficacy of diabetes treatment with dulaglutide. Keywords: pharmacokinetics, pharmacodynamics, dulaglutide, GLP-1 agonists,
2025-07-07		A Physiologically-Based Pharmacokinetic and Pharmacodynamic Model of Liraglutide Isabella Tan2, Matthias König1 1Humboldt-Universität zu Berlin, Institute for Theoretical Biology, Berlin, Germany, 2University of Toronto, Dept. Pharmacology & Biomedical Toxicology, Toronto, Canada HIC conference 2025, Humboldt Internship Program Day, Berlin, 7 July 2025 Liraglutide, known commercially as Victoza(R), is a Glucagon-Like Peptide 1 (GLP-1) agonist used in the treatment of type 2 diabetes and obesity. The objective of this study is to develop a physiologically-based pharmacokinetic/pharmacodynamic (PBPK/PD) model of liraglutide. Through this study, the aim is to develop a better understanding of liraglutide pharmacology and improve personalized medicine approaches. Keywords: pharmacokinetics, pharmacodynamics, liraglutide, GLP-1 agonists,
2024-11-05		Multi-scale Modelling of Liver Perfusion and Function Matthias König1 1Humboldt-Universität zu Berlin, Faculty of Life Science, Institute for Biology, Systems Medicine of the Liver, Berlin, Germany Qualiperf 2 Defense, 5 November 2024 Hypothesis: Computational modelling of 3D spatial heterogeneity of perfusion & function will significantly improve functional assessment of the liver. Contribution: A multi-scale model of liver 3D perfusion & function heterogeneity. Keywords: pharmacokinetics, pharmacodynamics, digital twin, liver, perfusion, function,
2024-11-05		Data Management Project Matthias König1, Hans-Michael Tautenhahn2 1Humboldt-Universität zu Berlin, Faculty of Life Science, Institute for Biology, Systems Medicine of the Liver, Berlin, Germany 2Department of Visceral, Transplantation, Thoracic and Vascular Surgery, Universitätsklinikum Leipzig Qualiperf 2 Defense, 5 November 2024 Central data management project. Keywords: data management, FAIR,
2024-07-18		PK-LLM : Large Language Model (LLM) for Pharmacokinetic (PK) Data Curation Prerna Parakkat2, Matthias König1 1Humboldt-University of Berlin, Institute for Theoretical Biology, Berlin, Germany, 2Vellore Institute of Technology, Chennai, India HIC conference 2024, Humboldt Internship Program Day, Berlin, 18 July 2024 Our group has developed PK-DB, an open pharmacokinetics database from clinical and preclinical research. The aim of this Humboldt Internship project is to use Large Language Models (LLM) to support effective data curation for PK-DB from scientific pharmacokinetic literature. Keywords: LLM, large language models, pharmacometrics, pharmacokinetics,
2024-07-18		Canagliflozin Vera Tereshchuk1, Matthias König2 1Moscow Institute of Physics and Technology, 2Humboldt-University of Berlin, Institute for Theoretical Biology, Berlin, Germany HIC conference 2024, Humboldt Internship Program Day, Berlin, 18 July 2024 In this project, we are developing a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model of the SGLT2 inhibitor canagliflozin. The aim is to improve our understanding of intra-individual variability in diabetes treatment with SGLT2 inhibitors, e.g. differences in hepatorenal function. Keywords: canagliflozin, pharmacometrics,
2024-07-18		A physiologically based pharmacokinetic model of morphine Deepa Maheshvare M.2, Rohini Chakraborty2, Rohit Chakraborty2, Matthias König1 2Humboldt-University of Berlin, Institute for Theoretical Biology, Berlin, Germany, 2Indian Institute of Science, Bengaluru, India HIC conference 2024, Humboldt Internship Program Day, Berlin, 18 July 2024 This Humboldt Internship project develops a physiologically based pharmacokinetic (PBPK) model of the pain medication morphine. The objective is to enhance our understanding of how underlying causes of intraindividual variability in morphine treatment, e.g., differences in absorption rates or hepatorenal function. Keywords: morphine, pharmacometrics,
