Importance of the Unstirred Water Layer and Hepatocyte Membrane Integrity In Vitro for Quantification of Intrinsic Metabolic Clearance

Abstract

Prediction of clearance-a vital component of drug discovery-remains in need of improvement and, in particular, requires more incisive assessment of mechanistic methodology in vitro, according to a number of recent reports. Although isolated hepatocytes have become an irreplaceable standard system for the measurement of intrinsic hepatic clearance mediated by active uptake transport and metabolism, the lack of prediction reliability appears to reflect a lack of methodological validation, especially for highly cleared drugs, as we have previously shown. Here, novel approaches were employed to explore fundamental experimental processes and associated potential limitations of in vitro predictions of clearance. Rat hepatocytes deemed nonviable by trypan blue staining showed undiminished metabolic activity for probe cytochrome P450 (P450) substrates midazolam and propranolol; supplementation with NADPH enhanced these activities. Extensive permeabilization of the plasma membrane using saponin showed either full or minimal P450 activity, depending on the presence or absence of 1 mM NADPH, respectively. The shaking of incubations facilitated P450 metabolic rates up to 5-fold greater than static incubation, depending on intrinsic clearance, indicating the critical influence of the unstirred water layer (UWL). Permeabilization allowed static incubation metabolic rates to approach those of shaking for intact cells, indicating an artificially induced breakdown of the UWL. Permeabilization combined with shaking allowed an increased metabolic rate for saquinavir, resolving the membrane permeability limitation for this drug. These findings advance the interpretation of the rate-limiting processes involved in intrinsic clearance measurements and could be critical for successful in vitro prediction.

The Extended Clearance Concept Following Oral and Intravenous Dosing: Theory and Critical Analyses

“…Studies often involve hepatocyte uptake studies over a range of drug concentrations to be able to estimate V max and K m parameters, allowing active versus passive permeability to be determined, studies at 4°C or in inactivated/dead hepatocytes to differentiate unspecified binding effects, microsome studies to estimate metabolic clearance, sandwich-cultured hepatocytes to differentiate biliary clearance from metabolic clearance, and attempts to predict efflux permeability clearances by subtracting metabolic and biliary clearances from total cellular clearance measures. Layered on top of the experimental difficulties in carrying out such studies is the recognition that in vitro to in vivo extrapolation is unreliable with in vitro measures predominantly and often significantly under-predicting in vivo clearance even when only metabolism is evaluated as we and others have well documented (37–40). For example, in the Yao et al (27) cerivastatin-cyclosporine DDI analysis the in vitro value for fraction of cerivastatin metabolized by CYP2C8 was found to be too low to account for the observed clinical data.…”

Use of Segregated Hepatocyte Scaling Factors and Cross-Species Relationships to Resolve Clearance Dependence in the Prediction of Human Hepatic Clearance

“…It has become clear in recent years that physiologic scaling of CL int obtained from suspended human hepatocytes not only underpredicts in vivo CL int on average (Ito and Houston, 2005;Riley et al, 2005;TABLE 2 Accuracy and precision of human hepatocyte prediction of in vivo CL int using rat and human in vitro-in vivo scaling factors, as represented by GMFE, RMSE, and the percentage of predictions that fall within 2-fold of the observed in vivo CL int Segregated Hepatocyte Scaling Factors in Prediction of Clearance Brown et al, 2007;Bowman and Benet, 2016) but does so in a clearance-dependent way (Hallifax et al, 2010;Wood et al, 2017). Although the reasons for this dependence remain unclear but could involve effects of the unstirred water layer and/or cofactor depletion in vitro (Hengstler et al, 2000;Hewitt et al, 2000;Hewitt and Utesch, 2004;Hallifax et al, 2010;Foster et al, 2011;Wood et al, 2017Wood et al, , 2018, achieving resolution of this clearance-dependent bias from the considerable prediction uncertainty has provided an opportunity to apply better targeted empirical correction. Because prediction from rat hepatocytes has now been shown to be clearance dependent in the same manner as human hepatocytes (Wood et al, 2017), there appears to exist a basis for renewed potential in the utility of rat hepatocytes for prediction of human in vivo CL int .…”

“…Beyond the system-specific factor, there are species differences between hepatocytes whose impact can be dependent on the drug, such as the shaking of hepatocyte incubations (Wood et al, 2018). Other drugspecific species differences in hepatic clearance include metabolic and transporter pathways, not least due to species differences in cytochrome P450 enzymes or transporters resulting in differences in capacity and/or affinity.…”

“…A recent article by Wood et al (2017) demonstrated that both rat and human hepatic in vitro systems (hepatocytes and microsomes) tend to underpredict in vivo intrinsic clearance (CL int ) in a clearance-dependent way. The reason for this is not yet clear but in vitro factors including cofactor exhaustion (Swales and Utesch, 1998;Hengstler et al, 2000;Wang et al, 2005) and a rate-limiting unstirred water layer (Wood et al, 2018) may play significant roles. Underprediction of hepatic CL int using standard in vitro systems, particularly human, has been recognized for more than a decade but the bias has thus far been generally assumed to be imprecise and irrespective of in vivo CL int .…”

Exposure Measurements on Biomimetic Lobules Using Virtual Experiments to Help Improve IVIVE

“…The sources of inaccuracies are still poorly understood [3][4][5]. Dissimilar biological and methodological factors are cited frequently as causes [6,7], and efforts are underway to identify and reduce IVIVE inaccuracies. For example, reported that, for low-clearance compounds, errors in determining the unbound fraction of drug are proportional to the errors in predicted clearance [8].…”