The influence of nonspecific microsomal binding on apparent intrinsic clearance, and its prediction from physicochemical properties

Inhibition of human UDP-glucuronosyltransferase (UGT) enzymes by darolutamide: Prediction of in vivo drug-drug interactions

Darolutamide is a potent second-generation, selective nonsteroidal androgen receptor inhibitor (ARI), which has been approved by the US Food and Drug Administration (FDA) in treating castrate-resistant, non-metastatic prostate cancer (nmCRPC). Whether darolutamide affects the activity of UDP-glucuronosyltransferases (UGTs) is unknown. The purpose of the present study is to evaluate the inhibitory effect of darolutamide on recombinant human UGTs and pooled human liver microsomes (HLMs), and explore the potential for drug-drug interactions (DDIs) mediated by darolutamide through UGTs inhibition. The product formation rate of UGTs substrates with or without darolutamide was determined by HPLC or UPLC-MS/MS to estimate the inhibitory effect and inhibition modes of darolutamide on UGTs were evaluated by using the inhibition kinetics experiments. The results showed that 100 μM darolutamide exhibited inhibitory effects on most of the 12 UGTs tested. Inhibition kinetic studies of the enzyme revealed that darolutamide noncompetitively inhibited UGT1A1 and competitively inhibited UGT1A7 and 2B15, with the Ki of 14.75 ± 0.78 μM, 14.05 ± 0.42 μM, and 6.60 ± 0.08 μM, respectively. In particular, it also potently inhibited SN-38, the active metabolite of irinotecan, glucuronidation in HLMs with an IC50 value of 3.84 ± 0.46 μM. In addition, the in vitro-in vivo extrapolation (IVIVE) method was used to quantitatively predict the risk of darolutamide-mediated DDI via inhibiting UGTs. The prediction results showed that darolutamide may increase the risk of DDIs when administered in combination with substrates of UGT1A1, UGT1A7, or UGT2B15. Therefore, the combined administration of darolutamide and drugs metabolized by the above UGTs should be used with caution to avoid the occurrence of potential DDIs.

Balancing Molecular Size, Activity, Permeability, and Other Properties: Drug Candidates in the Context of Their Chemical Structure Optimization

Chemical structure optimization is a vital part of early drug discovery projects. Starting with compounds that show activity on the target of interest, the chemical structures are subsequently optimized toward a development candidate (DC) molecule with the best chances of clinical success. However, the DCs in the context of such optimization programs, as well as detailed characterization of major limiting factors, have not been investigated in detail so far. Here, we report an analysis of the historical DC molecules at Novartis since 2005 in the context of their optimization projects. Mapping the DCs into their respective chemical optimization series, we find that these tend to be synthesized rather early in a substantial number of cases. Further analysis of structural properties, ADMET, and potency-related readouts revealed that DC compounds tend to be generally significantly smaller, more permeable, and have higher ligand efficiency than other compounds sent to in vivo PK studies, which we also show for compounds from the same chemical series. Although this might seem obvious to most practitioners in medicinal chemistry, for all of these properties, we could show that they tend to evolve in an undesired direction during structure optimization. This highlights the difficulty of successfully translating our knowledge to medicinal chemistry optimizations.

Identification of potent and reversible piperidine carboxamides that are species-selective orally active proteasome inhibitors to treat malaria

Malaria remains a global health concern as drug resistance threatens treatment programs. We identified a piperidine carboxamide (SW042) with anti-malarial activity by phenotypic screening. Selection of SW042-resistant Plasmodium falciparum (Pf) parasites revealed point mutations in the Pf_proteasome β5 active-site (Pfβ5). A potent analog (SW584) showed efficacy in a mouse model of human malaria after oral dosing. SW584 had a low propensity to generate resistance (minimum inoculum for resistance [MIR] >109) and was synergistic with dihydroartemisinin. Pf_proteasome purification was facilitated by His8-tag introduction onto β7. Inhibition of Pfβ5 correlated with parasite killing, without inhibiting human proteasome isoforms or showing cytotoxicity. The Pf_proteasome_SW584 cryoelectron microscopy (cryo-EM) structure showed that SW584 bound non-covalently distal from the catalytic threonine, in an unexplored pocket at the β5/β6/β3 subunit interface that has species differences between Pf and human proteasomes. Identification of a reversible, species selective, orally active series with low resistance propensity provides a path for drugging this essential target.