2024-06-26		Captopril in Focus: Establishing an Open Pharmacokinetic Dataset and PBPK Modeling Mariia Myshkina1, Matthias König1 1Humboldt-University of Berlin, Institute for Theoretical Biology, Berlin, Germany PAGE2024 - Population Approach Group Europe, Rome, 26-28 June 2024 Introduction: Angiotensin-converting enzyme (ACE) inhibitors, such as captopril, are widely prescribed for the treatment of hypertension and heart failure. Captopril, the first ACE inhibitor developed in the 1980s, is primarily taken orally and is rapidly absorbed, reaching peak plasma concentrations within an hour. Its half-life is approximately 2 hours, but several factors, including renal function, heart disease, age and sex, can affect its pharmacokinetics. Despite the widespread use of captopril, comprehensive pharmacokinetic data have been lacking. Our group has developed PK-DB (https://pk-db.com) [1], an open database containing high-quality pharmacokinetic data from clinical and preclinical research. PK-DB includes patient cohort characteristics, interventions, concentration-time profiles, and kinetic parameters, with the ability to automatically calculate pharmacokinetic parameters using non-compartmental methods. Objectives: The objectives of this study were to curate and analyze captopril pharmacokinetic data, expand the PK-DB, develop a whole-body physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model of captopril in accordance with FAIR principles [2], and improve understanding of the intra-individual variability in captopril pharmacokinetics influenced by factors such as age, sex, renal and cardiac function. Methods: Over 600 publications on captopril pharmacokinetics were reviewed through a systematic literature search, with a subset selected for data curation in PK-DB. The PBPK model was developed using a compartmental approach and encoded in Systems Biology Markup Language (SBML) [3] for accessibility and reproducibility. Results: A comprehensive set of captopril pharmacokinetic data was generated from 15 clinical studies in healthy volunteers and patients with renal impairment, heart failure and hypertension. The PBPK model includes four major compartments (blood, intestine, liver, kidney) and describes absorption, distribution, metabolism and excretion. It successfully represents the pharmacokinetic profile of captopril in different age groups, showing minimal age-related differences in unchanged drug concentration. Heart failure did not significantly affect maximum plasma concentration or area under the curve (AUC), but renal function strongly influenced captopril elimination. We present this data set and open PBPK model of captopril as a valuable resource for further research. Conclusions: This study successfully establishes a freely accessible, comprehensive dataset and an open PBPK model of captopril, enhancing our understanding of its pharmacokinetic behavior across different patient groups. Our findings emphasize the significance of renal function in captopril elimination and provide a valuable resource for personalized medicine approaches in hypertension and heart failure treatment. References: [1] Grzegorzewski, J. et al. 2021. PK-DB: pharmacokinetics database for individualized and stratified computational modeling. Nucleic Acids Research. 49, D1 (Jan. 2021), D1358–D1364. DOI:https://doi.org/10.1093/nar/gkaa990. [2] Wilkinson, M.D. et al. 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. 3, (Mar. 2016), 160018. DOI:https://doi.org/10.1038/sdata.2016.18. [3] Keating, SM. et al, SBML Level 3: an extensible format for the exchange and reuse of biological models. Mol Syst Biol. 2020 Aug;16(8):e9110. doi: 10.15252/msb.20199110. Keywords: captopril, pharmacometrics,
2010-06-01		Blood glucose control by the human hepatocyte Matthias König1, Sascha Bulik1, Hermann-Georg Holzhütter1 1Charité University Medicine Berlin, Insitute of Biochemistry, Berlin, Germany Spetses 2010 Introduction: Plasma glucose levels are tightly controlled to ensure a constant glucose supply and to avoid toxic effects of hyperglycemic conditions. The liver is the central organ of glucose homeostasis and the main glucose producer (hepatic glucose production HGP), but also utilizes glucose for biosyntheses and storage in fatty acids (hepatic glucose utilization HGU). Results: We present the first detailed kinetic model of the human hepatocyte glucose metabolism [Fig.1] which comprises allosteric regulation as well as hormonal regulation by insulin and glucagon via inter-convertible enzymes [Fig.2]. The model reproduces fundamental features of hepatic glucose metabolism like glucose dependent switch between HGP and HGU [Fig.3] observed changes in glucose homeostasis in diabetes II [Fig.4] dependency of HGP on gluconeogenic substrates (lactate). Outlook: Possible future applications of the model are analysis of hepatic effects of various diabetic treatments simulations of the influence of temporary changes in the gene expression on the glucose homeostasis (for example circadian rhythms of gene expression). Keywords: glucose, modelling,