HLM chip - A microfluidic approach to study the mechanistic basis of cytochrome P450 inhibition using immobilized human liver microsomes

Cytochrome P450 (CYP) system is a critical elimination route to most pharmaceuticals in human, but also prone to drug-drug interactions arising from the fact that concomitantly administered pharmaceuticals inhibit one another's CYP metabolism. The most severe form of CYP interactions is irreversible inhibition, which results in permanent inactivation of the critical CYP pathway and is only restored by de novo synthesis of new functional enzymes. In this study, we conceptualize a microfluidic approach to mechanistic CYP inhibition studies using human liver microsomes (HLMs) immobilized onto the walls of a polymer micropillar array. We evaluated the feasibility of these HLM chips for CYP inhibition studies by establishing the stability and the enzyme kinetics for a CYP2C9 model reaction under microfluidic flow and determining the half-maximal inhibitory concentrations (IC50) of three human CYP2C9 inhibitors (sulfaphenazole, tienilic acid, miconazole), including evaluation of their inhibition mechanisms and nonspecific microsomal binding on chip. Overall, the enzyme kinetics of CYP2C9 metabolism on the HLM chip (KM = 127 ± 55 µM) was shown to be similar to that of static HLM incubations (KM = 114 ± 14 µM) and the IC50 values toward CYP2C9 derived from the microfluidic assays (sulfaphenazole 0.38 ± 0.09 µM, tienilic acid 3.4 ± 0.6 µM, miconazole 0.54 ± 0.09 µM) correlated well with those determined using current standard IC50 shift assays. Most importantly, the HLM chip could distinguish between reversible (sulfaphenazole) and irreversible (tienilic acid) enzyme inhibitors in a single, automated experiment, indicating the great potential of the HLM chip to simplify current workflows used in mechanistic CYP inhibition studies. Furthermore, the results suggest that the HLM chip can also identify irreversible enzyme inhibitors, which are not necessarily resulting in a time-dependent inhibition (like suicide inhibitors), but whose inhibition mechanism is based on other kind of covalent or irreversible interaction with the CYP system. With our HLM chip approach, we could identify miconazole as such a compound that nonselectively inhibits the human CYP system with a prolonged, possibly irreversible impact in vitro, even if it is not a time-dependent inhibitor according to the IC50 shift assay.

In vitro and in vivo studies on the metabolism and pharmacokinetics of the selective gut microbial β-glucuronidase targeting compound Inh 1

1. In vitro studies using rat, mouse and human microsomes and hepatocytes on the bacterial β-glucuronidase inhibitor (1-((6,8-dimethyl-2-oxo-1,2-dihydroquinolin-3-yl)methyl)-3-(4-ethoxyphenyl)-1-(2-hydroxyethyl)thiourea) (Inh 1) revealed extensive metabolism in all species.2. The intrinsic clearances of Inh 1 in human, mouse and rat hepatic microsomes were 30.9, 67.8 and 201 µL/min/mg, respectively. For intact hepatocytes intrinsic clearances of 21.6, 96.0 and 129 µL/min/106 cells were seen for human, mouse and rat, respectively.3. The metabolism of Inh 1 involved an uncommon desulphurisation reaction in addition to oxidation, deethylation and conjugation reactions at multiple sites. Six metabolites were detected in microsomal incubations in human and rat, and seven for the mouse. With hepatocytes, eighteen metabolites were characterised, nine for human, and eleven for mouse and rat.4. Following IV administration to mice (3 mg/kg), plasma concentrations of Inh 1 declined bi-exponentially with a terminal elimination half-life of 0.91 h and low systemic clearance (11.8% of liver blood flow). After PO dosing to mice (3 mg/kg), peak observed Inh 1 concentrations of 495 ng/ml were measured 0.5 hr post dose, declining to under 10 ng/ml at 8 hr post dose. The absolute oral bioavailability of Inh 1in the mouse was ca. 26%.

From hazard to risk prioritization: a case study to predict drug-induced cholestasis using physiologically based kinetic modeling

Cholestasis is characterized by hepatic accumulation of bile acids. Clinical manifestation of cholestasis only occurs in a small proportion of exposed individuals. The present study aims to develop a new approach methodology (NAM) to predict drug-induced cholestasis as a result of drug-induced hepatic bile acid efflux inhibition and the resulting bile acid accumulation. To this end, hepatic concentrations of a panel of drugs were predicted by a generic physiologically based kinetic (PBK) drug model. Their effects on hepatic bile acid efflux were incorporated in a PBK model for bile acids. The predicted bile acid accumulation was used as a measure for a drug's cholestatic potency. The selected drugs were known to inhibit hepatic bile acid efflux in an assay with primary suspension-cultured hepatocytes and classified as common, rare, or no for cholestasis incidence. Common cholestasis drugs included were atorvastatin, chlorpromazine, cyclosporine, glimepiride, ketoconazole, and ritonavir. The cholestasis incidence of the drugs appeared not to be adequately predicted by their Ki for inhibition of hepatic bile acid efflux, but rather by the AUC of the PBK model predicted internal hepatic drug concentration at therapeutic dose level above this Ki. People with slower drug clearance, a larger bile acid pool, reduced bile salt export pump (BSEP) abundance, or given higher than therapeutic dose levels were predicted to be at higher risk to develop drug-induced cholestasis. The results provide a proof-of-principle of using a PBK-based NAM for cholestasis risk prioritization as a result of transporter inhibition and identification of individual risk factors.

Comparison of Human Long-Term Liver Models for Clearance Prediction of Slowly Metabolized Compounds

The accurate prediction of human clearance is an important task during drug development. The proportion of low clearance compounds has increased in drug development pipelines across the industry since such compounds may be dosed in lower amounts and at lower frequency. These type of compounds present new challenges to in vitro systems used for clearance extrapolation. In this study, we compared the accuracy of clearance predictions of suspension culture to four different long-term stable in vitro liver models, including HepaRG sandwich culture, the Hµrel stochastic co-culture, the Hepatopac micropatterned co-culture (MPCC), and a micro-array spheroid culture. Hepatocytes in long-term stable systems remained viable and active over several days of incubation. Although intrinsic clearance values were generally high in suspension culture, clearance of low turnover compounds could frequently not be determined using this method. Metabolic activity and intrinsic clearance values from HepaRG cultures were low and, consequently, many compounds with low turnover did not show significant decline despite long incubation times. Similarly, stochastic co-cultures occasionally failed to show significant turnover for multiple low and medium turnover compounds. Among the different methods, MPCCs and spheroids provided the most consistent measurements. Notably, all culture methods resulted in underprediction of clearance; this could, however, be compensated for by regression correction. Combined, the results indicate that spheroid culture as well as the MPCC system provide adequate in vitro tools for human extrapolation for compounds with low metabolic turnover. SIGNIFICANCE STATEMENT: In this study, we compared suspension cultures, HepaRG sandwich cultures, the Hµrel liver stochastic co-cultures, the Hepatopac micropatterned co-cultures (MPCC), and micro-array spheroid cultures for low clearance determination and prediction. Overall, HepaRG and suspension cultures showed modest value for the low determination and prediction of clearance compounds. The micro-array spheroid culture resulted in the most robust clearance measurements, whereas using the MPCC resulted in the most accurate prediction for low clearance compounds.

Comparison of Commonly Used and New Methods to Determine Small Molecule Non-Specific Binding to Human Liver Microsomes

Accurate measurement of non-specific binding of a drug candidate to human liver microsomes (HLM) can be critical for the accurate determination of key enzyme kinetic parameters such as Michaelis-Menton (Km), reversible inhibition (Ki), or inactivation (KI) constants. Several methods have been developed to determine non-specific binding of small molecules to HLM, such as rapid equilibrium dialysis (RED), ultrafiltration (UF), HLM bound to magnetizable beads (HLM-beads), ultracentrifugation (UC), the linear extrapolation stability assay (LESA), and the Transil™ system. Despite various differences in methodology between these methods, it is generally presumed that similar free fraction values (fu,mic) should be generated. To evaluate this hypothesis, a test set of 9 compounds were selected, representing low (high fu,mic value) and significant (low fu,mic value) HLM binding, respectively, across HLM concentrations tested in this manuscript. The fu,mic values were determined using a single compound concentration (1.0 µM) and three HLM concentrations (0.025, 0.50, and 1.0 mg/mL). When the HLM non-specific binding event is not extensive resulting in high fu,mic values, all methods generated similar fu,mic values. However, fu,mic values varied markedly across assay formats when high binding to HLM occurred, where fu,mic values differed by up to 33-fold depending on the method used. Potential causes for such discrepancies across the various methods employed, practical implications related to conduct the different assays, and implications to clinical drug-drug interaction (DDI) predictions are discussed.