The Drug-Drug Interaction between Erlotinib and OSI-930 Is Mediated through Aldehyde Oxidase Inhibition

The propensity for aldehyde oxidase (AO) substrates to be implicated in drug-drug interactions (DDIs) is not well understood due to the dearth of potent inhibitors that elicit in vivo inhibition of AO. Although there is only one reported instance of DDI that has been ascribed to the inhibition of AO to date, the supporting evidence for this clinical interaction is rather tenuous, and its veracity has been called into question. Our group recently reported that the epidermal growth factor receptor inhibitor erlotinib engendered potent time-dependent inhibition of AO with inactivation kinetic constants in the same order of magnitude as its free circulating plasma concentrations. At the same time, it was previously reported that the concomitant administration of erlotinib with the investigational drug OSI-930 culminated in a an approximately twofold increase in its systemic exposure. Although the basis underpinning this interaction remains unclear, the structure of OSI-930 contains a quinoline motif that is amenable to oxidation at the electrophilic carbon adjacent to the nitrogen atom by molybdenum-containing hydroxylases like AO. In this study, we conducted metabolite identification that revealed that OSI-930 undergoes AO metabolism to a mono-oxygenated 2-oxo metabolite and assessed its formation kinetics in human liver cytosol. Additionally, reaction phenotyping in human hepatocytes revealed that AO contributes nearly 50% to the overall metabolism of OSI-930. Finally, modeling the interaction between erlotinib and OSI-930 using a mechanistic static model projected an ∼1.85-fold increase in the systemic exposure of OSI-930, which accurately recapitulated clinical observations. SIGNIFICANCE STATEMENT: This study delineates an aldehyde oxidase (AO) metabolic pathway in the investigational drug OSI-930 for the first time and confirmed that it represented a major route of metabolism through reaction phenotyping in human hepatocytes. Our study provided compelling mechanistic and modeling evidence for the first instance of an AO-mediated clinical drug-drug interaction stemming from the in vivo inhibition of the AO-mediated quinoline 2-oxidation pathway in OSI-930 by erlotinib.

Evaluation and Optimization of a Microcavity Plate-Based Human Hepatocyte Spheroid Model for Predicting Clearance of Slowly Metabolized Drug Candidates

In vitro clearance assays are routinely conducted in drug discovery to predict in vivo clearance, but low metabolic turnover compounds are often difficult to evaluate. Hepatocyte spheroids can be cultured for days, achieving higher drug turnover, but have been hindered by limitations on cell number per well. Corning Elplasia microcavity 96-well microplates enable the culture of 79 hepatocyte spheroids per well. In this study, microcavity spheroid properties (size, hepatocyte function, longevity, culturing techniques) were assessed and optimized for clearance assays, which were then compared with microsomes, hepatocyte suspensions, two-dimensional-plated hepatocytes, and macrowell spheroids cultured as one per well. Higher enzyme activity coupled with greater hepatocyte concentrations in microcavity spheroids enabled measurable turnover of all 17 test compounds, unlike the other models that exhibited less drug turnover. Microcavity spheroids also predicted intrinsic clearance (CLint) and blood clearance (CLb) within threefold for 53% [9/17; average absolute fold error (AAFE), 3.9] and 82% (14/17; AAFE, 2.6) of compounds using a linear regression correction model, respectively. An alternate method incorporating mechanistic modeling that accounts for mass transport (permeability and diffusion) within spheroids demonstrated improved predictivity for CLint (12/17; AAFE, 4.0) and CLb (14/17; AAFE, 2.1) without the need for empirical scaling factors. The estimated fraction of drug metabolized by cytochrome P450 3A4 (fm,CYP3A4) using 3 μM itraconazole was within 25% of observed values for 6 of 8 compounds, with 5 of 8 compounds within 10%. In sum, spheroid cultures in microcavity plates permit the ability to test and predict clearance as well as fm,CYP3A4 of low metabolic turnover compounds and represent a valuable complement to conventional in vitro clearance assays. SIGNIFICANCE STATEMENT: Culturing multiple spheroids in ultralow attachment microcavities permits accurate quantitation of metabolically stable compounds in substrate depletion assays, overcoming limitations with singly cultured spheroids. In turn, this permits robust estimates of intrinsic clearance, which is improved with the consideration of mass transport within the spheroid. Incubations with 3 μM itraconazole enabled assessments of CYP3A4 involvement in hepatic clearance.

