title: Merging concepts - coupling an agent-based model of hematopoietic stem cells with an ODE model of granulopoiesis.
abstract: BACKGROUND
  Hematopoiesis is a complex process involving different cell types and feedback mechanisms mediated by cytokines. This complexity stimulated various models with different scopes and applications. A combination of complementary models promises to provide their mutual confirmation and to explain a broader range of scenarios. Here we propose a combination of an ordinary differential equation (ODE) model of human granulopoiesis and an agent-based model (ABM) of hematopoietic stem cell (HSC) organization. The first describes the dynamics of bone marrow cell stages and circulating cells under various perturbations such as G-CSF treatment or chemotherapy. In contrast to the ODE model describing cell numbers, our ABM focuses on the organization of individual cells in the stem population.
  
  
  RESULTS
  We combined the two models by replacing the HSC compartment of the ODE model by a difference equation formulation of the ABM. In this hybrid model, regulatory mechanisms and parameters of the original models were kept unchanged except for a few specific improvements: (i) Effect of chemotherapy was restricted to proliferating HSC and (ii) HSC regulation in the ODE model was replaced by the intrinsic regulation of the ABM. Model simulations of bleeding, chronic irradiation and stem cell transplantation revealed that the dynamics of hybrid and ODE model differ markedly in scenarios with stem cell damage. Despite these differences in response to stem cell damage, both models explain clinical data of leukocyte dynamics under four chemotherapy regimens.
  
  
  CONCLUSIONS
  ABM and ODE model proved to be compatible and were combined without altering the structure of both models. The new hybrid model introduces model improvements by considering the proliferative state of stem cells and enabling a cell cycle-dependent effect of chemotherapy. We demonstrated that it is able to explain and predict granulopoietic dynamics for a large variety of scenarios such as irradiation, bone marrow transplantation, chemotherapy and growth factor applications. Therefore, it promises to serve as a valuable tool for studies in a broader range of clinical applications, in particular where stem cell activation and proliferation are involved.
authors.affiliation: Institute for Medical Informatics and Biometry, TU Dresden, Blasewitzer str, 86, D-01307 Dresden, Germany. axel.krinner@tu-dresden.de.
authors.forename: Axel
authors.initials: A
authors.lastname: Krinner
authors.forename: Ingo
authors.initials: I
authors.lastname: Roeder
authors.forename: Markus
authors.initials: M
authors.lastname: Loeffler
authors.forename: Markus
authors.initials: M
authors.lastname: Scholz
mesh_terms: D016026:Bone Marrow Transplantation; D006098:Granulocytes / Q000166:cytology* / Q000187:drug effects; D006410:Hematopoiesis / Q000187:drug effects; D006412:Hematopoietic Stem Cells / Q000166:cytology* / Q000187:drug effects; D006801:Humans; D008954:Models, Biological