Mathematical models of lipoprotein metabolism and kinetics: current status and future perspective

Analysis of "On/Off" Kinetics of a CETP Inhibitor Using a Mechanistic Model of Lipoprotein Metabolism and Kinetics

RG7232 is a potent inhibitor of cholesteryl-ester transfer protein (CETP). Daily oral administration of RG7232 produces a dose- and time-dependent increase in high-density lipoprotein-cholesterol (HDL-C) and apolipoproteinA-I (ApoA-I) levels and a corresponding decrease in low-density lipoprotein-cholesterol (LDL-C) and apolipoproteinB (ApoB) levels. Due to its short plasma half-life (∼3 hours), RG7232 transiently inhibits CETP activity during each dosing interval ("on/off" kinetics), as reflected by the temporal effects on HDL-C and LDL-C. The influence of RG7232 on lipid-poor ApoA-I (i.e., pre-β 1) levels and reverse cholesterol transport rates is unclear. To investigate this, a published model of lipoprotein metabolism and kinetics was combined with a pharmacokinetic model of RG7232. After calibration and validation of the combined model, the effect of RG7232 on pre-β 1 levels was simulated. A dose-dependent oscillation of pre-β 1, driven by the "on/off" kinetics of RG7232 was observed. The possible implications of these findings are discussed.

An in-silico model of lipoprotein metabolism and kinetics for the evaluation of targets and biomarkers in the reverse cholesterol transport pathway

High-density lipoprotein (HDL) is believed to play an important role in lowering cardiovascular disease (CVD) risk by mediating the process of reverse cholesterol transport (RCT). Via RCT, excess cholesterol from peripheral tissues is carried back to the liver and hence should lead to the reduction of atherosclerotic plaques. The recent failures of HDL-cholesterol (HDL-C) raising therapies have initiated a re-examination of the link between CVD risk and the rate of RCT, and have brought into question whether all target modulations that raise HDL-C would be atheroprotective. To help address these issues, a novel in-silico model has been built to incorporate modern concepts of HDL biology, including: the geometric structure of HDL linking the core radius with the number of ApoA-I molecules on it, and the regeneration of lipid-poor ApoA-I from spherical HDL due to remodeling processes. The ODE model has been calibrated using data from the literature and validated by simulating additional experiments not used in the calibration. Using a virtual population, we show that the model provides possible explanations for a number of well-known relationships in cholesterol metabolism, including the epidemiological relationship between HDL-C and CVD risk and the correlations between some HDL-related lipoprotein markers. In particular, the model has been used to explore two HDL-C raising target modulations, Cholesteryl Ester Transfer Protein (CETP) inhibition and ATP-binding cassette transporter member 1 (ABCA1) up-regulation. It predicts that while CETP inhibition would not result in an increased RCT rate, ABCA1 up-regulation should increase both HDL-C and RCT rate. Furthermore, the model predicts the two target modulations result in distinct changes in the lipoprotein measures. Finally, the model also allows for an evaluation of two candidate biomarkers for in-vivo whole-body ABCA1 activity: the absolute concentration and the % lipid-poor ApoA-I. These findings illustrate the potential utility of the model in drug development.