Many human pharmaceuticals are weak inhibitors of the cytochrome P450 system in rainbow trout (Oncorhynchus mykiss) liver S9 fractions

Introduction

Pharmaceutical residues are widely detected in aquatic environment and can be taken up by nontarget species such as fish. The cytochromes P450 (CYP) represent an important detoxification mechanism in fish, like in humans. In the present study, we assessed the correlation of the substrate selectivities of rainbow trout CYP1A and CYP3A homologues with those of human, through determination of the half-maximal inhibitory concentrations (IC50) of a total sixteen human pharmaceuticals toward CYP1A-like ethoxyresorufin O-deethylase (EROD) and CYP3A-like 7-benzyloxy-4-trifluoromethylcoumarin O-debenzylase (BFCOD) in rainbow trout (Oncorhynchus mykiss) liver S9 fractions (RT-S9).

Methods

The inhibitory impacts (IC50) of atomoxetine, atorvastatin, azelastine, bimatoprost, clomethiazole, clozapine, desloratadine, disulfiram, esomeprazole, felbinac, flecainide, orphenadrine, prazosin, quetiapine, sulpiride, and zolmitriptan toward the EROD and BFCOD activities in RT-S9 were determined using the IC50 shift assay, capable of identifying time-dependent inhibitors (TDI). Additionally, the nonspecific binding of the test pharmaceuticals to RT-S9 was assessed using equilibrium dialysis.

Results

Most test pharmaceuticals were moderate to weak inhibitors of both EROD and BFCOD activity in RT-S9, even if most are noninhibitors of human CYP1A or CYP3A. Only bimatoprost, clomethiazole, felbinac, sulpiride, and zolmitriptan did not inhibit either activity in RT-S9. EROD inhibition was generally stronger than that of BFCOD and some substances (atomoxetine, flecainide, and prazosin) inhibited selectively only EROD activity. The strongest EROD inhibition was detected with azelastine and esomeprazole (unbound IC50 of 3.8 ± 0.5 µM and 3.0 ± 0.8 µM, respectively). None of the test substances were TDIs of BFCOD, but esomeprazole was a TDI of EROD. Apart from clomethiazole and disulfiram, the nonspecific binding of the test pharmaceuticals to the RT-S9 was extensive (unbound fractions <0.5) and correlated well (R 2 = 0.7135) with their water-octanol distribution coefficients.

Discussion

The results indicate that the P450 interactions in RT-S9 cannot be explicitly predicted based on human data, but the in vitro data reported herein can shed light on the substrate selectivity of rainbow trout CYP1A1 and CYP3A27 in comparison to their human homologues. The IC50 concentrations are however many orders of magnitude higher than average environmental concentrations of pharmaceuticals. The time-dependent EROD inhibition by esomeprazole could warrant further research to evaluate its possible interlinkages with hepatotoxic impacts on fish.

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.

