Abstract

The Entelos® CV PhysioLab® platform, a mechanistic model of CHD, quantitatively predicts cholesterol metabolism and plaque growth in the coronary artery over time through the dynamic simulation of relevant biological pathways. Statistical methodologies are used to translate predicted changes in circulating lipids and plaque characteristics to predictions of CHD risk. Such predictions can be made for approved or novel therapeutics over time in virtual populations representing a diverse set of patient populations that can be created. PK and PD effects of cholesteryl ester transfer protein (CETP) inhibitors, torcetrapib (60 mg qd), dalcetrapib (600 mg qd) and anacetrapib (100mg qd) were implemented in the platform, calibrated to published data and administered to simulated patients to predict effects on lipoprotein profile and the mean hazard ratio (HR) relative to the same simulated patients on a statin treated background (statin treated mean LDL-C 84 ± 15 mg/dL, HDL-C 44 ± 9 mg/dL). An additional effect of the reported increase on blood pressure was implemented for torcetrapib simulations only. Predicted changes in lipoproteins and 4 year HRare shown in the table. When the mechanistic effects of the reported increase in systolic blood pressure with torcetrapib are added to the lipoprotein changes that result from appropriate CETP inhibition, simulations predict an increased HR similar to that seen in the ILLUMINATE study. Dalcetrapib simulations do not predict any clinically meaningful changes in HR. Finally, despite an additional decrease in LDL-C and the largest increase in HDL-C, anacetrapib simulations predict a very small reduction in HR. Simulations also define a subpopulation within whom the inhibition of CETP activity is more beneficial with the general characteristics of high TG and low HDL-C. 1Additional effect on blood pressure was included in simulations

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