Mechanobiological stimulation in organ-on-a-chip systems reduces hepatic drug metabolic capacity in favor of regenerative specialization

Hepatic physiology depends on the liver's complex structural composition which among others, provides high oxygen supply rates, locally differential oxygen tension, endothelial paracrine signaling, as well as residual hemodynamic shear stress to resident hepatocytes. While functional improvements were shown by implementing these factors into hepatic culture systems, direct cause-effect relationships are often not well characterized-obfuscating their individual contribution in more complex microphysiological systems. By comparing increasingly complex hepatic in vitro culture systems that gradually implement these parameters, we investigate the influence of the cellular microenvironment to overall hepatic functionality in pharmacological applications. Here, hepatocytes were modulated in terms of oxygen tension and supplementation, endothelial coculture, and exposure to fluid shear stress delineated from oxygen influx. Results from transcriptomic and metabolomic evaluation indicate that particularly oxygen supply rates are critical to enhance cellular functionality-with cellular drug metabolism remaining comparable to physiological conditions after prolonged static culture. Endothelial signaling was found to be a major contributor to differential phenotype formation known as metabolic zonation, indicated by WNT pathway activity. Lastly, oxygen-delineated shear stress was identified to direct cellular fate towards increased hepatic plasticity and regenerative phenotypes at the cost of drug metabolic functionality - in line with regenerative effects observed in vivo. With these results, we provide a systematic evaluation of critical parameters and their impact in hepatic systems. Given their adherence to physiological effects in vivo, this highlights the importance of their implementation in biomimetic devices, such as organ-on-a-chip systems. Considering recent advances in basic liver biology, direct translation of physiological structures into in vitro models is a promising strategy to expand the capabilities of pharmacological models.

Aminobenzotriazole inhibits and induces several key drug metabolizing enzymes complicating its utility as a pan CYP inhibitor for reaction phenotyping

Aminobenzotriazole (ABT) is commonly used as a non-selective inhibitor of cytochrome P450 (CYP) enzymes to assign contributions of CYP versus non-CYP pathways to the metabolism of new chemical entities. Despite widespread use, a systematic review of the drug-drug interaction (DDI) potential for ABT has not been published nor have the implications for using it in plated hepatocyte models for low clearance reaction phenotyping. The goal being to investigate the utility of ABT as a pan-CYP inhibitor for reaction phenotyping of low clearance compounds by evaluating stability over the incubation period, inhibition potential against UGT and sulfotransferase enzymes, and interaction with nuclear receptors involved in the regulation of drug metabolizing enzymes and transporters. Induction potential for additional inhibitors used to ascribe fraction metabolism (fm ), pathway including erythromycin, ketoconazole, azamulin, atipamezole, ZY12201, and quinidine was also investigated. ABT significantly inhibited the clearance of a non-selective UGT substrate 4-methylumbelliferone, with several UGTs shown to be inhibited using selective probe substrates in human hepatocytes and rUGTs. The inhibitors screened in the induction assay were shown to induce enzymes regulated through Aryl Hydrocarbon Receptor, Constitutive Androstane Receptor, and Pregnane X Receptor. Lastly, a case study identifying the mechanisms of a clinical DDI between Palbociclib and ARV-471 is provided as an example of the potential consequences of using ABT to derive fm . This work demonstrates that ABT is not an ideal pan-CYP inhibitor for reaction phenotyping of low clearance compounds and establishes a workflow that can be used to enable robust characterization of other prospective inhibitors.

Creation of Novel Sensitive Probe Substrate and Moderate Inhibitor Models for a Comprehensive Prediction of CYP2C8 Interactions for Tucatinib

A physiologically-based pharmacokinetic (PBPK) model was developed to simulate plasma concentrations of tucatinib (TUKYSA®) after single-dose or multiple-dose administration of 300 mg b.i.d. orally. This PBPK model was subsequently applied to support evaluation of drug-drug interaction (DDI) risk as a perpetrator resulting from tucatinib inhibition of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was also applied to support evaluation of DDI risk as a victim resulting from co-administration with CYP3A4 or CYP2C8 inhibitors, or a CYP3A4 inducer. After refinement with clinical DDI data, the final PBPK model was able to recover the clinically observed single and multiple-dose plasma concentrations for tucatinib when tucatinib was administered as a single agent in healthy subjects. In addition, the final model was able to recover clinically observed plasma concentrations of tucatinib when administered in combination with itraconazole, rifampin, or gemfibrozil as well as clinically observed plasma concentrations of probe substrates of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was then applied to prospectively predict the potential perpetrator or victim DDIs with other substrates, inducers, or inhibitors. To simulate a potential interaction with a moderate CYP2C8 inhibitor, two novel PBPK models representing a moderate CYP2C8 inhibitor and a sensitive CYP2C8 substrate were developed based on the existing PBPK models for gemfibrozil and rosiglitazone, respectively. The simulated population geometric mean area under the curve ratio of tucatinib with a moderate CYP2C8 inhibitor ranged from 1.98- to 3.08-fold, and based on these results, no dose modifications were proposed for moderate CYP2C8 inhibitors for the tucatinib label.

Prediction of CYP Down Regulation after Tusamitamab Ravtansine Administration (a DM4-Conjugate), Based on an In Vitro-In Vivo Extrapolation Approach

Tusamitamab ravtansine is an antibody-drug conjugate (ADC) composed of a humanized monoclonal antibody (IgG1) and DM4 payload. Even if DM4 and its main metabolite methyl-DM4 (Me-DM4) circulate at low concentrations after ADC administration, their potential as perpetrators of cytochrome P450 mediated drug-drug interaction was assessed. In vitro studies in human hepatocytes indicated that Me-DM4 elicited a clear concentration-dependent down regulation of cytochrome P450 enzymes (CYP3A4, 1A2, and 2B6). Because DM4 was unstable under the incubation conditions studied, the in vitro constants could not be determined for this entity. Thus, to predict the clinical relevance of this observed downregulation, an in vitro-in vivo extrapolation (IVIVE) pharmacokinetic (PK) based approach was developed. To mitigate model prediction errors and because of their similar inhibitory effect on tubulin polymerization, the same downregulation constants were used for DM4 and Me-DM4. This approach describes the time course of decreasing CYP3A4, 1A2, and 2B6 enzyme amounts as a function of circulating concentrations of DM4 and Me-DM4 predicted from a population PK model. The developed IVIVE-PK model showed that the highest CYP abundance decrease was observed for CYP3A4, with a transient reduction of < 10% from baseline. The impact on midazolam exposure, as probe substrate of CYP3A, was then simulated based on a physiologically-based PK static method. The maximal CYP3A4 abundance reduction was associated with a predicted midazolam area under the curve (AUC) ratio of 1.14. To conclude, the observed in vitro downregulation of CYPs by Me-DM4 is not expected to have relevant clinical impact.

DNDI-6174 is a preclinical candidate for visceral leishmaniasis that targets the cytochrome bc1

New drugs for visceral leishmaniasis that are safe, low cost, and adapted to the field are urgently required. Despite concerted efforts over the last several years, the number of new chemical entities that are suitable for clinical development for the treatment of Leishmania remains low. Here, we describe the discovery and preclinical development of DNDI-6174, an inhibitor of Leishmania cytochrome bc1 complex activity that originated from a phenotypically identified pyrrolopyrimidine series. This compound fulfills all target candidate profile criteria required for progression into preclinical development. In addition to good metabolic stability and pharmacokinetic properties, DNDI-6174 demonstrates potent in vitro activity against a variety of Leishmania species and can reduce parasite burden in animal models of infection, with the potential to approach sterile cure. No major flags were identified in preliminary safety studies, including an exploratory 14-day toxicology study in the rat. DNDI-6174 is a cytochrome bc1 complex inhibitor with acceptable development properties to enter preclinical development for visceral leishmaniasis.

