Overview and Digital Twins
The overall goal of our group is to develop, test, and apply medical digital twins.
Our medical digital twins are computer copies of a person. In other words, just like a normal monozygotic twin, your medical digital twin looks like you, on the outside, and has a similar physiology on the inside.
We have built up these medical digital twins, by modeling all of the main organs in the human body. These models are primarily mechanistic models, which describes the processes happening inside the organs, and inside the cells.
We have also developed an approach to integrate all of these organ models into an interconnected whole-body model. In other words, our models are multi-level, ranging from the whole-body level to the intracellular molecular level. Our digital twins are also multi-timescale, because they can simulate processes from the range of ms (e.g. action potentials in neurons) to years (e.g. disease progression). Finally, our digital twins are personalized, i.e. we use person-specific data to continuously update the digital twins to a specific person, as he/she is at a given time.
These digital twins can be used for a variety of purposes, e.g. in medicine, drug development, education, entertainment, defense, etc, and we are pursuing all of these applications, to various extent.
How we develop, test, and make use of our digital twins
Pre-clinical studies to test cellular and organ models
COMING SOON
Applications in end-usage areas
COMING SOON
Key References
- Overview of some of the key publications for the different organ models, for how we connect the models into a whole-body multi-organ model, and for how we personalize the models into digital twins for specific individuals.
Belén Casas, Jonas Lantz, Federica Viola, Gunnar Cedersund, Ann F Bolger, Carl-Johan Carlhäll, Matts Karlsson, Tino Ebbers (2017).“Bridging the gap between measurements and modelling: a cardiovascular functional avatar”,Sci Rep,7(1):6214.
Belén Casas, Federica Viola, Gunnar Cedersund, Ann F Bolger, Matts Karlsson, Carl-Johan Carlhäll, Tino Ebbers (2018).“Uncertainty in cardiovascular digital twins despite non-normal errors in 4D flow MRI: Identifying reliable biomarkers such as ventricular relaxation rate”,Front Physiol,9:1515.
Kajsa Tunedal, Federica Viola, Belén Casas Garcia, Ann Bolger, Fredrik H Nyström, Carl Johan Östgren, Jan Engvall, Peter Lundberg, Petter Dyverfeldt, Carl-Johan Carlhäll, Gunnar Cedersund, Tino Ebbers (2023).“Haemodynamic effects of hypertension and type 2 diabetes: Insights from a 4D flow MRI-based personalized cardiovascular mathematical model”,J Physiol,601(17):3765-3787.
Kajsa Tunedal, Tino Ebbers, Gunnar Cedersund (2025).“Uncertainty in cardiovascular digital twins despite non-normal errors in 4D flow MRI: Identifying reliable biomarkers such as ventricular relaxation rate”,Comput Biol Med,188:109878.
Mikael Fredrik Forsgren, Olof Dahlqvist Leinhard, Nils Dahlström, Gunnar Cedersund, Peter Lundberg (2014)."Physiologically realistic and validated mathematical liver model reveals [corrected] hepatobiliary transfer rates for Gd-EOB-DTPA using human DCE-MRI data".PLoS One,9(4):e95700.
Mikael Fredrik Forsgren, Markus Karlsson, Olof Dahlqvist Leinhard, Nils Dahlström, Bengt Norén, Tobias Romu, Simone Ignatova, Mattias Ekstedt, Stergios Kechagias, Peter Lundberg, Gunnar Cedersund (2019)."Model-inferred mechanisms of liver function from magnetic resonance imaging data: Validation and variation across a clinically relevant cohort.".PLoS Comput Biol.,15(6):e1007157.
Henrik Podéus, Christian Simonsson, Patrik Nasr, Mattias Ekstedt, Stergios Kechagias, Peter Lundberg, William Lövfors, Gunnar Cedersund (2024)."A physiologically-based digital twin for alcohol consumption-predicting real-life drinking responses and long-term plasma PEth".NPJ Digit Med.,7(1):112.
