Accurate prediction of the hepatic clearance in humans is essential during pre-clinical drug development. As conventional in vitro models do not replicate the complexity of the human liver physiology, hepatocyte-specific functions are rapidly lost resulting in limited assay sensitivity. In this study, a commercially available organ-on-chip model featuring a two-compartment microfluidic architecture was evaluated to estimate human hepatic clearance for a panel of 15 commercial drug compounds with diverse metabolic pathways and clearance rates. Upon further optimization of the model for the co-culture of primary human hepatocytes and liver sinusoidal endothelial cells, key system parameters - including compound permeability, non-specific binding, and evaporation - were systematically characterized. Despite optimized conditions, the human hepatic clearance was generally underpredicted by the liver-chip. The best performance was observed for compounds with low to moderate clearance while the underprediction was more pronounced for compounds exhibiting high metabolic turnover. By introducing a model-specific systematic scaling factor, more than 79% of clearance predictions fell within a three-fold range of observed human values. The study identified challenges in liver-chip systems for ADME applications that stem from specific design features and proposes optimization strategies for using liver-chips in metabolic stability assessments.

Accurate predictions of complex clinical drug-drug interactions (DDIs), arising from dual induction and time-dependent inhibition (TDI) of CYP3A4, has remained challenging with conventional in vitro and static/dynamic modeling approaches. In this work, we aimed to anticipate the hepatic DDI effects of 6 CYP3A4 precipitant drugs using a liver-chip coupled to microfluidic perfusion, which enabled simulating clinically relevant pharmacokinetic (PK) time-concentration profiles. Midazolam clearance was measured in the liver-chip to determine the CYP3A4-mediated DDI net effect following exposure to precipitants under either dynamic or constant concentration conditions. For direct comparison, hepatic DDI reference values were generated based on clinical DDI studies by physiologically based PK modeling. Under microfluidic perfusion, CYP3A4 activity in the liver-chip was retained for 3 days and inducible by rifampicin. Although most precipitant drugs induced CYP3A4 mRNA levels, CYP3A4 activity net effects showed either induction or inhibition, in line with clinical observations. Compared with a mechanistic static net effect model and physiologically based PK simulations, liver-chip predictions showed closer alignment and higher accuracy relative to hepatic reference values. Although constant exposures offered the strongest quantitative performance, the ability to apply dynamic PK profiles represents a distinctive feature of this platform. Collectively, these findings position the human liver-chip as a novel translational platform for predicting complex hepatic CYP3A4 DDIs arising from dual TDI and induction in a single, holistic in vitro model. This approach aligns with the broader global regulatory shift toward human-relevant new approach methodologies. SIGNIFICANCE STATEMENT: Complex CYP3A4-mediated drug-drug interactions (DDIs), driven by concurrent time-dependent inhibition and induction, remain difficult to anticipate using conventional in vitro and modeling frameworks. This study establishes a human liver-chip model capable of capturing dual CYP3A4 inhibition and induction within a single experiment, and evaluates how clinical exposure regimes shape the quantitative prediction of hepatic DDI effects. Relative to modeling approaches, this platform demonstrates superior accuracy against hepatic DDI references, supporting more translational DDI risk assessments.

PurposeThe Extended Clearance Concept Classification System was established as a development-stage tool to provide a framework for identifying fundamental mechanism(s) governing drug disposition in humans. In the present study, the applicability of the EC3S in drug discovery has been investigated. In its current format, the EC3S relies on low-throughput hepatocyte uptake data, which are not frequently generated in a discovery setting.MethodsA relationship between hepatocyte uptake clearance and MDCK permeability was first established along with intrinsic clearance from human liver microsomes. The performance of this approach was examined by categorizing 64 drugs into EC3S classes and comparing the predicted major elimination pathway(s) to that observed in humans. As an extension of the work, the ability of the simplified EC3S to predict human systemic clearance based on intrinsic clearance generated using in-vitro metabolic systems was evaluated.ResultsThe assessment enabled the use of MDCK permeability and unscaled unbound intrinsic clearance to generate cut-off criteria to categorize compounds into four EC3S classes: Class 12ab, 2cd, 34ab, and 34cd, with major elimination mechanism(s) assigned to each class. The predictivity analysis suggested that systemic clearance could generally be predicted within threefold for EC3S class 12ab and 34ab compounds. For classes 2cd and 34cd, systemic clearance was poorly predicted using in-vitro systems explored in this study.ConclusionCollectively, our simplified classification approach is expected to facilitate the identification of mechanism(s) involved in drug elimination, faster resolution of in-vitro to in-vivo disconnects, and better design of mechanistic pharmacokinetic studies in drug discovery.