A workflow to practically apply true dose considerations to in vitro testing for next generation risk assessment

With the move away from safety testing assessment based on data generated in experimental animals the concept of Next Generation Risk Assessment (NGRA) has arisen which instead uses data from in silico and in vitro models. A key uncertainty in risk assessment is the actual dose of test chemical at the target site, and therefore surrogate dose metrics, such as nominal concentration in test media are used to describe in vitro effect (or no-effect) doses. The reliability and accuracy of the risk assessment therefore depends largely on our ability to understand and characterise the relationship between the dose metrics used and the actual biologically effective dose at the target site. The objective of this publication is to use 40 case study chemicals to illustrate how in vitro dose considerations can be applied to characterise the "true dose" and build confidence in the understanding of the biologically effective dose in in vitro test systems for the determination e.g. points of departure (PoDs) for NGRA. We propose a workflow that can be applied to assess whether the nominal test concentration can be considered a conservative dose metric for use in NGRA. The workflow examines the implications of volatility, stability, hydrophobicity, binding to plastic and serum, solubility, and the potential use of in silico models for some of these parameters. For the majority of the case study chemicals we found that the use of nominal concentrations in risk assessment would result in conservative decision making. However, for serval chemicals a potential for underestimation of the risk in humans in vivo based on in vitro nominal effect concentrations was identified, and approaches for refinement by characterisation of the actual effect concentration are proposed.

Inhibition of human UDP-glucuronosyltransferase enzyme by entrectinib: Implications for drug-drug interactions

As a new type of oral tyrosine kinase inhibitor, entrectinib can act on multiple targets and exert efficacy and has been approved for the treatment of non-small cell lung cancer (NSCLC) and solid tumors. However, whether entrectinib affects the activities of recombinant human UDP-glucuronosyltransferases (UGTs) remains unclear. Herein, we aimed to investigate the inhibitory effects of entrectinib on human UGTs and to assess the potential risk of causing drug-drug interactions (DDIs) based on the inhibition against UGTs. High-performance liquid chromatography (HPLC) was used to evaluate the inhibitory effects of entrectinib on UGTs according to the product formation rate of UGT substrate with or without entrectinib, and the inhibition kinetics experiment was conducted to assess the inhibitory type of entrectinib on UGTs. Our results showed that entrectinib exhibited extensive inhibitory effects on most human UGTs, and especially inhibited the activities of UGT1A7, UGT1A8, and UGT2B15 with Ki (Inhibition constant) of lower than 5 μM (0.95-4.38 μM). Furthermore, the results from quantitative prediction research suggested that the combination of entrectinib at 600 mg/day with substrates primarily metabolized by hepatic UGT2B15 or intestinal UGT1A7 and UGT1A8 might cause clinical DDIs. Thus, special attention should be paid to avoid adverse reactions induced by DDIs when co-administration of entrectinib and drugs metabolized by UGTs.

Characterization of Pediatric Rectal Absorption, Drug Disposition, and Sedation Level for Midazolam Gel Using Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling

This study aims to explore and characterize the role of pediatric sedation via rectal route. A pediatric physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) model of midazolam gel was built and validated to support dose selection for pediatric clinical trials. Before developing the rectal PBPK model, an intravenous PBPK model was developed to determine drug disposition, specifically by describing the ontogeny model of the metabolic enzyme. Pediatric rectal absorption was developed based on the rectal PBPK model of adults. The improved Weibull function with permeability, surface area, and fluid volume parameters was used to extrapolate pediatric rectal absorption. A logistic regression model was used to characterize the relationship between the free concentrations of midazolam and the probability of sedation. All models successfully described the PK profiles with absolute average fold error (AAFE) < 2, especially our intravenous PBPK model that extended the predicted age to preterm. The simulation results of the PD model showed that when the free concentrations of midazolam ranged from 3.9 to 18.4 ng/mL, the probability of "Sedation" was greater than that of "Not-sedation" states. Combined with the rectal PBPK model, the recommended sedation doses were in the ranges of 0.44-2.08 mg/kg for children aged 2-3 years, 0.35-1.65 mg/kg for children aged 4-7 years, 0.24-1.27 mg/kg for children aged 8-12 years, and 0.20-1.10 mg/kg for adolescents aged 13-18 years. Overall, this model mechanistically quantified drug disposition and effect of midazolam gel in the pediatric population, accurately predicted the observed clinical data, and simulated the drug exposure for sedation that will inform dose selection for following pediatric clinical trials.

Uridine 5'-Diphospho-glucuronosyltransferase 1A3 (UGT1A3) