A population analysis of the DGAT1 inhibitor GSK3008356 and its effect on endogenous and meal‐induced triglyceride turnover in healthy subjects. (7th March 2019)

• Record Type: Journal Article
• Authors: Okour, Malek; Brigandi, Richard A.; Tenero, David
• Is Part Of: Fundamental & clinical pharmacology. Volume 33:Number 5(2019)
• Page Start: 567
• Page End: 580
• Publication Date: 2019-03-07
• Subjects: DGAT -- meal -- model -- PK -- PKPD -- triglyceride; Pharmacology -- Periodicals; 615.1
• DOI: 10.1111/fcp.12455
• Languages: English
• ISSNs: 0767-3981

Abstract

Abstract: Non‐alcoholic steatohepatitis (NASH) is a liver disease in which fatty infiltration is accompanied by liver inflammation. GSK3008356 is under development as a selective inhibitor of diacylglycerol acyltransferase 1 (DGAT1), a key enzyme involved in the formation of triglyceride (TG). Decreased DGAT1 activity can reduce circulating TG and liver TG, and therefore could potentially prevent or treat NASH. The aim of the current study was to develop a population pharmacokinetic–pharmacodynamic (PKPD) model that characterizes the PK disposition of GSK3008356 and its relation to the changes in blood TG. Drug concentrations were measured in 104 healthy adults receiving various single (SD) and repeat doses (RD) in a first time in human (FiH) study. A 30% fat meal was given at hour 2 postdose, and blood postprandial TG concentrations were measured at various time points. The population PKPD model consists of several parts including a PK model, drug effect model, meal effect model, and a turnover model. The pharmacokinetic data were described using a 3‐compartment model. Drug effect was described by an inhibitory sigmoidal Emax model. Since TG levels change with the introduction of a meal, a bi‐exponential meal effect model was utilized. The total change in TG was fitted using a turnover model with drug and meal effects on the TG production rate. The current analysis presents a PKPD modeling strategy of time‐varying TG data coming from both endogenous and exogenous sources. In general, the presented model could be utilized in the model‐based drug development of drugs that influence TG levels in blood.