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Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers.

Nayak S, Lee D, Patel-Hett S, Pittman DD, Martin SW, Heatherington AC, Vicini P, Hua F - CPT Pharmacometrics Syst Pharmacol (2015)

Bottom Line: A number of therapeutics have been developed or are under development aiming to modulate the coagulation network to treat various diseases.We used a systems model to better understand the effect of modulating various components on blood coagulation.We also used the model to explore how variability in concentrations of the proteins in coagulation network can impact the response to FVIIa treatment.

View Article: PubMed Central - PubMed

Affiliation: Pharmacometrics, Global Innovative Pharma Business (GIPB), Pfizer Inc. Cambridge, Massachusetts, USA.

ABSTRACT
A number of therapeutics have been developed or are under development aiming to modulate the coagulation network to treat various diseases. We used a systems model to better understand the effect of modulating various components on blood coagulation. A computational model of the coagulation network was built to match in-house in vitro thrombin generation and activated Partial Thromboplastin Time (aPTT) data with various concentrations of recombinant factor VIIa (FVIIa) or factor Xa added to normal human plasma or factor VIII-deficient plasma. Sensitivity analysis applied to the model revealed that lag time, peak thrombin concentration, area under the curve (AUC) of the thrombin generation profile, and aPTT show different sensitivity to changes in coagulation factors' concentrations and type of plasma used (normal or factor VIII-deficient). We also used the model to explore how variability in concentrations of the proteins in coagulation network can impact the response to FVIIa treatment.

No MeSH data available.


Effect of small variation in the levels of coagulation proteins on TGA profile in response to FVIIa treatment in 8DP by simulation. (a) TGA profile for 100 subjects when initial levels of zymogens or inhibitors were varied up to ±25% of their nominal values. (b) Boxplot of the fold change from nominal value for lag time, peak thrombin, and AUC of the TGA profile. (c) The relative median sensitivity values for proteins.
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fig06: Effect of small variation in the levels of coagulation proteins on TGA profile in response to FVIIa treatment in 8DP by simulation. (a) TGA profile for 100 subjects when initial levels of zymogens or inhibitors were varied up to ±25% of their nominal values. (b) Boxplot of the fold change from nominal value for lag time, peak thrombin, and AUC of the TGA profile. (c) The relative median sensitivity values for proteins.

Mentions: There are substantial variations in the responses to FVIIa treatment.34 We used the model to explore whether small variations in the protein levels (up to 25% in either direction) due to normal population variability could contribute to the observed variability in the response. The TGA profile resulting from treatment with 20 nM of FVIIa in 8DP was simulated for 100 subjects with small variation of coagulation protein levels (Figure6, panela). Figure6 (panelb) shows the variation in lag time, AUC, and peak thrombin expressed as fold change from the nominal values for 8DP. The simulation results show that substantial variability in TGA can be observed. Peak thrombin is most sensitive to changes in the initial levels of coagulation protein and lag time is least sensitive to the variation of the protein levels. To understand which protein may contribute the most to the variability in TGA response to FVIIa, we applied local sensitivity analysis to the 100 sets of initial conditions representing the 100 subjects. The mean results of the 100 sensitivity analyses are shown in Figure6 (panelc). As expected, the potent anticoagulant ATIII is very sensitive, implying that TGA levels are highly dependent on variations in ATIII. TGA is also predicted to be very sensitive to changes in the TFPI level.


Using a Systems Pharmacology Model of the Blood Coagulation Network to Predict the Effects of Various Therapies on Biomarkers.

Nayak S, Lee D, Patel-Hett S, Pittman DD, Martin SW, Heatherington AC, Vicini P, Hua F - CPT Pharmacometrics Syst Pharmacol (2015)

Effect of small variation in the levels of coagulation proteins on TGA profile in response to FVIIa treatment in 8DP by simulation. (a) TGA profile for 100 subjects when initial levels of zymogens or inhibitors were varied up to ±25% of their nominal values. (b) Boxplot of the fold change from nominal value for lag time, peak thrombin, and AUC of the TGA profile. (c) The relative median sensitivity values for proteins.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4544053&req=5

fig06: Effect of small variation in the levels of coagulation proteins on TGA profile in response to FVIIa treatment in 8DP by simulation. (a) TGA profile for 100 subjects when initial levels of zymogens or inhibitors were varied up to ±25% of their nominal values. (b) Boxplot of the fold change from nominal value for lag time, peak thrombin, and AUC of the TGA profile. (c) The relative median sensitivity values for proteins.
Mentions: There are substantial variations in the responses to FVIIa treatment.34 We used the model to explore whether small variations in the protein levels (up to 25% in either direction) due to normal population variability could contribute to the observed variability in the response. The TGA profile resulting from treatment with 20 nM of FVIIa in 8DP was simulated for 100 subjects with small variation of coagulation protein levels (Figure6, panela). Figure6 (panelb) shows the variation in lag time, AUC, and peak thrombin expressed as fold change from the nominal values for 8DP. The simulation results show that substantial variability in TGA can be observed. Peak thrombin is most sensitive to changes in the initial levels of coagulation protein and lag time is least sensitive to the variation of the protein levels. To understand which protein may contribute the most to the variability in TGA response to FVIIa, we applied local sensitivity analysis to the 100 sets of initial conditions representing the 100 subjects. The mean results of the 100 sensitivity analyses are shown in Figure6 (panelc). As expected, the potent anticoagulant ATIII is very sensitive, implying that TGA levels are highly dependent on variations in ATIII. TGA is also predicted to be very sensitive to changes in the TFPI level.

Bottom Line: A number of therapeutics have been developed or are under development aiming to modulate the coagulation network to treat various diseases.We used a systems model to better understand the effect of modulating various components on blood coagulation.We also used the model to explore how variability in concentrations of the proteins in coagulation network can impact the response to FVIIa treatment.

View Article: PubMed Central - PubMed

Affiliation: Pharmacometrics, Global Innovative Pharma Business (GIPB), Pfizer Inc. Cambridge, Massachusetts, USA.

ABSTRACT
A number of therapeutics have been developed or are under development aiming to modulate the coagulation network to treat various diseases. We used a systems model to better understand the effect of modulating various components on blood coagulation. A computational model of the coagulation network was built to match in-house in vitro thrombin generation and activated Partial Thromboplastin Time (aPTT) data with various concentrations of recombinant factor VIIa (FVIIa) or factor Xa added to normal human plasma or factor VIII-deficient plasma. Sensitivity analysis applied to the model revealed that lag time, peak thrombin concentration, area under the curve (AUC) of the thrombin generation profile, and aPTT show different sensitivity to changes in coagulation factors' concentrations and type of plasma used (normal or factor VIII-deficient). We also used the model to explore how variability in concentrations of the proteins in coagulation network can impact the response to FVIIa treatment.

No MeSH data available.