Characterizing the pharmacokinetic properties of drug candidates represents an essential task during drug development. In the past, liver microsomes and primary suspended hepatocytes have been extensively used for this purpose, but their relatively short stability limits the applicability of such in vitro systems for drug compounds with low metabolic turnover. In the present study, we used three-dimensional primary human hepatocyte spheroids to predict the hepatic clearance of seven drugs with low to intermediate clearance in humans. Our results indicate that hepatocyte spheroids maintain their in vivo–like phenotype during prolonged incubations, allowing to monitor the depletion of parent drug for 7 days. In contrast, attempts to increase the relative metabolic capacity by pooling hepatocyte spheroids resulted in an immediate fusion of the spheroids followed by hepatocellular de-differentiation processes, demonstrating limited applicability of the pooling approach for quantitative pharmacokinetic studies. The hepatic clearance values obtained from incubations with individual spheroids were in close correlation with the clinical reference data, with six out of seven drug compounds being predicted within a 3-fold deviation and average fold and absolute average fold errors of 0.57 and 1.74, respectively. In conclusion, the hepatocyte spheroid model enables accurate hepatic clearance predictions for slowly metabolized drug compounds and represents a valuable tool for determining the pharmacokinetic properties of new drug candidates as well as for mechanistic pharmacokinetic studies. SIGNIFICANCE STATEMENT Traditional in vitro systems often fail to predict the hepatic clearance of slowly metabolized drug compounds. The current study demonstrates the ability of primary human hepatocyte spheroids to provide accurate projections on the hepatic clearance of drug compounds with low and intermediate clearance.

Drug hepatotoxicity is often delayed in onset. An exemplar case is the chronic nature of fialuridine hepatotoxicity, which resulted in the deaths of several patients in clinical trials as preclinical studies failed to identify this human-specific hepatotoxicity. Conventional preclinical in vitro models are mainly designed to evaluate the risk of acute drug toxicity. Here, we evaluated the utility of 3D spheroid cultures of primary human hepatocytes (PHHs) to assess chronic drug hepatotoxicity events using fialuridine as an example. Fialuridine toxicity was only detectable after 7 days of repeated exposure. Clinical manifestations, including reactive oxygen species formation, lipid accumulation, and induction of apoptosis, were readily identified. Silencing the expression or activity of the human equilibrative nucleoside transporter 1 (ENT1), implicated in the mitochondrial transport of fialuridine, modestly protected PHH spheroids from fialuridine toxicity. Interference with the phosphorylation of fialuridine into the active triphosphate metabolites by silencing of thymidine kinase 2 (TK2) provided substantial protection, whereas simultaneous silencing of ENT1 and TK2 provided near-complete protection. Fialuridine-induced mitochondrial dysfunction was suggested by a decrease in the expression of mtDNA-encoded genes, which correlated with the onset of toxicity and was prevented under the simultaneous silencing of ENT1 and TK2. Furthermore, interference with the expression or activity of ribonucleotide reductase (RNR), which is critical to deoxyribonucleoside triphosphate (dNTP) pool homeostasis, resulted in selective potentiation of fialuridine toxicity. Our findings demonstrate the translational applicability of the PHH 3D spheroid model for assessing drug hepatotoxicity events which manifest only under chronic exposure conditions.

The generation of reliable kinetic parameters to describe P-glycoprotein (P-gp) activity is essential for predicting the impact of efflux transport on gastrointestinal drug absorption. The compound-specific selection of in vitro assay designs and ensuing data analysis methods is explored in this manuscript. We measured transcellular permeability and cellular uptake of five P-gp substrates in Caco-2 and LLC-PK1 MDR1 cells. Kinetic parameters of P-gp-mediated efflux transport (Km, Vmax) were derived from conventional and mechanistic compartmental models. The estimated apparent Km values based on medium concentrations in the conventional permeability model indicated significant differences between the cell lines. The respective intrinsic Km values based on unbound intracellular concentrations in the mechanistic compartmental models were significantly lower and comparable between cell lines and assay formats. Non-specific binding or lysosomal trapping were shown to cause discrepancies in the kinetic parameters obtained from different assay formats. A guidance for the selection of in vitro assays and kinetic assessment methods is proposed in line with the Biopharmaceutics Drug Disposition Classification System (BDDCS). The recommendations are expected to aid the acquisition of robust and reproducible kinetic parameters of P-gp-mediated efflux transport.

Unbound intrahepatic drug concentrations determine the interaction potential with intracellular targets related to toxicity, pharmacokinetics, or pharmacodynamics. Recently, the unbound liver-to-blood partition coefficient (Kpuu) based on the Extended Clearance Model (ECM) has been developed providing indirect estimates of unbound intrahepatic drug concentrations. This study aimed to determine Kpuu for 18 diverse drug compounds by 3 alternative in vitro methods and to compare the outcome with the ECM approach. Kpuu was calculated from independent measurements of hepatocellular drug accumulation (Kp) and unbound fraction in hepatocytes (fuhep) either assessed from steady-state accumulation at 4°C (temperature method), using equilibrium dialysis (homogenization method), or empirically from logD7.4 (logD7.4 method). Deviations to ECM-based Kpuu data were closely linked to the absence of intrinsic clearance processes (metabolism, biliary secretion) in the investigated methods. Differences in fuhep additionally contributed to deviations in Kpuu. The homogenization method generally provided lowest fuhep values, especially for compounds with high molecular weight or low logD7.4. Kpuu values of compounds with low intrinsic clearance correlated well between the ECM and temperature methods independent of physicochemical properties. Therefore, only the ECM provides an integrated quantitative determination of hepatic Kpuu. Temperature and homogenization methods, however, represent useful alternatives if compound properties are appropriately considered.