Karin Lundengård, Gunnar Cedersund, Sebastian Sten, Felix Leong, Alexander Smedberg, Fredrik Elinder, Maria Engström (2016)."Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI.".PLoS Comput Biol.,12(6):e1004971.
Sebastian Sten, Henrik Podéus, Nicolas Sundqvist, Fredrik Elinder, Maria Engström, Gunnar Cedersund (2023)."A quantitative model for human neurovascular coupling with translated mechanisms from animals".PLoS Comput Biol.,19(1):e101081.
Nicolas Sundqvist, Henrik Podéus, Sebastian Sten, Maria Engström, Salvador Dura-Bernal, Gunnar Cedersund, (2024).“A Model-Driven Meta-Analysis Supports the Emerging Consensus View that Inhibitory Neurons Dominate BOLD-fMRI Responses”,bioRxiv [Preprint],17:2024.10.15.618416.
Cecilia Brännmark, Robert Palmér, S Torkel Glad, Gunnar Cedersund, Peter Strålfors (2010).“Mass and information feedbacks through receptor endocytosis govern insulin signaling as revealed using a parameter-free modeling framework”,J Biol Chem.,285(26):20171-9.
Cecilia Brännmark, Elin Nyman, Siri Fagerholm, Linnéa Bergenholm, Eva-Maria Ekstrand, Gunnar Cedersund, Peter Strålfors (2013).“Insulin signaling in type 2 diabetes: experimental and modeling analyses reveal mechanisms of insulin resistance in human adipocytes”,J Biol Chem.,288(14):9867-9880.
Elin Nyman, Meenu Rohini Rajan, Siri Fagerholm, Cecilia Brännmark, Gunnar Cedersund, Peter Strålfors (2014).“A single mechanism can explain network-wide insulin resistance in adipocytes from obese patients with type 2 diabetes”,J Biol Chem.,289(48):33215-30.
Gunnar Cedersund (2006)."Elimination of the initial value parameters when identifying a system close to a Hopf bifurcation", Syst Biol (Stevenage),153(6):448-56.
R Palmér, E Nyman, M Penney, A Marley, G Cedersund, B Agoram (2014)."Effects of IL-1β-Blocking Therapies in Type 2 Diabetes Mellitus: A Quantitative Systems Pharmacology Modeling Approach to Explore Underlying Mechanisms", CPT Pharmacometrics Syst Pharmacol.,3(6):e118
Rasmus Magnusson, Guido Pio Mariotti, Mattias Köpsén, William Lövfors, Danuta R Gawel, Rebecka Jörnsten, Jörg Linde, Torbjörn E M Nordling, Elin Nyman, Sylvie Schulze, Colm E Nestor, Huan Zhang, Gunnar Cedersund, Mikael Benson, Andreas Tjärnberg, Mika Gustafsson (2017)."LASSIM-A network inference toolbox for genome-wide mechanistic modeling", PLoS Comput Biol.,13(6):e1005608.
Elin Nyman, Maria Lindh, William Lövfors, Christian Simonsson, Alexander Persson, Daniel Eklund, Erica Bäckström, Markus Fridén, Gunnar Cedersund G. (2020)." Mechanisms of a Sustained Anti-inflammatory Drug Response in Alveolar Macrophages Unraveled with Mathematical Modeling", CPT Pharmacometrics Syst Pharmacol.,9(12):707-717.
Niloofar Nikaein, Kedeye Tuerxun, Gunnar Cedersund, Daniel Eklund, Robert Kruse, Eva Särndahl, Eewa Nånberg, Antje Thonig, Dirk Repsilber, Alexander Persson, Elin Nyman; X-HiDE Consortium. (2023)."Mathematical models disentangle the role of IL-10 feedbacks in human monocytes upon proinflammatory activation", J Biol Chem.,299(10):105205.