In vitro and in vivo pharmacokinetic characterization, chiral conversion and PBPK scaling towards human PK simulation of S-MRI-1867, a drug candidate for Hermansky-Pudlak syndrome pulmonary fibrosis

Hermansky-Pudlak syndrome (HPS) is a rare autosomal recessive disorder that affects lysosome-related organelles, often leading to fatal pulmonary fibrosis (PF). The search for a treatment for HPS pulmonary fibrosis (HPSPF) is ongoing. S-MRI-1867, a dual cannabinoid receptor 1 (CB1R)/inducible nitric oxide synthase (iNOS) inhibitor, has shown great promise for the treatment of several fibrotic diseases, including HPSPF. In this study, we investigated the in vitro ADME characteristics of S-MRI-1867, as well as its pharmacokinetic (PK) properties in mice, rats, dogs, and monkeys. S-MRI-1867 showed low aqueous solubility (< 1 µg/mL), high plasma protein binding (>99%), and moderate to high metabolic stability. In its preclinical PK studies, S-MRI-1867 exhibited moderate to low plasma clearance (CLp) and high steady-state volume of distribution (Vdss) across all species. Despite the low solubility and P-gp efflux, S-MRI-1867 showed great permeability and metabolic stability leading to a moderate bioavailability (21-60%) across mouse, rat, dog, and monkey. Since the R form of MRI-1867 is CB1R-inactive, we investigated the potential conversion of S-MRI-1867 to R-MRI-1867 in mice and found that the chiral conversion was negligible. Furthermore, we developed and validated a PBPK model that adequately fits the PK profiles of S-MRI-1867 in mice, rats, dogs, and monkeys using various dosing regimens. We employed this PBPK model to simulate the human PK profiles of S-MRI-1867, enabling us to inform human dose selection and support the advancement of this promising drug candidate in the treatment of HPSPF.

Challenges and Opportunities for In Vitro-In Vivo Extrapolation of Aldehyde Oxidase-Mediated Clearance: Toward a Roadmap for Quantitative Translation

Underestimation of aldehyde oxidase (AO)-mediated clearance by current in vitro assays leads to uncertainty in human dose projections, thereby reducing the likelihood of success in drug development. In the present study we first evaluated the current drug development practices for AO substrates. Next, the overall predictive performance of in vitro-in vivo extrapolation of unbound hepatic intrinsic clearance (CLint,u) and unbound hepatic intrinsic clearance by AO (CLint,u,AO) was assessed using a comprehensive literature database of in vitro (human cytosol/S9/hepatocytes) and in vivo (intravenous/oral) data collated for 22 AO substrates (total of 100 datapoints from multiple studies). Correction for unbound fraction in the incubation was done by experimental data or in silico predictions. The fraction metabolized by AO (fmAO) determined via in vitro/in vivo approaches was found to be highly variable. The geometric mean fold errors (gmfe) for scaled CLint,u (mL/min/kg) were 10.4 for human hepatocytes, 5.6 for human liver cytosols, and 5.0 for human liver S9, respectively. Application of these gmfe's as empirical scaling factors improved predictions (45%-57% within twofold of observed) compared with no correction (11%-27% within twofold), with the scaling factors qualified by leave-one-out cross-validation. A road map for quantitative translation was then proposed following a critical evaluation on the in vitro and clinical methodology to estimate in vivo fmAO In conclusion, the study provides the most robust system-specific empirical scaling factors to date as a pragmatic approach for the prediction of in vivo CLint,u,AO in the early stages of drug development. SIGNIFICANCE STATEMENT: Confidence remains low when predicting in vivo clearance of AO substrates using in vitro systems, leading to de-prioritization of AO substrates from the drug development pipeline to mitigate risk of unexpected and costly in vivo impact. The current study establishes a set of empirical scaling factors as a pragmatic tool to improve predictability of in vivo AO clearance. Developing clinical pharmacology strategies for AO substrates by utilizing mass balance/clinical drug-drug interaction data will help build confidence in fmAO.

Shared learning from a physiologically based pharmacokinetic modeling strategy for human pharmacokinetics prediction through retrospective analysis of Genentech compounds

The quantitative prediction of human pharmacokinetics (PK) including the PK profile and key PK parameters are critical for early drug development decisions, successful phase I clinical trials, and the establishment of a range of doses to enable phase II clinical dose selection. Here, we describe an approach employing physiologically based pharmacokinetic (PBPK) modeling (Simcyp) to predict human PK and to validate its performance through retrospective analysis of 18 Genentech compounds for which clinical data are available. In short, physicochemical parameters and in vitro data for preclinical species were integrated using PBPK modeling to predict the in vivo PK observed in mouse, rat, dog, and cynomolgus monkey. Through this process, the in vitro to in vivo extrapolation (IVIVE) was determined and then incorporated into PBPK modeling in order to predict human PK. Overall, the prediction obtained using this PBPK-IVIVE approach captured the observed human PK profiles of the compounds from the dataset well. The predicted Cmax was within 2-fold of the observed Cmax for 94% of the compounds while the predicted area under the curve (AUC) was within 2-fold of the observed AUC for 72% of the compounds. Additionally, important IVIVE trends were revealed through this investigation, including application of scaling factors determined from preclinical IVIVE to human PK prediction for each molecule. Based upon the analysis, this PBPK-based approach now serves as a practical strategy for human PK prediction at the candidate selection stage at Genentech.

Plasma Protein-Mediated Uptake and Contradictions to the Free Drug Hypothesis: A Critical Review

According to the free drug hypothesis (FDH), only free, unbound drug is available to interact with biological targets. This hypothesis is the fundamental principle that continues to explain the vast majority of all pharmacokinetic and pharmacodynamic processes. Under the FDH, the free drug concentration at the target site is considered the driver of pharmacodynamic activity and pharmacokinetic processes. However, deviations from the FDH are observed in hepatic uptake and clearance predictions, where observed unbound intrinsic hepatic clearance (CL_int,u) is larger than expected. Such deviations are commonly observed when plasma proteins are present and form the basis of the so-called plasma protein-mediated uptake effect (PMUE). This review will discuss the basis of plasma protein binding as it pertains to hepatic clearance based on the FDH, as well as several hypotheses that may explain the underlying mechanisms of PMUE. Notably, some, but not all, potential mechanisms remained aligned with the FDH. Finally, we will outline possible experimental strategies to elucidate PMUE mechanisms. Understanding the mechanisms of PMUE and its potential contribution to clearance underprediction is vital to improving the drug development process.

Simplifying the Extended Clearance Concept Classification System (EC3S) to Guide Clearance Prediction in Drug Discovery

PURPOSE

The 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.

METHODS

A 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.

RESULTS

The 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.

CONCLUSION

Collectively, 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.

Investigation of the Pharmacokinetics and Metabolic Fate of Fasiglifam (TAK-875) in Male and Female Rats Following Oral and Intravenous Administration

The metabolism and pharmacokinetics of fasiglifam (TAK-875, 2-[(3S)-6-[[3-[2,6-dimethyl-4-(3-methylsulfonylpropoxy)phenyl]phenyl]methoxy]-2,3-dihydro-1-benzofuran-3-yl]acetic acid), a selective free fatty acid receptor 1 (FFAR1)/GPR40 agonist, were studied following intravenous (5 mg/kg) and oral administration (10 and 50 mg/kg) to male and female Sprague Dawley rats.Following intravenous dosing at 5 mg/kg, peak observed plasma concentrations of 8.8/9.2 μg/ml were seen in male and female rats respectively.Following oral dosing, peak plasma concentrations at 1 h of ca. 12.4/12.9 μg/ml for 10 mg/kg and 76.2/83.7 μg/ml for 50 mg/kg doses were obtained for male and female rats respectively. Drug concentrations then declined in the plasma of both sexes with t_1/2's of 12.4 (male) and 11.2 h (female). Oral bioavailability was estimated to be 85-120% in males and females at both dose levels.Urinary excretion was low, but in a significant sex-related difference, female rats eliminated ca. 10-fold more drug-related material by this route.Fasiglifam was the principal drug-related compound in plasma, with 15 metabolites, including the acyl glucuronide, also detected. In addition to previously identified metabolites, a novel biotransformation, that produced a side-chain shortened metabolite via elimination of CH₂ from the acetyl side chain was noted with implications for drug toxicity.

