Transport proteins (transporters) play a vital role in governing drug concentrations in the blood and in various organs including the liver, brain, intestine, lung and kidney. Transporters can move drugs into the tissues (increasing tissue drug levels) and also remove drugs (reducing tissue levels) depending on the location and function of the transporter within the tissue. These proteins often modulate intestinal drug absorption, hepatic/renal elimination, and can enhance the effectiveness of cholesterol-lowering statin drugs.
Assessing the drug interaction potential of investigational drug products is a critical step in their development. The recently published FDA guidance “In Vitro Metabolism- and Transporter-mediated Drug-drug Interaction Studies” addresses how to use in vitro methods to evaluate potential interactions between investigational drugs and transporters.
Drug-mediated inhibition of bile acid transporters in the liver affects bile acid homeostasis, which has important implications for safe and efficacious drug therapy. Current methods to predict these interactions are limited by the interplay of multiple transporters and inaccurate estimates of the relevant inhibitor concentrations. There is no consensus on which type of inhibitor concentration (total or unbound; cellular or cytosolic) is optimal to use for predicting the inhibition of efflux transporters.
Join this webinar with Cen Guo—a graduate student at UNC-Chapel Hill—to learn how she used an integrated approach to predict alterations in bile acid disposition due to inhibition of multiple transporters using the model bile acid taurocholate (TCA). TCA pharmacokinetic (PK) parameters were estimated by mechanistic PK modeling using data from sandwich-cultured human hepatocytes. Monte Carlo simulations of TCA disposition in the presence of model inhibitors (telmisartan and bosentan) were performed using inhibition constants for TCA transporters and inhibitor concentrations including cellular total or unbound concentrations and cytosolic total or unbound concentrations.
Phoenix WinNonlin® uses Phoenix Modeling Language (PML) to encode pharmacokinetic and pharmacodynamic models. Although most models can be built using the graphical user interface (GUI) in Phoenix, some models require custom coding with PML. By attending this webinar, you will learn how to use PML to perform mechanistic pharmacokinetic modeling.
About Our Speaker
Cen Guo is a fifth-year PhD candidate in Pharmaceutical Sciences at the University of North Carolina at Chapel Hill. She is a Chancellor’s Fellow from Royster Society of Fellows. Under the guidance of Dr. Kim Brouwer, Associate Dean for Research and Graduate Education, Guo’s dissertation research focuses on hepatic transporters and pharmacokinetic modeling. Prior to attending UNC, Guo received her BS in pharmacy in 2010 and her MS in pharmacokinetics in 2013 from China Pharmaceutical University.