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HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles

Overview
Description:

The central objective of HaematoOpt project is to demonstrate that recently developed dynamic mathematical models of normal and leukemic hematopoiesis can be used to practically impact clinical decision- making

Programme: This Project is not associated with a Programme

Health Atlas ID: 7RRNQ9WC7J-9

Funding codes:
  • BMBF

Public web page: https://haematoopt.de/

Organisms: No Organisms specified

Human Diseases: Non-hodgkin lymphoma

Health Atlas PALs: Markus Scholz

Project Coordinators: No Project coordinators for this Project

Project created: 8th May 2019

Project Hierarchy

Related items

Modeling individual time courses of thrombopoiesis during multi-cyclic chemotherapy.
Genetical Statistics and Systems Biology, HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles

Abstract (Expand)

BACKGROUND: Thrombocytopenia is a major side-effect of cytotoxic cancer therapies. The aim of precision medicine is to develop therapy modifications accounting for the individual's risk. … METHODOLOGY/PRINCIPLE FINDINGS: To solve this task, we develop an individualized bio-mechanistic model of the dynamics of bone marrow thrombopoiesis, circulating platelets and therapy effects thereon. Comprehensive biological knowledge regarding cell differentiation, amplification, apoptosis rates, transition times and corresponding regulations are translated into ordinary differential equations. A model of osteoblast/osteoclast interactions was incorporated to mechanistically describe bone marrow support of quiescent cell stages. Thrombopoietin (TPO) as a major regulator is explicitly modelled including pharmacokinetics and-dynamics of TPO injections. Effects of cytotoxic drugs are modelled by transient depletions of proliferating cells. To calibrate the model, we used population data from the literature and close-meshed individual data of N = 135 high-grade non-Hodgkin's lymphoma patients treated with CHOP-like chemotherapies. To limit the number of free parameters, several parsimony assumptions were derived from biological data and tested via Likelihood methods. Heterogeneity of patients was explained by a few model parameters. The over-fitting issue of individual parameter estimation was successfully dealt with a virtual participation of each patient in population-based experiments. The model qualitatively and quantitatively explains a number of biological observations such as the role of osteoblasts in explaining long-term toxic effects, megakaryocyte-mediated feedback on stem cells, bi-phasic stimulation of thrombopoiesis by TPO, dynamics of megakaryocyte ploidies and non-exponential platelet degradation. Almost all individual time series could be described with high precision. We demonstrated how the model can be used to provide predictions regarding individual therapy adaptations. CONCLUSIONS: We propose a mechanistic thrombopoiesis model of unprecedented comprehensiveness in both, biological mechanisms considered and experimental data sets explained. Our innovative method of parameter estimation allows robust determinations of individual parameter settings facilitating the development of individual treatment adaptations during chemotherapy.

Authors: Y. Kheifetz, M. Scholz

Date Published: 7th Mar 2019

Publication Type: Not specified

Human Diseases: blood platelet disease

Model-based individual managing of thrombocytopenia during multi-cyclic chemotherapy
HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles

Abstract (Expand)

Background: Thrombocytopenia is a major side-effect of cytotoxic cancer therapies. The aim of precision medicine is to develop therapy modifications accounting for the individual’s risk. Methodology/Principle … Findings: To solve this task, we develop an individualized bio-mechanistic model of the dynamics of bone marrow thrombopoiesis, circulating platelets and therapy effects thereon. Comprehensive biological knowledge regarding cell differentiation, amplification, apoptosis rates, transition times and corresponding regulations are translated into ordinary differential equations. A model of osteoblast/osteoclast interactions was incorporated to mechanistically describe bone marrow support of quiescent cell stages. Thrombopoietin (TPO) as a major regulator is explicitly modelled including pharmacokinetics and –dynamics of TPO injections. Effects of cytotoxic drugs are modelled by transient depletions of proliferating cells. To calibrate the model, we used population data from the literature and close-meshed individual data of N=135 high-grade non-Hodgkin’s lymphoma patients treated with CHOP-like chemotherapies. To limit the number of free parameters, several parsimony assumptions were derived from biological data and tested via Likelihood methods. Heterogeneity of patients was explained by a few model parameters. The over-fitting issue of individual parameter estimation was successfully dealt with a virtual participation of each patient in population-based experiments. The model qualitatively and quantitatively explains a number of biological observations such as the role of osteoblasts in explaining long-term toxic effects, megakaryocyte-mediated feedback on stem cells, bi-phasic stimulation of thrombopoiesis by TPO, dynamics of megakaryocyte ploidies and non-exponential platelet degradation. Almost all individual time series could be described with high precision. We demonstrated how the model can be used to provide predictions regarding individual therapy adaptations. Conclusions: We propose a mechanistic thrombopoiesis model of unprecedented comprehensiveness in both, biological mechanisms considered and experimental data sets explained. Our innovative method of parameter estimation allows robust determinations of individual parameter settings facilitating the development of individual treatment adaptations during chemotherapy.

