Simultaneous Assessment In Vitro of Transporter and Metabolic Processes in Hepatic Drug Clearance: Use of a Media Loss Approach

Exploring the Boundaries for In Vitro-In Vivo Extrapolation: Use of Isolated Rat Hepatocytes in Co-culture and Impact of Albumin Binding Properties in the Prediction of Clearance of Various Drug Types

Prediction of hepatic clearance of drugs (via uptake or metabolism) from in vitro systems continues to be problematic, particularly when plasma protein binding is high. The following work explores simultaneous assessment of both clearance processes, focusing on a commercial hepatocyte-fibroblast co-culture system (HμREL) over a 24-hour period using six probe drugs (ranging in metabolic and transporter clearance and low-to-high plasma protein binding). A rat hepatocyte co-culture assay was established using drug depletion (measuring both medium and total concentrations) and cell uptake kinetic analysis, both in the presence and absence of plasma protein (1% bovine serum albumin). Secretion of endogenous albumin was monitored as a marker of viability, and this reached 0.004% in incubations (at a rate similar to in vivo synthesis). Binding to stromal cells was substantial and required appropriate correction factors. Drug concentration-time courses were analyzed both by conventional methods and a mechanistic cell model prior to in vivo extrapolation. Clearance assayed by drug depletion in conventional suspended rat hepatocytes provided a benchmark to evaluate co-culture value. Addition of albumin appeared to improve predictions for some compounds (where fraction unbound in the medium is less than 0.1); however, for high-binding drugs, albumin significantly limited quantification and thus predictions. Overall, these results highlight ongoing challenges concerning in vitro hepatocyte system complexity and limitations of practical expediency. Considering this, more reliable measurement of hepatically cleared compounds seems possible through judicious use of available hepatocyte systems, including co-culture systems, as described herein; this would include those compounds with low metabolic turnover but high active uptake clearance. SIGNIFICANCE STATEMENT: Co-culture systems offer a more advanced tool than standard hepatocytes, with the ability to be cultured for longer periods of time, yet their potential as an in vitro tool has not been extensively assessed. We evaluate the strengths and limitations of the HμREL system using six drugs representing various metabolic and transporter-mediated clearance pathways with various degrees of albumin binding. Studies in the presence/absence of albumin allow in vitro-in vivo extrapolation and a framework to maximize their utility.

A model-informed method to retrieve intrinsic from apparent cooperativity and project cellular target occupancy for ternary complex-forming compounds

There is an increasing interest to develop therapeutics that modulate challenging or undruggable target proteins via a mechanism that involves ternary complexes. In general, such compounds can be characterized by their direct affinities to a chaperone and a target protein and by their degree of cooperativity in the formation of the ternary complex. As a trend, smaller compounds have a greater dependency on intrinsic cooperativity to their thermodynamic stability relative to direct target (or chaperone) binding. This highlights the need to consider intrinsic cooperativity of ternary complex-forming compounds early in lead optimization, especially as they provide more control over target selectivity (especially for isoforms) and more insight into the relationship between target occupancy and target response via estimation of ternary complex concentrations. This motivates the need to quantify the natural constant of intrinsic cooperativity (α) which is generally defined as the gain (or loss) in affinity of a compound to its target in pre-bound vs. unbound state. Intrinsic cooperativities can be retrieved via a mathematical binding model from EC₅₀ shifts of binary binding curves of the ternary complex-forming compound with either a target or chaperone relative to the same experiment but in the presence of the counter protein. In this manuscript, we present a mathematical modeling methodology that estimates the intrinsic cooperativity value from experimentally observed apparent cooperativities. This method requires only the two binary binding affinities and the protein concentrations of target and chaperone and is therefore suitable for use in early discovery therapeutic programs. This approach is then extended from biochemical assays to cellular assays (i.e., from a closed system to an open system) by accounting for differences in total ligand vs. free ligand concentrations in the calculations of ternary complex concentrations. Finally, this model is used to translate biochemical potency of ternary complex-forming compounds into expected cellular target occupancy, which could ultimately serve as a way for validation or de-validation of hypothesized biological mechanisms of action.