Translational PK/PD Modeling of Tumor Growth Inhibition and Target Inhibition to Support Dose Range Selection of the LMP7 Inhibitor M3258 in Relapsed/Refractory Multiple Myeloma

M3258 is an orally bioavailable, potent, selective, reversible inhibitor of the large multifunctional peptidase 7 (LMP7, β5i, PSMB8) proteolytic subunit of the immunoproteasome, a component of the cellular protein degradation machinery, highly expressed in malignant hematopoietic cells including multiple myeloma. Here we describe the fit-for-purpose pharmacokinetic (PK)/pharmacodynamic (PD)/efficacy modeling of M3258 based on preclinical data from several species. The inhibition of LMP7 activity (PD) and tumor growth (efficacy) were tested in human multiple myeloma xenografts in mice. PK and efficacy data were correlated yielding a free M3258 concentration of 45 nM for half-maximal tumor growth inhibition (KC₅₀). As M3258 only weakly inhibits LMP7 in mouse cells, both in vitro and in vivo bridging studies were performed in rats, monkeys, and dogs for translational modeling. These data indicated that the PD response in human xenograft models was closely reflected in dog PBMCs. A PK/PD model was established, predicting a free IC₅₀ value of 9 nM for M3258 in dogs in vivo, in close agreement with in vitro measurements. In parallel, the human PK parameters of M3258 were predicted by various approaches including in vitro extrapolation and allometric scaling. Using PK/PD/efficacy simulations, the efficacious dose range and corresponding PD response in human were predicted. Taken together, these efforts supported the design of a phase Ia study of M3258 in multiple myeloma patients (NCT04075721). At the lowest tested dose level, the predicted exposure matched well with the observed exposure while the duration of LMP7 inhibition was underpredicted by the model. SIGNIFICANCE STATEMENT: M3258 is a novel inhibitor of the immunoproteasome subunit LMP7. The human PK and human efficacious dose range of M3258 were predicted using in vitro-in vivo extrapolation and allometric scaling methods together with a fit-for-purpose PK/PD and efficacy model based on data from several species. A comparison with data from the Phase Ia clinical study showed that the human PK was accurately predicted, while the extent and duration of PD response were more pronounced than estimated.

Analysis of Time-Dependent Pharmacokinetics Using In Vitro-In Vivo Extrapolation and Physiologically Based Pharmacokinetic Modeling

SCR430, a sorafenib derivative, is an investigational drug exhibiting anti-tumor action. This study aimed to have a mechanistic understanding of SCR430's time-dependent pharmacokinetics (TDPK) through an ex vivo study combined with an in vitro-in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) modeling. A non-compartmental pharmacokinetic analysis was performed after intravenous SCR430 administration in female Sprague-Dawley rats for a control group (no treatment), a vehicle group (vehicle only, 14 days, PO), and a repeated-dosing group (SCR430, 30 mg/kg/day, 14 days, PO). In addition, hepatic uptake and metabolism modulation were investigated using isolated hepatocytes from each group of rats. The minimal PBPK model based on IVIVE was constructed to explain SCR430's TDPK. Repeated SCR430 administration decreased the systemic exposure by 4.4-fold, which was explained by increased hepatic clearance (4.7-fold). The ex vivo study using isolated hepatocytes from each group suggested that the increased hepatic uptake (9.4-fold), not the metabolic activity, contributes to the increased hepatic clearance. The minimal PBPK modeling based on an ex vivo study could explain the decreased plasma levels after the repeated doses. The current study demonstrates the TDPK after repeated dosing by hepatic uptake induction, not hepatic metabolism, as well as the effectiveness of an ex vivo approach combined with IVIVE and PBPK modeling to investigate the TDPK.

LipMetE (Lipophilic Metabolism Efficiency) as a Simple Guide for Half-Life and Dosing Regimen Prediction of Oral Drugs

The in vivo half-life is a key property of every drug molecule, as it determines dosing regimens, peak-to-trough ratios and often dose. However, half-life optimization can be challenging due to its multifactorial nature, with in vitro metabolic turnover, plasma protein binding and volume of distribution all impacting half-life. We here propose that the medicinal chemistry design parameter Lipophilic Metabolism Efficiency (LipMetE) can greatly simplify half-life optimization of neutral and basic compounds. Using mathematical transformations, examples from preclinical GABAA projects and clinical compounds with human pharmacokinetic data, we show that LipMetE is directly proportional to the logarithm of half-life. As the design parameter LipMetE can be swiftly calculated using the readily available parameters LogD, intrinsic clearance and fraction unbound in human liver microsomes or hepatocytes, this approach enables rational half-life optimization from the early stages of drug discovery projects.

SimRFlow: An R-based workflow for automated high-throughput PBPK simulation with the Simcyp® simulator

SimRFlow is a high-throughput physiologically based pharmacokinetic (PBPK) modelling tool which uses Certara’s Simcyp® simulator. The workflow is comprised of three main modules: 1) a Data Collection module for automated curation of physicochemical (from ChEMBL and the Norman Suspect List databases) and experimental data (i.e.: clearance, plasma-protein binding, and blood-to-plasma ratio, from httk-R package databases), 2) a Simulation module which activates the Simcyp® simulator and runs Monte Carlo simulations on virtual subjects using the curated data, and 3) a Data Visualisation module for understanding the simulated compound-specific profiles and predictions. SimRFlow has three administration routes (oral, intravenous, dermal) and allows users to change some simulation parameters including the number of subjects, simulation duration, and dosing. Users are only expected to provide a file of the compounds they wish to simulate, and in return the workflow provides summary statistics, concentration-time profiles of various tissue types, and a database file (containing in-depth results) for each simulated compound. This is presented within a guided and easy-to-use R Shiny interface which provides many plotting options for the visualisation of concentration-time profiles, parameter distributions, trends between the different parameters, as well as comparison of predicted parameters across all batch-simulated compounds. The in-built R functions can be assembled in user-customised scripts which allows for the modification of the workflow for different purposes. SimRFlow proves to be a time-efficient tool for simulating a large number of compounds without any manual curation of physicochemical or experimental data necessary to run Simcyp® simulations.

Characterization of intravenous pharmacokinetics in Göttingen minipig and clearance prediction using established in vitro to in vivo extrapolation methodologies

1. The use of the Göttingen minipig as an animal model for drug safety testing and prediction of human pharmacokinetics (PK) continues to gain momentum in pharmaceutical research and development. The aim of this study was to evaluate in vitro to in vivo extrapolation (IVIVE) methodologies for prediction of hepatic, metabolic clearance (CL_hep,met) in Göttingen minipig, using a comprehensive set of compounds.2. In vivo clearance was determined in Göttingen minipig by intravenous cassette dosing and hepatocyte intrinsic clearance, plasma protein binding and non-specific incubation binding were determined in vitro. Prediction of CL_hep,met was performed by IVIVE using conventional and adapted formats of the well-stirred liver model.3. The best prediction of in vivo CL_hep,met from scaled in vitro kinetic data was achieved using an empirical correction factor based on a 'regression offset' of the IVIV relationship.4. In summary, these results expand the in vitro and in vivo PK knowledge in Göttingen minipig. We show regression corrected IVIVE provides superior prediction of in vivo CL_hep,met in minipig offering a practical, unified scaling approach to address systematic under-predictions. Finally, we propose a reference set for researchers to establish their own 'lab-specific' regression correction for IVIVE in minipig.

