Prediction of Pharmacokinetics and Drug–Drug Interactions When Hepatic Transporters are Involved

Abstract

Hepatobiliary transport mechanisms have been identified to play a significant role in determining the systemic clearance for a number of widely prescribed drugs and an increasing number of new molecular entities (NMEs). While determining the pharmacokinetics, drug transporters also regulate the target tissue exposure and play a key role in regulating the pharmacological and/or toxicological responses. Consequently, it is of great relevance in drug discovery and development to assess hepatic transporter activity in regard to pharmacokinetic and dose predictions and to evaluate pharmacokinetic variability associated with drug-drug interactions (DDIs) and genetic variants. Mechanistic predictions utilizing physiological-based pharmacokinetic modeling are increasingly used to evaluate transporter contribution and delineate the transporter-enzyme interplay on the basis of hypothesis-driven functional in vitro findings. Significant strides were made in the development of in vitro techniques to facilitate characterization of hepatobiliary transport. However, challenges exist in the quantitative in vitro-in vivo extrapolation of transporter kinetics due to the lack of information on absolute abundance of the transporter in both in vitro and in vivo situations, and/or differential function in the holistic in vitro reagents such as suspended and plated hepatocytes systems, and lack of complete mechanistic understanding of liver model structure. On the other hand, models to predict transporter-mediated DDIs range from basic models to mechanistic static and dynamic models. While basic models provide conservative estimates and are useful upfront in avoiding false negative predictions, mechanistic models integrate multiple victim and perpetrator drugs parameters and are expected to provide quantitative predictions. The aim of this paper is to review the current state of the model-based approaches to predict clinical pharmacokinetics and DDIs of drugs or NMEs that are substrates of hepatic transporters.

Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS)

“…For example, atorvastatin has a high extent of metabolism (>90% of parent eliminated as metabolites), however, active uptake mediated by organic anion transporting polypeptide (OATP) transporters is the rate-determining step of its clearance [12]. Similar evidences were reported with bosentan, cerivastatin, fluvastatin, and repaglinide [5][6][7][8][9][10][11]. In addition, compounds such as valsartan and rosuvastatin are predominantly excreted unchanged in bile while active uptake mediated by OATP transporters is the rate-determining step of their clearance.…”

“…It should be emphasized that a drug's predominant elimination process such as metabolism, biliary or renal excretion may not be always its ratedetermining step in systemic clearance -the latter being the determinant of systemic drug exposure [5][6][7][8][9][10][11]. For example, atorvastatin has a high extent of metabolism (>90% of parent eliminated as metabolites), however, active uptake mediated by organic anion transporting polypeptide (OATP) transporters is the rate-determining step of its clearance [12].…”

Quantitative Prediction of Transporter- and Enzyme-Mediated Clinical Drug-Drug Interactions of Organic Anion-Transporting Polypeptide 1B1 Substrates Using a Mechanistic Net-Effect Model

“…Genetic polymorphism in SLCO1B1, particularly homozygous OATP1B1*15 variant, was reported to possess reduced transport activity (Nishizato et al, 2003;Niemi et al, 2011;Lai et al, 2012;Tomita et al, 2013), and the hepatocytes with such variant may underpredict in vivo clearance. Further investigation in these areas is warranted to understand the lower functional activity in the in vitro systems (Barton et al, 2013;Zamek-Gliszczynski et al, 2013;Li et al, 2014;Lundquist et al, 2014). Nevertheless, improved DDI predictions with mean and drug-specific SF active (Fig.…”

“…CL int,h is mathematically defined by extended clearance concept (further details in Supplemental Equation) (Liu and Pang, 2005;Camenisch and Umehara, 2012;Barton et al, 2013;Li et al, 2014).…”

Alteration of human hepatic drug transporter activity and expression by cigarette smoke condensate

“…Activity and/or expression of hepatic transporters have been shown to be regulated by a wide range of xenobiotics (Fardel et al 2001), leading thus to drug-drug interactions, alterations of pharmacokinetics and liver toxicity (Li et al 2014;Terada and Hira 2015). Interestingly, some chemicals highly present in cigarette smoke such as polycyclic aromatic hydrocarbons (PAHs) regulate expression of some hepatic transporters like BCRP (Ebert et al 2005), MRP4 (Xu et al 2010) and P-gp (Fardel et al 1996;Mathieu et al 2001).…”