A Systems Pharmacology Model for Predicting Effects of Factor Xa Inhibitors in Healthy Subjects: Assessment of Pharmacokinetics and Binding Kinetics

Zhou, Xiao‐Yang; Huntjens, Drh; Gilissen, Rahj

doi:10.1002/psp4.12035

Cited by 12 publications

(16 citation statements)

References 46 publications

(90 reference statements)

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“…The current model allows for the simulation of several individual clotting factor concentrations under VKA, enoxaparin, and rivaroxaban treatment. In contrast to other recently published systems pharmacology models of the coagulation network, this work presents the first attempt to estimate parameters of the coagulation network using individual clotting factor concentrations from TDM data.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Systems Pharmacology Model to Predict the Effects of Commonly Used Anticoagulants on the Human Coagulation Network

Hartmann

Biliouris

et al. 2016

CPT Pharmacometrics Syst. Pharmacol.

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Warfarin is the anticoagulant of choice for venous thromboembolism (VTE) treatment, although its suppression of the endogenous clot‐dissolution complex APC:PS may ultimately lead to longer time‐to‐clot dissolution profiles, resulting in increased risk of re‐thrombosis. This detrimental effect might not occur during VTE treatment using other anticoagulants, such as rivaroxaban or enoxaparin, given their different mechanisms of action within the coagulation network. A quantitative systems pharmacology model was developed describing the coagulation network to monitor clotting factor levels under warfarin, enoxaparin, and rivaroxaban treatment. The model allowed for estimation of all factor rate constants and production rates. Predictions of individual coagulation factor time courses under steady‐state warfarin, enoxaparin, and rivaroxaban treatment reflected the suppression of protein C and protein S under warfarin compared to rivaroxaban and enoxaparin. The model may be used as a tool during clinical practice to predict effects of anticoagulants on individual clotting factor time courses and optimize antithrombotic therapy.

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Section: Discussionmentioning

confidence: 99%

Quantitative Systems Pharmacology Model to Predict the Effects of Commonly Used Anticoagulants on the Human Coagulation Network

Hartmann

Biliouris

et al. 2016

CPT Pharmacometrics Syst. Pharmacol.

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“…Sensitivity Analysis. A local SA evaluating the change in steadystate levels of each of the ILs as a function of variations in the model parameters was performed in MATLAB version R2018b, using the complex-step approximation method (Zhou et al, 2015;MATLAB, 2018). The integrals of the fully normalized time-dependent sensitivities from day 0 to day 28 were computed and reported as a heatmap.…”

Section: Capturing Behaviormentioning

confidence: 99%

A Quantitative Systems Pharmacology Model for the Key Interleukins Involved in Crohn's Disease

Balbas-Martinez

Asín-Prieto

Parra-Guillén

et al. 2019

J Pharmacol Exp Ther

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Crohn's disease (CD) is a complex inflammatory bowel disease whose pathogenesis appears to involve several immunologic defects causing functional impairment of the gut. Its complexity and the reported loss of effectiveness over time of standard of care together with the increase in its worldwide incidence require the application of techniques aiming to find new therapeutic strategies. Currently, systems pharmacology modeling has been gaining importance as it integrates the available knowledge of the system into a single computational model. In this work, the following workflow for robust application of systems pharmacology modeling was followed: 1) scope definition; 2) species selection and circulating plasma levels based on a search in the literature; 3) representation of model topology and parametrization of the interactions, after literature data extraction and curation, and the implementation of ordinary differential equations in SimBiology (MATLAB version R2018b); and 4) model curation and evaluation by visual comparison of simulated interleukin (IL) concentrations with the reported levels in plasma, and sensitivity analysis performed to confirm model robustness and identify the most influential parameters. Finally, 5) exposure to two dose levels of recombinant human IL10 was evaluated by simulation and comparison with reported clinical study results. In summary, we present a quantitative systems pharmacology model for the main ILs involved in CD developed using a standardized methodology and supported by a comprehensive repository summarizing the most relevant literature in the field. However, it has to be taken into account that external validation is still pending as available clinical data were primarily used for model training. SIGNIFICANCE STATEMENTCrohn's disease (CD) is a complex heterogeneous inflammatory bowel disorder. Systems pharmacology modeling offers a great opportunity for integration of the available knowledge on the disease using a computational framework. As a result of this work, a comprehensive repository along with a quantitative systems pharmacology model for the main interleukins involved in CD is provided. This model is useful for the in silico evaluation of biomarkers and potential therapeutic targets and can be adapted to address research gaps regarding CD.

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“…Recently, the model was used in order to study the optimal dosing schedule for switching from warfarin to rivaroxaban treatment (Burghaus et al 2014). Another systems pharmacology model of rivaroxaban action was developed by Zhou et al [36]. It contains one of the most complete descriptions of the blood coagulation cascade and accurately predicts clotting times during anticoagulant treatment.…”

Section: Pk-pd and Systems Pharmacology In Blood Clotting Pathologiesmentioning

confidence: 99%

Mathematics of Pharmacokinetics and Pharmacodynamics: Diversity of Topics, Models and Methods

Bocharov

Bouchnita

Clairambault

et al. 2016

Math. Model. Nat. Phenom.

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A short review on pharmacokinetics-pharmacodynamics (PK-PD) presented below aims to show the evolution of some concepts and ideas in this field. Some of them are developed in more detail in the papers of this issue. The key question for a practical application of PK-PD models is the ability to estimate the model parameters using patients data. In [1] a novel approach to an accurate quantification of the uncertainty in parameter estimates attributed to inter-individual variability is proposed. The analyzed PK-PD model is formulated as a compartmental ODE system. The methodology of recognizing and capturing the uncertainty in predicted quantities of interest due to inter-individual variability when the individual is not available for repeated measurements may prove to be invaluable in the risk assessment of future experiments and drug applications. Anticancer molecular PK-PD in a cell population dynamics model with drug delivery optimisation is discussed in [2]. The works [3] and [4] deal with various aspects of hemostasis modelling, and [5] with metabolic aspects in a whole-body setting. These studies represent the diversity of aspects of PK-PD modelling nowadays: theoretical about parameter estimation in general versus applied to medical questions in particular, localised cell population versus whole-body settings, cell population and whole-body versus patient population settings.

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A Systems Pharmacology Model for Predicting Effects of Factor Xa Inhibitors in Healthy Subjects: Assessment of Pharmacokinetics and Binding Kinetics

Cited by 12 publications

References 46 publications

Quantitative Systems Pharmacology Model to Predict the Effects of Commonly Used Anticoagulants on the Human Coagulation Network

Quantitative Systems Pharmacology Model to Predict the Effects of Commonly Used Anticoagulants on the Human Coagulation Network

A Quantitative Systems Pharmacology Model for the Key Interleukins Involved in Crohn's Disease

Mathematics of Pharmacokinetics and Pharmacodynamics: Diversity of Topics, Models and Methods

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