Non-specific binding of compounds in in vitro metabolism assays: a comparison of microsomal and hepatocyte binding in different species and an assessment of the accuracy of prediction models

Non-specific binding in in vitro metabolism systems leads to an underestimation of the true intrinsic metabolic clearance of compounds being studied. Therefore in vitro binding needs to be accounted for when extrapolating in vitro data to predict the in vivo metabolic clearance of a compound. While techniques exist for experimentally determining the fraction of a compound unbound in in vitro metabolism systems, early in drug discovery programmes computational approaches are often used to estimate the binding in the in vitro system.Experimental fraction unbound data (n = 60) were generated in liver microsomes (fu_mic) from five commonly used pre-clinical species (rat, mouse, dog, minipig, monkey) and humans. Unbound fraction in incubations with mouse, rat or human hepatocytes was determined for the same 60 compounds. These data were analysed to determine the relationship between experimentally determined binding in the different matrices and across different species. In hepatocytes there was a good correlation between fraction unbound in human and rat (r²=0.86) or mouse (r²=0.82) hepatocytes. Similar correlations were observed between binding in human liver microsomes and microsomes from rat, mouse, dog, Göttingen minipig or monkey liver microsomes (r² of >0.89, n = 51 - 52 measurements in different species). Physicochemical parameters (logP, pKa and logD) were predicted for all evaluated compounds. In addition, logP and/or logD were measured for a subset of compounds.Binding to human hepatocytes predicted using 5 different methods was compared to the measured data for a set of 59 compounds. The best methods evaluated used measured microsomal binding in human liver microsomes to predict hepatocyte binding. The collated physicochemical data were used to predict the human fu_mic using four different in silico models for a set of 53-60 compounds. The correlation (r²) and root mean square error between predicted and observed microsomal binding was 0.69 & 0.20, 0.47 & 0.23, 0.56 & 0.21 and 0.54 & 0.26 for the Turner-Simcyp, Austin, Hallifax-Houston and Poulin models, respectively. These analyses were extended to include measured literature values for binding in human liver microsomes for a larger set of compounds (n=697). For the larger dataset of compounds, microsomal binding was well predicted for neutral compounds (r²=0.67 - 0.70) using the Poulin, Austin, or Turner-Simcyp methods but not for acidic or basic compounds (r²<0.5) using any of the models. While the lipophilicity-based models can be used, the in vitro binding should be measured for compounds where more certainty is needed, using appropriately calibrated assays and possibly established weak, moderate, and strong binders as reference compounds to allow comparison across databases.

The in vitro metabolism and in vivo pharmacokinetics of the bacterial β-glucuronidase inhibitor UNC10201652

In vitro incubation of the bacterial β-glucuronidase inhibitor UNC10201652 (4-(8-(piperazin-1-yl)-1,2,3,4-tetrahydro-[1,2,3]triazino[4',5':4,5]thieno[2,3-c]isoquinolin-5-yl)morpholine) with mouse, rat, and human liver microsomes and hepatocytes generated metabolites at multiple sites via deethylations, oxidations and glucuronidation.Two UNC10201652 metabolites were detected in human, and four in mouse and rat liver microsomal incubations. Intrinsic clearances of UNC10201652 in human, mouse, and rat liver microsomes were 48.1, 115, and 194 µL/min/mg respectively.Intrinsic clearances for human, mouse, and rat hepatocytes were 20.9, 116, and 140 µL/min/106 cells respectively and 24 metabolites were characterised: 9 for human and 11 for both rodent species.Plasma clearance was 324.8 mL/min/kg with an elimination half-life of 0.66 h following IV administration of UNC10201652 to Swiss Albino mice (3 mg/kg). Pre-treatment with 1-aminobenzotriazole (ABT) decreased clearance to 127.43 mL/min/kg, increasing the t1/2 to 3.66 h.Comparison of profiles after oral administration of UNC10201652 to control and pre-treated mice demonstrated a large increase in Cmax (from 15.2 ng/mL to 184.0 ng/mL), a delay in Tmax from 0.25 to 1 h and increased AUC from 20.1 to 253 h ng/ml. ABT pre-treatment increased oral bioavailability from 15% to >100% suggesting that CYP450's contributed significantly to UNC10201652 clearance in mice.

Multi-Well Array Culture of Primary Human Hepatocyte Spheroids for Clearance Extrapolation of Slowly Metabolized Compounds

Accurate prediction of human pharmacokinetics using in vitro tools is an important task during drug development. Albeit, currently used in vitro systems for clearance extrapolation such as microsomes and primary human hepatocytes in suspension culture show reproducible turnover, the utility of these systems is limited by a rapid decline of activity of drug metabolizing enzymes. In this study, a multi-well array culture of primary human hepatocyte spheroids was compared to suspension and single spheroid cultures from the same donor. Multi-well spheroids remained viable and functional over the incubation time of 3 days, showing physiological excretion of albumin and α-AGP. Their metabolic activity was similar compared to suspension and single spheroid cultures. This physiological activity, the high cell concentration, and the prolonged incubation time resulted in significant turnover of all tested low clearance compounds (n = 8). In stark contrast, only one or none of the compounds showed significant turnover when single spheroid or suspension cultures were used. Using multi-well spheroids and a regression offset approach (log(CL_int) = 1.1 × + 0.85), clearance was predicted within 3-fold for 93% (13/14) of the tested compounds. Thus, multi-well spheroids represent a novel and valuable addition to the ADME in vitro tool kit for the determination of low clearance and overall clearance prediction. Graphical Abstract.

Predictive Performance of Next Generation Physiologically Based Kinetic (PBK) Model Predictions in Rats Based on In Vitro and In Silico Input Data

The goal of the present study was to assess the predictive performance of a minimal generic rat physiologically based kinetic (PBK) model based on in vitro and in silico input data to predict peak plasma concentrations (Cmax) upon single oral dosing. To this purpose, a dataset was generated of 3960 Cmax predictions for 44 compounds, applying different combinations of in vitro and in silico approaches for chemical parameterization, and comparison of the predictions to reported in vivo data. Best performance was obtained when (1) the hepatic clearance was parameterized based on in vitro measured intrinsic clearance values, (2) the method of Rodgers and Rowland for calculating partition coefficients, and (3) in silico calculated fraction unbound plasma and Papp values (the latter especially for very lipophilic compounds). Based on these input data, the median Cmax of 32 compounds could be predicted within 10-fold of the observed Cmax, with 22 out of these 32 compounds being predicted within 5-fold, and 8 compounds within 2-fold. Overestimations of more than 10-fold were observed for 12 compounds, whereas no underestimations of more than 10-fold occurred. Median Cmax predictions were frequently found to be within 10-fold of the observed Cmax when the scaled unbound hepatic intrinsic clearance (Clint,u) was either higher than 20 l/h or lower than 1 l/h. Similar findings were obtained with a test set of 5 in-house BASF compounds. Overall, this study provides relevant insights in the predictive performance of a minimal PBK model based on in vitro and in silico input data.

Predictive In Vitro-In Vivo Extrapolation for Time Dependent Inhibition of CYP1A2, CYP2C8, CYP2C9, CYP2C19 and CYP2D6 Using Pooled Human Hepatocytes, Human Liver Microsomes, and a Simple Mechanistic Static Model

Inactivation of Cytochrome P450 (CYP450) enzymes can lead to significant increases in exposure of co-medicants. The majority of reported in vitro to in vivo extrapolation (IVIVE) data have historically focused on CYP3A4 leaving the assessment of other CYP isoforms insubstantial. To this end, the utility of human hepatocytes (HHEP) and microsome (HLM) to predict clinically relevant DDIs was investigated with a focus on CYP1A2, CYP2C8, CYP2C9, CYP2C19 and CYP2D6. Evaluation of IVIVE for CYP2B6 was limited to only weak inhibition. A search of the University of Washington Drug-Drug Interaction Database was conducted to identify a clinically relevant weak, moderate and strong inhibitor for selective substrates of CYP1A2, CYP2C8, CYP2C9, CYP2C19 and CYP2D6, resulting in 18 inhibitors for in vitro characterization against 119 clinical interaction studies. Pooled human hepatocytes and HLM were pre-incubated with increasing concentrations of inhibitors for designated timepoints. Time dependent inhibition (TDI) was detected in HLM for four moderate/strong inhibitors suggesting that some optimization of incubation conditions (i.e. lower protein concentrations) is needed to capture weak inhibition. Clinical risk assessment was conducted by incorporating the in vitro derived kinetic parameters k_inact and K_I into static equations recommended by regulatory authorities. Significant overprediction was observed when applying the basic models recommended by regulatory agencies. Mechanistic static models (MSM), which consider the fraction of metabolism through the impacted enzyme, using the unbound hepatic inlet concentration lead to the best overall prediction accuracy with 92% and 85% of data from HHEPs and HLM, respectively, within 2-fold of the observed value. Significance Statement Collectively, the data demonstrate that coupling time-dependent inactivation parameters derived from pooled human hepatocytes and HLM with a mechanistic static model provides an easy and quantitatively accurate means to determine clinical DDI risk from in vitro data. Weak and moderate inhibitors did not show TDI under standard incubation conditions using HLM and optimization of incubation conditions is warranted. Recommendations are made with respect to input parameters for IVIVE of TDI with non-CYP3A enzymes using available data from HLM and HHEPs.