Inhibition of the bile salt export pump (BSEP) has been recognized as a key factor in the development of drug-induced cholestasis (DIC). The risk of DIC in humans has been previously assessed using in vitro BSEP inhibition data (IC50) and unbound systemic drug exposure under assumption of the "free drug hypothesis." This concept, however, is unlikely valid, as unbound intrahepatic drug concentrations are affected by active transport and metabolism. To investigate this hypothesis, we experimentally determined the in vitro liver-to-blood partition coefficients (Kpuu) for 18 drug compounds using the hepatic extended clearance model (ECM). In vitro-in vivo translatability of Kpuu values was verified for a subset of compounds in rat. Consequently, unbound intrahepatic concentrations were calculated from clinical exposure (systemic and hepatic inlet) and measured Kpuu data. Using these values, corresponding safety margins against BSEP IC50 values were determined and compared with the clinical incidence of DIC. Depending on the ECM class of a drug, in vitro Kpuu values deviated up to 14-fold from unity, and unbound intrahepatic concentrations were affected accordingly. The use of in vitro Kpuu-based safety margins allowed separation of clinical cholestasis frequency into three classes (no cholestasis, cholestasis in ≤2%, and cholestasis in >2% of subjects) for 17 out of 18 compounds. This assessment was significantly superior compared with using unbound extracellular concentrations as a surrogate for intrahepatic concentrations. Furthermore, the assessment of Kpuu according to ECM provides useful guidance for the quantitative evaluation of genetic and physiologic risk factors for the development of cholestasis.

Total human clearance is a key determinant for the pharmacokinetic behavior of drug candidates. Our group recently introduced the Extended Clearance Model (ECM) as an accurate in vitro-in vivo extrapolation (IVIVE) method for the prediction of hepatic clearance. Yet, knowledge about relative elimination pathway contributions is needed in order to predict the total human clearance of drug candidates. In the present work, a training set of 18 drug compounds was used to describe the affiliations between in vitro sinusoidal uptake clearance and the fractional contributions of hepatic (metabolic and biliary) or renal clearance to overall in vivo elimination. By means of these quantitative relationships and using a validation set of 10 diverse drug molecules covering different (sub)classes of the Extended Clearance Concept Classification System (ECCCS), the relative contributions of elimination pathways were calculated and demonstrated to well correlate with human reference data. Likewise, ECM- and pathway-based predictions of total clearances from both data sets demonstrated a strong correlation with the observed clinical values with 26 out of 28 compounds within a three-fold deviation. Hence, total human clearance and relative contributions of elimination pathways were successfully predicted by the presented method using solely hepatocyte and microsome in vitro data.

Hepatic elimination is a function of the interplay between different processes such as sinusoidal uptake, intracellular metabolism, canalicular (biliary) secretion, and sinusoidal efflux. In this review, we outline how drugs can be classified according to their in vitro determined clearance mechanisms using the extended clearance model as a reference. The approach enables the determination of the rate-determining hepatic clearance step. Some successful applications will be highlighted, together with a discussion on the major consequences for the pharmacokinetics and the drug-drug interaction potential of drugs. Special emphasize is put on the role of passive permeability and active transport processes in hepatic elimination.

The nuclear matrix (NM) is an operationally defined structure of the mammalian cell nucleus that resists stringent biochemical extraction procedures applied subsequent to nuclease-mediated chromatin digestion of intact nuclei. This comprises removal of soluble biomolecules and chromatin by means of either detergent (LIS: lithium diiodosalicylate) or high salt (AS: ammonium sulfate, sodium chloride) treatment. So far, progress toward defining bona fide NM proteins has been hindered by the problem of distinguishing them from copurifying abundant contaminants and extraction-method-intrinsic precipitation artifacts. Here, we present a highly improved NM purification strategy, adding a FACS sorting step for efficient isolation of morphologically homogeneous lamin B positive NM specimens. SILAC-based quantitative proteome profiling of LIS-, AS-, or NaCl-extracted matrices versus the nuclear proteome together with rigorous statistical filtering enables the compilation of a high-quality catalogue of NM proteins commonly enriched among the three different extraction methods. We refer to this set of 272 proteins as the NM central proteome. Quantitative NM retention profiles for 2381 proteins highlight elementary features of nuclear organization and correlate well with immunofluorescence staining patterns reported in the Human Protein Atlas, demonstrating that the NM central proteome is significantly enriched in proteins exhibiting a nuclear body as well as nuclear speckle-like morphology.