Intracellular drug concentrations and transporters: measurement, modeling, and implications for the liver

Abstract

Intracellular concentrations of drugs and metabolites are often important determinants of efficacy, toxicity, and drug interactions. Hepatic drug distribution can be affected by many factors, including physicochemical properties, uptake/efflux transporters, protein binding, organelle sequestration, and metabolism. This white paper highlights determinants of hepatocyte drug/metabolite concentrations and provides an update on model systems, methods, and modeling/simulation approaches used to quantitatively assess hepatocellular concentrations of molecules. The critical scientific gaps and future research directions in this field are discussed.

Figure 1

Microanatomy of the liver. Hepatocytes, bile ductules, and sinusoids are represented. The structure of a hepatocyte is depicted with its apical, basal, and lateral sides. The sinusoid is depicted to highlight the fact that the blood is not well mixed in the sinusoid.

Figure 2

Factors affecting intracellular drug concentrations in the hepatocyte. (a) Processes affecting intracellular drug concentrations are depicted. (1) Drug in the blood that is not associated with blood cells or plasma proteins can enter the hepatocyte (2) through passive diffusion or (3) via active uptake mediated by basolateral uptake transporters. Within the hepatocytes, (4,5) the drug can bind to intracellular structures (e.g., proteins, DNA, and membranes) or (6) partition into subcellular organelles such as mitochondria or lysosomes via a combination of carrier-mediated transport and/or passive diffusion driven by the electrochemical membrane potential and the pH gradient. Based on the free-drug hypothesis, only the unbound drug in the hepatocyte can undergo (7) efflux back to sinusoidal blood via the action of basolateral efflux transporters, (8) enzymatic biotransformation, or (9) excretion into the bile mediated by canalicular efflux transporters. (b) Passive and active clearance processes affecting hepatocyte intracellular concentrations. CL_act,efflux, intrinsic active efflux clearance; CL_act,uptake, intrinsic active uptake clearance; CL_bile, intrinsic biliary excretion clearance; CL_diff, passive diffusion clearance; CL_met, intrinsic metabolic clearance; f_u,b, unbound fraction of drug in the blood; f_u,cell, unbound fraction of drug in cell; f_u,ISF , unbound fraction of drug in interstitial fluid. (c) Membrane localization of key uptake and efflux transporters that may affect hepatocyte intracellular concentrations. The schematic representation is limited to transporters expressed in the plasma membrane that have previously shown effects on drug disposition and toxicity and could potentially modulate unbound drug concentrations in the liver.

Figure 3

PBPK simulations of the unbound plasma and liver concentration–time profiles and the ratio of unbound liver tissue to liver sinusoidal concentrations (K_puu,liver). A permeability-limited liver model was used for simulations to account for active transport processes. (a–c) Drugs with a large contribution of passive diffusion to total uptake and substantial metabolic elimination/biliary excretion. Profiles represent the impact of variation in hepatic elimination resulting in differential liver exposures, where the solid line represents CL_met (or CL_bile); dashed line, 0.5× CL_met (or CL_bile); and dashed-dotted line, 2× CL_met (or CL_bile). (d–f) Active uptake is the major contributor to the total uptake (CL_act,uptake > CL_diff > CL_met or CL_bile). Variation in uptake transporter activity (solid line represents CL_act,uptake; dashed line, 0.5× CL_act,uptake; and dashed-dotted line, 2× CL_act,uptake) results in differential blood exposure (d) with no effect on liver AUC (e) for drugs primarily cleared by liver, either via biliary excretion (e.g., pravastatin) or CYP450-mediated metabolism (e.g., repaglinide). (a–f) The drug is assumed to have a high extent of intracellular binding (f_u,cell < 0.1) and minimal contribution of renal clearance to overall elimination. Changing the f_u,cell in the PBPK model will affect the total liver concentration, but the overall trends will remain the same. AUC, area under the concentration–time curve; CL_act,uptake, intrinsic active uptake clearance; CL_bile, intrinsic biliary excretion clearance; CL_diff, passive diffusion clearance; CL_met, intrinsic metabolic clearance; f_u,cell, unbound fraction of drug in cell; PBPK, physiologically based pharmacokinetic.