Reaction Phenotyping of Low-Turnover Compounds in Long-Term Hepatocyte Cultures Through Persistent Selective Inhibition of Cytochromes P450

Recognizing the challenges of determining the relative contribution of different drug metabolizing enzymes to the metabolism of slowly metabolized compounds, a cytochrome P450 reaction phenotyping (CRP) method using cocultured human hepatocytes (HEPATOPAC) has been established. In this study, the emphasis on the relative contribution of different cytochrome P450 (P450) isoforms was assessed by persistently inhibiting P450 isoforms over 7 days with human HEPATOPAC. P450 isoform-selective inhibition was achieved with the chemical inhibitors furafylline (CYP1A2), tienilic acid (CYP2C9), (+)-N-3-benzylnirvanol (CYP2C19), paroxetine (CYP2D6), azamulin (CYP3A), and a combination of 1-aminobenzotriazole and tienilic acid (broad spectrum inhibition of P450s). We executed this CRP method using HEPATOPAC by optimizing for the choice of P450 inhibitors, their selectivity, and the temporal effect of inhibitor concentrations on maintaining selectivity of inhibition. In general, the established CRP method using potent and selective chemical inhibitors allows to measure the relative contribution of P450s and to calculate the fraction of metabolism (f _m) of low-turnover compounds. Several low-turnover compounds were used to validate this CRP method by determining their hepatic intrinsic clearance and f _m, with comparison with literature values. We established the foundation of a robust CRP for low-turnover compound test system which can be expanded to include inhibition of other drug metabolizing enzymes. This generic CRP assay, using human long-term hepatocyte cultures, will be an essential tool in drug development for new chemical entities in the quantitative assessment of the risk as a victim of drug-drug interactions. SIGNIFICANCE STATEMENT: An ongoing trend is to develop drug candidates which have limited metabolic clearance. The current studies report a generic approach to conducting reaction phenotyping studies with human HEPATOPAC, focusing on P450 metabolism of low-turnover compounds. Potent and selective chemical inhibitors were used to assess the relative contribution of the major human P450s. Validation was achieved by confirming hepatic intrinsic clearance and fraction of metabolism for previously reported low-turnover compounds. This approach is adaptable for assessment of all drug metabolizing enzymes.

Predicting human pharmacokinetics from preclinical data: clearance

We have streamlined known in vitro methods used to predict the clearance (CL) of small molecules in humans in this tutorial. There have been many publications on in vitro methods that are used at different steps of human CL prediction. The steps from initial intrinsic CL measurement in vitro to the final application of the well-stirred model to obtain predicted hepatic CL (CL_H) are somewhat complicated. Except for the experts on drug metabolism and PBPK, many drug development scientists found it hard to figure out the entire picture of human CL prediction. To help readers overcome this barrier, we introduce each method briefly and demonstrate its usage in the chain of related equations destined to the CL_H. Despite efforts in the laboratory steps, huge in vitro (predicted CL_H)-in vivo (observed CL_H) discrepancy is not rare. A simple remedy to this discrepancy is to correct human predicted CL_H using the ratio of in vitro-in vivo CL_H obtained from animal species.

High-throughput PBTK models for in vitro to in vivo extrapolation

INTRODUCTION

Toxicity data are unavailable for many thousands of chemicals in commerce and the environment. Therefore, risk assessors need to rapidly screen these chemicals for potential risk to public health. High-throughput screening (HTS) for in vitro bioactivity, when used with high-throughput toxicokinetic (HTTK) data and models, allows characterization of these thousands of chemicals.

AREAS COVERED

This review covers generic physiologically based toxicokinetic (PBTK) models and high-throughput PBTK modeling for in vitro-in vivo extrapolation (IVIVE) of HTS data. We focus on 'httk', a public, open-source set of computational modeling tools and in vitro toxicokinetic (TK) data.

EXPERT OPINION

HTTK benefits chemical risk assessors with its ability to support rapid chemical screening/prioritization, perform IVIVE, and provide provisional TK modeling for large numbers of chemicals using only limited chemical-specific data. Although generic TK model design can increase prediction uncertainty, these models provide offsetting benefits by increasing model implementation accuracy. Also, public distribution of the models and data enhances reproducibility. For the httk package, the modular and open-source design can enable the tool to be used and continuously improved by a broad user community in support of the critical need for high-throughput chemical prioritization and rapid dose estimation to facilitate rapid hazard assessments.

Evaluation and comparison of in vitro intrinsic clearance rates measured using cryopreserved hepatocytes from humans, rats, and rainbow trout

In vitro and in silico methods that can reduce the need for animal testing are being used with increasing frequency to assess chemical risks to human health and the environment. The rate of hepatic biotransformation is an important species-specific parameter for determining bioaccumulation potential and extrapolating in vitro bioactivity to in vivo effects. One approach to estimating hepatic biotransformation is to employ in vitro systems derived from liver tissue to measure chemical (substrate) depletion over time which can then be translated to a rate of intrinsic clearance (CL_int). In the present study, cryopreserved hepatocytes from humans, rats, and rainbow trout were used to measure CL_int values for 54 industrial and pesticidal chemicals at starting test concentrations of 0.1 and 1 μM. A data evaluation framework that emphasizes the behavior of Heat-Treated Controls (HTC) was developed to identify datasets suitable for rate reporting. Measured or estimated ("greater than" or "less than") CL_int values were determined for 124 of 226 (55 %) species-chemical-substrate concentration datasets with acceptable analytical chemistry. A large percentage of tested chemicals exhibited low HTC recovery values, indicating a substantial abiotic loss of test chemical over time. An evaluation of K_OW values for individual chemicals suggested that in vitro test performance declined with increasing chemical hydrophobicity, although differences in testing devices for mammals and fish also likely played a role. The current findings emphasize the value of negative controls as part of a rigorous approach to data quality assessment for in vitro substrate depletion studies. Changes in current testing protocols can be expected to result in the collection of higher quality data. However, poorly soluble chemicals are likely to remain a challenge for CL_int determination.

Designing QSARs for Parameters of High-Throughput Toxicokinetic Models Using Open-Source Descriptors

The intrinsic metabolic clearance rate (Cl_int) and the fraction of the chemical unbound in plasma (f_up) serve as important parameters for high-throughput toxicokinetic (TK) models, but experimental data are limited for many chemicals. Open-source quantitative structure-activity relationship (QSAR) models for both parameters were developed to offer reliable in silico predictions for a diverse set of chemicals regulated under the U.S. law, including pharmaceuticals, pesticides, and industrial chemicals. As a case study to demonstrate their utility, model predictions served as inputs to the TK component of a risk-based prioritization approach based on bioactivity/exposure ratios (BERs), in which a BER < 1 indicates that exposures are predicted to exceed a biological activity threshold. When applied to a subset of the Tox21 screening library (6484 chemicals), we found that the proportion of chemicals with BER <1 was similar using either in silico (1133/6484; 17.5%) or in vitro (148/848; 17.5%) parameters. Further, when considering only the chemicals in the Tox21 set with in vitro data, there was a high concordance of chemicals classified with either BER <1 or >1 using either in silico or in vitro parameters (767/848, 90.4%). Thus, the presented QSARs may be suitable for prioritizing the risk posed by many chemicals for which measured in vitro TK data are lacking.

Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization

Development of new chemical entities is costly, time-consuming, and has a low success rate. Accurate prediction of pharmacokinetic properties is critical to progress compounds with favorable drug-like characteristics in lead optimization. Of particular importance is the prediction of hepatic clearance, which determines drug exposure and contributes to projection of dose, half-life, and bioavailability. The most commonly employed methodology to predict hepatic clearance is termed in vitro to in vivo extrapolation (IVIVE) that involves measuring drug metabolism in vitro, scaling-up this in vitro intrinsic clearance to a prediction of in vivo intrinsic clearance by reconciling the enzymatic content between the incubation and an average human liver, and applying a model of hepatic disposition to account for limitations of protein binding and blood flow to predict in vivo clearance. This manuscript reviews common in vitro techniques used to predict hepatic clearance as well as current challenges and recent theoretical advancements in IVIVE.