Nature-Derived Compounds as Potential Bioactive Leads against CDK9-Induced Cancer: Computational and Network Pharmacology Approaches

Given the importance of cyclin-dependent kinases (CDKs) in the maintenance of cell development, gene transcription, and other essential biological operations, CDK blockers have been generated to manage a variety of disorders resulting from CDK irregularities. Furthermore, CDK9 has a crucial role in transcription by regulating short-lived anti-apoptotic genes necessary for cancer cell persistence. Addressing CDK9 with blockers has consequently emerged as a promising treatment for cancer. This study scrutinizes the effectiveness of nature-derived compounds (geniposidic acid, quercetin, geniposide, curcumin, and withanolide C) against CDK9 through computational approaches. A molecular docking study was performed after preparing the protein and the ligands. The selected blockers of the CDK9 exerted reliable binding affinities (−8.114 kcal/mol to −13.908 kcal/mol) against the selected protein, resulting in promising candidates compared to the co-crystallized ligand (LCI). The binding affinity of geniposidic acid (−13.908 kcal/mol) to CDK9 is higher than quercetin (−10.775 kcal/mol), geniposide (−9.969 kcal/mol), curcumin (−9.898 kcal/mol), withanolide C (−8.114 kcal/mol), and the co-crystallized ligand LCI (−11.425 kcal/mol). Therefore, geniposidic acid is a promising inhibitor of CDK9. Moreover, the molecular dynamics studies assessed the structure–function relationships and protein–ligand interactions. The network pharmacology study for the selected ligands demonstrated the auspicious compound–target–pathway signaling pathways vital in developing tumor, tumor cell growth, differentiation, and promoting tumor cell progression. Moreover, this study concluded by analyzing the computational approaches the natural-derived compounds that have potential interacting activities against CDK9 and, therefore, can be considered promising candidates for CKD9-induced cancer. To substantiate this study’s outcomes, in vivo research is recommended.

Time Matters - In vitro Cellular Disposition Kinetics Help Rationalizing Cellular Potency Disconnects

Loss in potency is commonly observed in early drug discovery when moving from biochemical to more complex cellular systems. Among other factors, low permeability is often considered to cause such potency disconnects.We developed a novel cellular disposition assay in MDCK cells to determine passive uptake clearance (PS_inf), cell-to-medium ratios at steady-state (Kp) and the time to reach 90% steady-state (TTSS₉₀) from a single experiment in a high-throughput format.The assay was validated using 40 marketed drugs, showing a wide distribution of PS_inf and K_p values. The parameters generally correlated with transcellular permeability and lipophilicity, while PS_inf data revealed better resolution in the high and low permeability ranges compared to traditional permeability data. A linear relationship between the K_p/PS_inf ratio and TTSS₉₀ was mathematically derived and experimentally validated, demonstrating the dependency of TTSS₉₀ on the rate and extent of cellular accumulation.Cellular disposition parameters could explain potency (IC₅₀) disconnects noted for seven Bruton's tyrosine kinase degrader compounds in a cellular potency assay. In contrast to transcellular permeability, PS_inf data enabled identification of the compounds with IC₅₀ disconnects based on their time to reach equilibrium. Overall, the novel assay offers the possibility to address potency disconnects in early drug discovery.

Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats

Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug–drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro–in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis–Menten constant (K_m,u) of gadoxetate was 106 μM (17%) (n = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK–IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE–MRI profiles and elimination from the liver. Therefore, in vivo rat DCE–MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE–MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI.

Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies

Physiologically based pharmacokinetic modelling is well established in the pharmaceutical industry and is accepted by regulatory agencies for the prediction of drug-drug interactions. However, physiologically based pharmacokinetic modelling is valuable to address a much wider range of pharmaceutical applications, and new regulatory impact is expected as its full power is leveraged. As one example, physiologically based pharmacokinetic modelling is already routinely used during drug discovery for in-vitro to in-vivo translation and pharmacokinetic modelling in preclinical species, and this leads to the application of verified models for first-in-human pharmacokinetic predictions. A consistent cross-industry strategy in this application area would increase confidence in the approach and facilitate further learning. With this in mind, this article aims to enhance a previously published first-in-human physiologically based pharmacokinetic model-building strategy. Based on the experience of scientists from multiple companies participating in the GastroPlus™ User Group Steering Committee, new Absorption, Distribution, Metabolism and Excretion knowledge is integrated and decision trees proposed for each essential component of a first-in-human prediction. We have reviewed many relevant scientific publications to identify new findings and highlight gaps that need to be addressed. Finally, four industry case studies for more challenging compounds illustrate and highlight key components of the strategy.

CYP2C9, a Metabolic CYP450s Enzyme, Plays Critical Roles in Activating Ellagic Acid in Human Intestinal Epithelial Cells

Background

The metabolic processing of ellagic acid (EA) by cytochrome P450s (CYP450s) expressed in the intestines is unclear. This study aimed to investigate the effects of CYP450s that are highly expressed in HIEC cells on metabolic activity of EA.

Material/Methods

HIEC cell models expressing 2B6, 2C9, 2D6, and 3A4 were generated by stably transfecting with CYP450 genes using a lentivirus system. PCR and Western blot assay were used to detect expression of CYP450s. Cell Counting Kit-8 (CCK-8) assay was used to examine the cytotoxic effect of EA on CYP450s-expressing HIEC cells. Flow cytometry was employed to evaluate apoptosis of CYP450s-expressing HIEC cells after addition of EA. Metabolic clearance rate of EA in vitro by the constructed HIEC cell models was measured using UPLC-MS method.

Results

CYP450s expression HIEC cell models, including CYP2B6, CYP2C9, CYP2D6, and CYP3A4, were successfully established. EA treatment at different concentrations (10 μg/mL and 50 μg/mL) remarkably decreased cell viability of HIEC cells expressing CYP2C9 compared to the untreated control (p<0.01), in a concentration-dependent and time-dependent manner. Expression of CYP2C9 significantly increased the apoptosis rate of HIEC cells treated with EA compared to that in HIEC cells without any CYP450s expression (p<0.01). The clearance rate of EA in CYP2B6-expressing (p<0.05) and CYP2C9-expressing (p<0.001) HIEC cell models was remarkably reduced after 120 min.

Conclusions

Ellagic acid was effectively activated by CYP2C9 in HIEC cells and caused cytotoxicity and apoptosis of HIEC cells. Therefore, CYP2C9 is main metabolic enzyme of EA when compared to other CYP450 HIEC cell models.

A mechanistic modelling approach for the determination of the mechanisms of inhibition by cyclosporine on the uptake and metabolism of atorvastatin in rat hepatocytes using a high throughput uptake method

Determine the inhibition mechanism through which cyclosporine inhibits the uptake and metabolism of atorvastatin in fresh rat hepatocytes using mechanistic models applied to data generated using a high throughput oil spin method.Atorvastatin was incubated in fresh rat hepatocytes (0.05-150 nmol/ml) with or without 20 min pre-incubation with 10 nmol/ml cyclosporine and sampled over 0.25-60 min using a high throughput oil spin method. Micro-rate constant and macro-rate constant mechanistic models were ranked based on goodness of fit values.The best fitting model to the data was a micro-rate constant mechanistic model including non-competitive inhibition of uptake and competitive inhibition of metabolism by cyclosporine (Model 2). The association rate constant for atorvastatin was 150-fold greater than the dissociation rate constant and 10-fold greater than the translocation into the cell. The association and dissociation rate constants for cyclosporine were 7-fold smaller and 10-fold greater, respectively, than atorvastatin. The simulated atorvastatin-transporter-cyclosporine complex derived using the micro-rate constant parameter estimates increased in line with the incubation concentration of atorvastatin.The increased amount of data generated with the high throughput oil spin method, combined with a micro-rate constant mechanistic model helps to explain the inhibition of uptake by cyclosporine following pre-incubation.