Fig 1.
QSP models of intravenous IFN-α administration in mice and men.
Provision of a novel quantitative cross-species extrapolation approach based on a mechanistically detailed QSP models of intracellular responses via JAK/STAT pathway in human and mice.
Fig 2.
Illustration of the canonical JAK/STAT pathway.
The key steps of the pathway in response to IFN-α are highlighted. IFN binds to the receptor and activates JAK1 and TYK2, which subsequently activate the STATs in the cytoplasm, all by phosphorylation. The phosphorylated STATs and IRF9 form the transcription complex ISGF3, which translocates to the nucleus, where it activates hundreds of ISGs, including IRF9, Mx2 and SOCS1. Heatmap summarizing all analyzed mouse-human correlations. E. Phase I metabolizing enzymes; and F. carriers differentially expressed in human liver disease.
Fig 3.
Fitted Mx2-expression data for the in vitro model ensemble.
Predictions of the model for Mx2 expression in response to 5 U or 500 U IFN-α stimulation (solid lines) and corresponding data points used for fitting (dotted lines).
Fig 4.
Predictions of the in vitro model ensemble for dose response data.
Predicted dose responses of the model for Mx2 expression at 24 h after stimulation with 0.13 nM, 0.26 nM, 1.3 nM, 2.6 nM, 6.5 nM, 13 nM, 26 nM and 65 nM IFN-α. (corresponding to 5 U, 10 U, 50 U, 100 U, 250 U, 500 U, 1000 U and 2500 U IFN-α).
Fig 5.
Development and validation of the mouse PBPK model to the venous blood plasma concentration.
Model fits of the PBPK model to experimental data for IFN-α concentration in blood plasma after i.v. injection of a single dose of 4.43 µg or 3.5 µg IFN- α from Bohoslawec et al. (upper left, [17]) or Rosztoczy et al. (upper right, [19]), respectively, and model validation against Kiuchi et al. (lower left, mix of IFN- α/IFN-β and a data set produced for this study (lower right) after i.v. injection of a single dose of 3.33 µg or 0.0357 µg IFN- α respectively.
Fig 6.
Model fit and validation for Mx2 activity.
Predictions of the model for the expression of Mx2 in response to 1.43 µg murine IFN-α (solid lines) and data on Mx2-Luciferase activity in the liver of mice (points). Mean values are depicted as black points and were used for fitting. Individual measurements were displayed as gray points to show variation in the data.
Fig 7.
In vitro - in vivo difference in signalling patterns.
Differences in signalling patterns in the in vivo QSP response (1.43 µg injected dose solid lines) vs the in vitro PD response (0.695 model units; initial dose; dashed lines). Displayed are the time profiles of IFN-α in the interstitial space of the liver, the activated receptor complex, the negative regulator SOCS1 and the target protein Mx2. For the first three, the ensemble predictions coincide; for Mx2 levels, the range of the ensemble’s predictions are shown.
Fig 8.
Predictions of a human and murine QSP for IFN-α.
Predictions of human fit 5 (dashed line) from Kalra et al. [9] and the here established mouse model (solid line) for the same dose per body weight stimulation with IFN-α. Shown are the concentration of IFN-α in the interstitial space of the liver, the activation of the receptor complex, formation of the transcription factor ISGF3 and its binding to the target genes as well as transcription and translation of IRF9 and SOCS1.
Fig 9.
Fold change difference of predicted signalling patterns between a human and a mouse PBPK/PD.
Fold change differences of signalling patterns predicted by the human ensemble from Kalra et al. 2019 [9] and the here established mouse model for the same dose per body weight stimulation with IFN-α. For evaluation of the differences the maximum concentration (Cmax, left), the time point when Cmax is reached (tmax, middle) and the area under the curve (AUC, right) were calculated for the concentration of IFN-α in the interstitial space of the liver, the activated receptor complex as well as SOCS1 and IRF9 mRNA and protein. Fold changes of these metrics were then calculated from all ten human models to the mouse model, and then averaged. Means are shown as log2 values, where positive fold changes indicate higher levels (Cmax, AUC) or later timing (tmax) in human, and negative values the same in mice.