A Systematic Study of the In Vitro Pharmacokinetics and Estimated Human In Vivo Clearance of Indole and Indazole-3-Carboxamide Synthetic Cannabinoid Receptor Agonists Detected on the Illicit Drug Market

In vitro pharmacokinetic studies were conducted on enantiomer pairs of twelve valinate or tert-leucinate indole and indazole-3-carboxamide synthetic cannabinoid receptor agonists (SCRAs) detected on the illicit drug market to investigate their physicochemical parameters and structure-metabolism relationships (SMRs). Experimentally derived Log D_7.4 ranged from 2.81 (AB-FUBINACA) to 4.95 (MDMB-4en-PINACA) and all SCRAs tested were highly protein bound, ranging from 88.9 ± 0.49% ((R)-4F-MDMB-BINACA) to 99.5 ± 0.08% ((S)-MDMB-FUBINACA). Most tested SCRAs were cleared rapidly in vitro in pooled human liver microsomes (pHLM) and pooled cryopreserved human hepatocytes (pHHeps). Intrinsic clearance (CL_int) ranged from 13.7 ± 4.06 ((R)-AB-FUBINACA) to 2944 ± 95.9 mL min⁻¹ kg⁻¹ ((S)-AMB-FUBINACA) in pHLM, and from 110 ± 34.5 ((S)-AB-FUBINACA) to 3216 ± 607 mL min⁻¹ kg⁻¹ ((S)-AMB-FUBINACA) in pHHeps. Predicted Human in vivo hepatic clearance (CL_H) ranged from 0.34 ± 0.09 ((S)-AB-FUBINACA) to 17.79 ± 0.20 mL min⁻¹ kg⁻¹ ((S)-5F-AMB-PINACA) in pHLM and 1.39 ± 0.27 ((S)-MDMB-FUBINACA) to 18.25 ± 0.12 mL min⁻¹ kg⁻¹ ((S)-5F-AMB-PINACA) in pHHeps. Valinate and tert-leucinate indole and indazole-3-carboxamide SCRAs are often rapidly metabolised in vitro but are highly protein bound in vivo and therefore predicted in vivo CL_H is much slower than CL_int. This is likely to give rise to longer detection windows of these substances and their metabolites in urine, possibly as a result of accumulation of parent drug in lipid-rich tissues, with redistribution into the circulatory system and subsequent metabolism.

Development of a Web-Based Toolbox to Support Quantitative In-Vitro-to-In-Vivo Extrapolations (QIVIVE) within Nonanimal Testing Strategies

The goal of the present study was to develop an online web-based toolbox that contains generic physiologically based kinetic (PBK) models for rats and humans, including underlying calculation tools to predict plasma protein binding and tissue:plasma distribution, to be used for quantitative in-vitro-to-in-vivo extrapolations (QIVIVE). The PBK models within the toolbox allow first estimations of internal plasma and tissue concentrations of chemicals to be made, based on the logP and pKa of the chemicals and values for intestinal uptake and intrinsic hepatic clearance. As a case study, the toolbox was used to predict oral equivalent doses of in vitro ToxCast bioactivity data for the food additives methylparaben, propyl gallate, octyl gallate, and dodecyl gallate. These oral equivalent doses were subsequently compared with human exposure estimates, as a low tier assessment allowing prioritization for further assessment. The results revealed that daily intake levels of especially propyl gallate can lead to internal plasma concentrations that are close to in vitro biological effect concentrations, particularly with respect to the inhibition of human thyroid peroxidase (TPO). Estrogenic effects were not considered likely to be induced by the food additives, as daily exposure levels of the different compounds remained 2 orders of magnitude below the oral equivalent doses for in vitro estrogen receptor activation. Overall, the results of the study show how the toolbox, which is freely accessible through www.qivivetools.wur.nl, can be used to obtain initial internal dose estimates of chemicals and to prioritize chemicals for further assessment, based on the comparison of oral equivalent doses of in vitro biological activity data with human exposure levels.

Case Study 5: Predicting the Drug Interaction Potential for Inhibition of CYP2C8 by Montelukast

Predicting drug-drug interactions (DDIs) from in vitro data is made difficult by not knowing concentrations of substrate and inhibitor at the target site. For in vivo targets, this is understandable, since intracellular concentrations can differ from extracellular concentrations. More vexing is that the concentration of the drug at the target for some in vitro assays can also be unknown. This uncertainty has resulted in standard in vitro practices that cannot accurately predict human pharmacokinetics. This case study highlights the impact of drug distribution, both in vitro and in vivo, with the example of the drug interaction potential of montelukast.

Consideration of the Unbound Drug Concentration in Enzyme Kinetics

The study of enzyme kinetics in drug metabolism involves assessment of rates of metabolism and inhibitory potencies over a suitable concentration range. In all but the very simplest in vitro system, these drug concentrations can be influenced by a variety of nonspecific binding reservoirs that can reduce the available concentration to the enzyme system(s) under investigation. As a consequence, the apparent kinetic parameters, such as K_m or K_i, that are derived can deviate from the true values. There are a number of sources of these nonspecific binding depots or barriers, including membrane permeation and partitioning, plasma or serum protein binding, and incubational binding. In the latter case, this includes binding to the assay apparatus as well as biological depots, depending on the characteristics of the in vitro matrix being used. Given the wide array of subcellular, cellular, and recombinant enzyme systems utilized in drug metabolism, each of these has different components which can influence the free drug concentration. The physicochemical properties of the test compound are also paramount in determining the influential factors in any deviation between true and apparent kinetic behavior. This chapter describes the underlying mechanisms determining the free drug concentration in vitro and how these factors can be accounted for in drug metabolism studies, illustrated with case studies from the literature.

Kinetics of metabolism of deltamethrin and cis- and trans-permethrin in vitro. Studies using rat and human liver microsomes, isolated rat hepatocytes and rat liver cytosol

The kinetics of metabolism of deltamethrin (DLM) and cis- and trans-permethrin (CPM and TPM) was studied in male Sprague-Dawley rat and human liver microsomes. DLM metabolism kinetics was also studied in isolated rat hepatocytes, liver microsomes and cytosol. Apparent intrinsic clearance (CL_int) values for the metabolism of DLM, CPM and TPM by cytochrome P450 (CYP) and carboxylesterase (CES) enzymes in rat and human liver microsomes decreased with increasing microsomal protein concentration. However, when apparent CL_int values were corrected for nonspecific binding to allow calculation of unbound (i.e., corrected) CL_int values, the unbound values did not vary greatly with microsomal protein concentration. Unbound CL_int values for metabolism of 0.05-1 μM DLM in rat liver microsomes (CYP and CES enzymes) and cytosol (CES enzymes) were not significantly different from rates of DLM metabolism in isolated rat hepatocytes. This study demonstrates that the nonspecific binding of these highly lipophilic compounds needs to be taken into account in order to obtain accurate estimates of rates of in vitro metabolism of these pyrethroids. While DLM is rapidly metabolised in vitro, the hepatocyte membrane does not appear to represent a barrier to the absorption and hence subsequent hepatic metabolism of this pyrethroid.

Use of Phenotypically Poor Metabolizer Individual Donor Human Liver Microsomes To Identify Selective Substrates of UGT2B10

UDP-glucuronosyltransferase (UGT)1A4 and UGT2B10 are the human UGT isoforms most frequently involved in N-glucuronidation of drugs. UGT2B10 exhibits higher affinity than UGT1A4 for numerous substrates, making it potentially the more important enzyme for metabolism of these compounds in vivo. Clinically relevant UGT2B10 polymorphisms, including a null activity splice site mutation common in African populations, can lead to large exposure differences for UGT2B10 substrates that may limit their developability as marketed drugs. UGT phenotyping approaches using recombinantly expressed UGTs are limited by low enzyme activity and lack of validation of scaling to in vivo. In this study, we describe the use of an efficient experimental protocol for identification of UGT2B10-selective substrates (i.e., those with high fraction metabolized by UGT2B10), which exploits the activity difference between pooled human liver microsomes (HLM) and HLM from a phenotypically UGT2B10 poor metabolizer donor. Following characterization of the approach with eight known UGT2B10 substrates, we used ligand-based virtual screening and literature precedents to select 24 potential UGT2B10 substrates of 140 UGT-metabolized drugs for testing. Of these, dothiepin, cidoxepin, cyclobenzaprine, azatadine, cyproheptadine, bifonazole, and asenapine were indicated to be selective UGT2B10 substrates that have not previously been described. UGT phenotyping experiments and tests comparing conjugative and oxidative clearance were then used to confirm these findings. These approaches provide rapid and sensitive ways to evaluate whether a potential drug candidate cleared via glucuronidation will be sensitive to UGT2B10 polymorphisms in vivo. SIGNIFICANCE STATEMENT: The role of highly polymorphic UDP-glucuronosyltransferase (UGT)2B10 is likely to be underestimated currently for many compounds cleared via N-glucuronidation due to high test concentrations often used in vitro and low activity of UGT2B10 preparations. The methodology described in this study can be combined with the assessment of UGT versus oxidative in vitro metabolism to rapidly identify compounds likely to be sensitive to UGT2B10 polymorphism (high fraction metabolized by UGT2B10), enabling either chemical modification or polymorphism risk assessment before candidate selection.

