2019 - Stockholm - Sweden

PAGE 2019: Drug/Disease modelling - Infection
Mats Jirstrand

A challenge model of TNFα turnover with LPS provocations and drug intervention

Felix Held (1), Edmund Hoppe (2), Marija Cvijovic (1), Mats Jirstrand (3), and Johan Gabrielsson (4)

Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Sweden (2) Grünenthal GmbH, Germany (3) Fraunhofer-Chalmers Centre, Sweden (4) Swedish University of Agricultural Sciences, Sweden

Objectives: Tumor necrosis factor alpha (TNFα) is a pro-inflammatory cytokine associated with the pathogenesis of several immune-mediated diseases. Free TNFα is almost undetectable in blood of healthy organisms. Experimentally, the effect of inflammatory mediators is studied in-vivo after intravenous admini­stration of lipopolysaccharides (LPS), where the challenger causes a rapid but transient release of TNFα. Hence, the base line of the biomarker under study is vanishing and only a transient effect is available for quantifying the effect of drug intervention. This poses a challenging situation for assessing the pharmacodynamic effect by exploratory data analysis and modeling of experimental data [1]. The objectives of this work were to

  • Demonstrate how to assess a pharmacodynamic effect represented by a biomarker with a baseline below the limit of detection.
  • Demonstrate how exploratory data analysis may provide guidance in formulating a model, which enables a better understanding of target biology.

Methods: Three different LPS challenges (Study 1: increasing intravenous dose 0, 3, 30 and 300 μg·kg−1 LPS) and three inhibitory test-compound doses (Study 2: increasing oral doses of test-compound 0, 0.3, 3 and 30 mg·kg−1 followed after two hours by an intravenous dose 30 μg·kg−1 LPS) were investigated using TNFα‑response as a biomarker of target behavior. The test-compound is a selective inhibitor of phosphodiesterase (PDE) type 4 isoforms. Data was pooled from two preclinical studies in rats. A mechanism-based biomarker model of TNFα-response was developed, which includes both external provocations of LPS challenge and test-compound intervention. The model contained system properties, challenge characteristics, and test-compound related parameters. Test-compound exposure was modeled by means of first-order input and Michaelis-Menten type of nonlinear elimination. Lack of LPS exposure time course data was solved by using a biophase model. A transduction type of model with non-linear stimulation of TNFα release was finally selected. TNFα-response was represented by a turnover model with a periphery compartment to account for observed transient effects in the elimination phase. Both stimulation through LPS and inhibition by the test-compound act on TNFα release. Typical features of a challenge experiment were shown by means of model simulations. Experimental shortcomings of present and published designs are identified and discussed. Parameter estimation was performed in three stages using Monolix [2]. In the first two stages test-compound parameters and TNFα turnover parameters after LPS challenge without test-compound intervention were fitted. In the last stage, TNFα time courses with combined LPS challenge and drug intervention were fitted.

Results: Experimental data show a 30 min time lag in onset coupled to a peak-shift in TNFα‑response at increasing LPS doses, which suggests a nonlinear stimulation of TNFα release. The elimination rate constant of LPS from the biophase compartment, the transit compartment rate constant, and the fractional turnover rate of TNFα‑response were all of the same order of magnitude (with half-lives of 7, 18 and 10 min, respectively). Test-compound potency was estimated to 20 nM with a 70% partial reduction in TNFα-response at the highest dose of 30 mg·kg-1. Model simulations were done with a fixed test-compound dose (3 mg·kg-1) and increasing LPS challenges in order to clarify the behavior of the model. Predictions show suppression of TNFα peak response proportional to LPS challenge, as well as a peak-shift in TNFα‑response with increasing LPS doses. A more extensive presentation of the model-based analysis surveyed on this poster can be found in [3].


  • Future selection of drug candidates may focus the estimation on potency and efficacy by applying the selected structure consisting of a TNFα system and LPS challenge charac­teristics
  • Repeated LPS-challenges may reveal how the rate and extent of replenishment of TNFα pools occur
  • Tackling a biomarker with a baseline below the limit of detection requires elaborate models

[1] Gabrielsson, Hjorth, Vogg, Harlfinger, Gutierrez, Peletier, Pehrson, and Davidsson (2015) Modeling and design of challenge tests: Inflammatory and metabolic biomarker study examples. Eur J Pharm Sci 67:144-159. DOI: 10.1016/j.ejps.2014.11.006
[2] Monolix version 2018R1 (2018) Lixoft SAS, Antony, France.
[3] Held, Hoppe, Cvijovic, Jirstrand, and Gabrielsson (2019) Challenge model of TNFα turnover at varying LPS and drug provocations. J Pharmacokinet Pharmacodyn. DOI: 10.1007/s10928-019-09622-x

Reference: PAGE 28 (2019) Abstr 9041 [www.page-meeting.org/?abstract=9041]
Poster: Drug/Disease modelling - Infection
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