Drug-induced liver injury remains a frequent reason for drug withdrawal. Accordingly, more predictive and translational models are required to assess human hepatotoxicity risk. This study presents a comprehensive evaluation of two promising models to assess mechanistic hepatotoxicity, microengineered Organ-Chips and 3D hepatic spheroids, which have enhanced liver phenotype, metabolic activity and stability in culture not attainable with conventional 2D models. Sensitivity of the models to two hepatotoxins, acetaminophen (APAP) and fialuridine (FIAU), was assessed across a range of cytotoxicity biomarkers (ATP, albumin, miR-122, α-GST) as well as their metabolic functionality by quantifying APAP, FIAU and CYP probe substrate metabolites. APAP and FIAU produced dose-and time-dependent increases in miR-122 and α-GST release as well as decreases in albumin secretion in both Liver-Chips and hepatic spheroids. Metabolic turnover of CYP probe substrates, APAP and FIAU, was maintained over the 10-day exposure period at concentrations where no cytotoxicity was detected and APAP turnover decreased at concentrations where cytotoxicity was detected. With APAP, the most sensitive biomarkers were albumin in the Liver-Chips (EC 50 5.6 mM, day 1) and miR-122 and ATP in the liver spheroids (14-fold and EC 50 2.9 mM, respectively, day 3). With FIAU, the most sensitive biomarkers were albumin in the Liver-Chip (EC 50 126 µM) and miR-122 (15-fold) in the liver spheroids, both on day 7. In conclusion, both models exhibited integrated toxicity and metabolism, and broadly similar sensitivity to the hepatotoxicants at relevant clinical concentrations, demonstrating the utility of these models for improved hepatotoxicity risk assessment.
In addition to hepatocytes, the liver comprises a host of specialised non-parenchymal cells which are important to consider in the development of in vitro models which are both physiologically and toxicologically relevant. We have characterized a 3D co-culture system comprising primary human hepatocytes (PHH) and non-parenchymal cells (NPC) and applied it to the investigation of acetaminophen-induced toxicity. Firstly, we titrated ratios of PHH:NPC and confirmed the presence of functional NPCs via both immunohistochemistry and activation with both LPS and TGF-β. Based on these data we selected a ratio of 2:1 PHH:NPC for further studies. We observed that spheroids supplemented with NPCs were protected against acetaminophen (APAP) toxicity as determined by ATP (up to threefold difference in EC 50 at day 14 compared to hepatocytes alone) and glutathione depletion, as well as miR-122 release. APAP metabolism was also altered in the presence of NPCs, with significantly lower levels of APAP-GSH detected. Expression of several CYP450 enzymes involved in the bioactivation of APAP was also lower in NPC-containing spheroids. Spheroids containing NPCs also expressed higher levels of miRNAs which have been implicated in APAP-induced hepatotoxicity, including miR-382 and miR-155 which have potential roles in liver regeneration and inflammation, respectively. These data indicate that the interaction between hepatocytes and NPCs can have significant metabolic and toxicological consequences important for the correct elucidation of hepatic safety mechanisms.
A structurally identifiable micro-rate constant mechanistic model was used to describe the interaction between pitavastatin and eltrombopag, with improved goodness-of-fit values through comeasurement of pitavastatin and eltrombopag. Transporter association and dissociation rate constants and passive rates out of the cell were similar between pitavastatin and eltrombopag. Translocation into the cell through transporter-mediated uptake was six times greater for pitavastatin, leading to pronounced inhibition of pitavastatin uptake by eltrombopag. The passive rate into the cell was 91 times smaller for pitavastatin compared with eltrombopag. A semimechanistic physiologically-based pharmacokinetic (PBPK) model was developed to evaluate the potential for clinical drug-drug interactions (DDIs). The PBPK model predicted a twofold increase in the pitavastatin peak blood concentration and area under the concentration-time curve in the presence of eltrombopag in simulated healthy volunteers. The use of structural identifiability supporting experimental design combined with robust micro-rate constant parameter estimates and a semimechanistic PBPK model gave more informed predictions of transporter-mediated DDIs.Pitavastatin, one of the family of 3-hydroxy-3-methyl-glutaryl-CoA (HMG-CoA) reductase inhibitors used to manage hypercholesterolemia, has been determined in vitro to be a substrate of organic anion transporting polypeptide (OATP)1B1 and OATP1B3 (fraction transported of 0.78) and of the efflux transporters breast cancer resistance protein (BCRP) and multidrug resistance associated protein (MRP) 2. 1,2 Pitavastatin is more sensitive to transporter inhibition than rosuvastatin in vitro as well as in healthy volunteers 2 and is therefore a good candidate for evaluating transporter-mediated drugdrug interactions (TrDDIs). Elimination of pitavastatin through metabolism and urinary excretion is relatively small compared with the biliary elimination of pitavastatin (53%). 3 Eltrombopag is a thrombopoietin agonist used in the management of thrombocytopenic purpura, and the dose is individualized based on the platelet count to prevent excessive clotting or a lack of effect. 4 It is highly protein bound, and the adsorption to plasma proteins was included to obtain an inhibition concentration at half of the maximum inhibition (IC 50 ) value that explained the inhibition of rosuvastatin. 5 In vitro studies found eltrombopag to be a substrate of OATP1B1, OATP2B1, organic cation transporter 1 (OCT1), ✔ Currently, most in vitro models are not guided by structural identifiability analysis, relying on substrate-only measurements to evaluate transporter inhibition and subsequent drug-drug interaction (DDI) predictions. WHAT QUESTION DID THIS STUDY ADDRESS? ✔ Whether using micro-rate constants compared with macro-rate constants to describe the comeasurement of uptake of substrate (pitavastatin) and inhibitor (eltrombopag) can improve model fits through structurally identifiable mechanistic models, and the potential for transporter DDIs ...
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