Authors: Y. Kheifetz, Markus Scholz, Markus Löffler

Date Published: 9th Jun 2017

Publication Type: Not specified

Human Diseases: thrombocytopenia

A biomathematical model of human thrombopoiesis under chemotherapy.
HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles

Abstract (Expand)

Intensification of cytotoxic chemotherapy enhances the outcome of several malignancies but is limited by haematotoxicity. While neutropenia and anaemia can be treated with supportive growth factor … applications, thrombocytopenia remains a dose-limiting side effect due to the lack of clinically approved pharmaceutical growth factors. Hence, it is necessary to assess the degree of thrombocytopenia of newly designed intensified regimens in the planning phase of a clinical trial. We present a simple ordinary differential equations model of thrombopoiesis under chemotherapy which maps the dynamics of stem cells, CFU-Mk, megakaryocytes and platelets in spleen and circulation. Major regulatory cytokine of thrombopoiesis is thrombopoietin (TPO) whose production and consumption is explicitly modelled. TPO acts by increasing the number of mitoses of CFU-Mk and increasing the mass and maturation of megakaryocytes. Chemotherapy is modelled by a drug-dose and cell-stage specific acute cell loss. Most of the cell kinetic parameters of the model were taken from literature. Parameters regarding TPO regulation and chemotherapy toxicity were estimated by fitting the predictions of the model to time series data of platelets received from large clinical data sets of patients under seven different chemotherapies. We obtained a good agreement between model and data for all scenarios. Parameter estimates were biologically plausible throughout. For validation, the model also explains data of TPO and platelet dynamics after thrombopheresis taken from literature. We used the model to make clinically relevant predictions. Regarding thrombocytopenia we estimated that the CHOP regimen for the treatment of high-grade non-Hodgkin's lymphoma can be time-intensified to a cycle duration of 12 days while the time-intensified CHOEP regimen would result in severe cumulative toxicity. We conclude that our proposed model proved validity for both, different chemotherapeutic regimens and thrombopheresis as well. It is useful to assess the thrombocytopenic risk in the planning phase of a clinical trial.

Authors: M. Scholz, A. Gross, M. Loeffler

Date Published: 21st May 2010

Publication Type: Not specified

Shiny App for managing next-cycle thrombopenia
HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles

Implementation of recently developed dynamic mathematical models of normal and leukemic hematopoiesis to practically impact clinical decision- making.

Fitting available individual patients information, prediction of next-cycle thrombopenia caused by CHOEP treatment based on the individual fits of the preceeding treatment cycles, changing next-cycle relative dosing, posponement of the next cycle, changing follow-up period, visualization of data and simulation

Creator: Markus Scholz

Submitter: René Hänsel

René Hänsel adminproject_administratorasset_housekeeperasset_gatekeeperprogramme_administrator

Projects: LHA - Leipzig Health Atlas, LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, LIFE HNC - Head and Neck Cancer Group, LIFE Heart, MMML - Molecular mechanisms in malignant lymphoma, GLA - German Lymphoma Alliance, MMML Demonstrators - Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine, HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles, GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer, GC-HNPCC - German Consortium for Hereditary Non-Polyposis Colorectal Cancer, MMML-MYC-SYS, NLP4CR - Natural Language Processing for Clinical Research, Genetical Statistics and Systems Biology, SepNet - German Competence Network Sepsis, LIFE Child, HNPCC-Sys - Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome, GGN - German Glioma Network, CAPSys - Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome, ProstataCA, SMITH - Smart Medical Information Technology for Healthcare, COVID-19 Leipzig, Management of health information systems

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

https://orcid.org/0000-0001-8344-0658
Markus Scholz palproject_administrator

Projects: HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles, LIFE Heart, LIFE - Leipzig Research Center for Civilization Diseases, Genetical Statistics and Systems Biology, COVID-19 Leipzig

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

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