Assessing Toxicokinetic Uncertainty and Variability in Risk Prioritization

High(er) throughput toxicokinetics (HTTK) encompasses in vitro measures of key determinants of chemical toxicokinetics and reverse dosimetry approaches for in vitro-in vivo extrapolation (IVIVE). With HTTK, the bioactivity identified by any in vitro assay can be converted to human equivalent doses and compared with chemical intake estimates. Biological variability in HTTK has been previously considered, but the relative impact of measurement uncertainty has not. Bayesian methods were developed to provide chemical-specific uncertainty estimates for 2 in vitro toxicokinetic parameters: unbound fraction in plasma (fup) and intrinsic hepatic clearance (Clint). New experimental measurements of fup and Clint are reported for 418 and 467 chemicals, respectively. These data raise the HTTK chemical coverage of the ToxCast Phase I and II libraries to 57%. Although the standard protocol for Clint was followed, a revised protocol for fup measured unbound chemical at 10%, 30%, and 100% of physiologic plasma protein concentrations, allowing estimation of protein binding affinity. This protocol reduced the occurrence of chemicals with fup too low to measure from 44% to 9.1%. Uncertainty in fup was also reduced, with the median coefficient of variation dropping from 0.4 to 0.1. Monte Carlo simulation was used to propagate both measurement uncertainty and biological variability into IVIVE. The uncertainty propagation techniques used here also allow incorporation of other sources of uncertainty such as in silico predictors of HTTK parameters. These methods have the potential to inform risk-based prioritization based on the relationship between in vitro bioactivities and exposures.

A Cell-Free Approach Based on Phospholipid Characterization for Determination of the Cell Specific Unbound Drug Fraction (fu,cell)

Purpose

The intracellular fraction of unbound compound (f_u,cell) is an important parameter for accurate prediction of drug binding to intracellular targets. f_u,cell is the result of a passive distribution process of drug molecules partitioning into cellular structures. Initial observations in our laboratory showed an up to 10-fold difference in the f_u,cell of a given drug for different cell types. We hypothesized that these differences could be explained by the phospholipid (PL) composition of the cells, since the PL cell membrane is the major sink of unspecific drug binding. Therefore, we determined the f_u,cell of 19 drugs in cell types of different origin.

Method

The cells were characterized for their total PL content and we used mass spectrometric PL profiling to delineate the impact of each of the four major cellular PL subspecies: phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS) and phosphatidylinositol (PI). The cell-based experiments were compared to cell-free experiments that used beads covered by PL bilayers consisting of the most abundant PL subspecies.

Results

PC was found to give the largest contribution to the drug binding. Improved correlations between the cell-based and cell-free assays were obtained when affinities to all four major PL subspecies were considered. Together, our data indicate that f_u,cell is influenced by PL composition of cells.

Conclusion

We conclude that cellular PL composition varies between cell types and that cell-specific mixtures of PLs can replace cellular assays for determination of f_u,cell as a rapid, small-scale assay covering a broad dynamic range.

Graphical Abstract

Prediction of Fraction Unbound in Microsomal and Hepatocyte Incubations: A Comparison of Methods across Industry Datasets

The fraction unbound in the incubation, f_u,inc, is an important parameter to consider in the evaluation of intrinsic clearance measurements performed in vitro in hepatocytes or microsomes. Reliable estimates of f_u,inc based on a compound's structure have the potential to positively impact the screening timelines in drug discovery. Previous works suggested that f_u,inc is primarily driven by passive processes and can be described using physicochemical properties such as lipophilicity and the protonation state of the molecule. While models based on these principles proved predictive in relatively small datasets that included marketed drugs, their applicability domain has not been extensively explored. The work presented here from the in silico ADME discussion group (part of the International Consortium for Innovation through Quality in Pharmaceutical Development, the IQ consortium) describes the accuracy of these models in large proprietary datasets that include several thousand of compounds across chemical space. Overall, the models do well for compounds with low lipophilicity. In other words, the equations correctly predict that f_u,inc is, in general, above 0.5 for compounds with a calculated logP of less than 3. When applied to lipophilic compounds, the models failed to produce quantitatively accurate predictions of f_u,inc, with a high risk of underestimating binding properties. These models can, therefore, be used quantitatively for less lipophilic compounds. On the other hand, internal machine-learning models using a company's own proprietary dataset also predict compounds with higher lipophilicity reasonably well. Additionally, the data shown indicate that microsomal binding is, in general, a good proxy for hepatocyte binding.

Impact of Intracellular Concentrations on Metabolic Drug-Drug Interaction Studies

Accurate prediction of drug-drug interactions (DDI) is a challenging task in drug discovery and development. It requires determination of enzyme inhibition in vitro which is highly system-dependent for many compounds. The aim of this study was to investigate whether the determination of intracellular unbound concentrations in primary human hepatocytes can be used to bridge discrepancies between results obtained using human liver microsomes and hepatocytes. Specifically, we investigated if Kp_uu could reconcile differences in CYP enzyme inhibition values (K_i or IC₅₀). Firstly, our methodology for determination of Kp_uu was optimized for human hepatocytes, using four well-studied reference compounds. Secondly, the methodology was applied to a series of structurally related CYP2C9 inhibitors from a Roche discovery project. Lastly, the Kp_uu values of three commonly used CYP3A4 inhibitors—ketoconazole, itraconazole, and posaconazole—were determined and compared to compound-specific hepatic enrichment factors obtained from physiologically based modeling of clinical DDI studies with these three compounds. Kp_uu obtained in suspended human hepatocytes gave good predictions of system-dependent differences in vitro. The Kp_uu was also in fair agreement with the compound-specific hepatic enrichment factors in DDI models and can therefore be used to improve estimations of enrichment factors in physiologically based pharmacokinetic modeling.

Using the concordance of in vitro and in vivo data to evaluate extrapolation assumptions

Linking in vitro bioactivity and in vivo toxicity on a dose basis enables the use of high-throughput in vitro assays as an alternative to traditional animal studies. In this study, we evaluated assumptions in the use of a high-throughput, physiologically based toxicokinetic (PBTK) model to relate in vitro bioactivity and rat in vivo toxicity data. The fraction unbound in plasma (f_up) and intrinsic hepatic clearance (Cl_int) were measured for rats (for 67 and 77 chemicals, respectively), combined with f_up and Cl_int literature data for 97 chemicals, and incorporated in the PBTK model. Of these chemicals, 84 had corresponding in vitro ToxCast bioactivity data and in vivo toxicity data. For each possible comparison of in vitro and in vivo endpoint, the concordance between the in vivo and in vitro data was evaluated by a regression analysis. For a base set of assumptions, the PBTK results were more frequently better associated than either the results from a “random” model parameterization or direct comparison of the “untransformed” values of AC₅₀ and dose (performed best in 51%, 28%, and 21% of cases, respectively). We also investigated several assumptions in the application of PBTK for IVIVE, including clearance and internal dose selection. One of the better assumptions sets–restrictive clearance and comparing free in vivo venous plasma concentration with free in vitro concentration–outperformed the random and untransformed results in 71% of the in vitro-in vivo endpoint comparisons. These results demonstrate that applying PBTK improves our ability to observe the association between in vitro bioactivity and in vivo toxicity data in general. This suggests that potency values from in vitro screening should be transformed using in vitro-in vivo extrapolation (IVIVE) to build potentially better machine learning and other statistical models for predicting in vivo toxicity in humans.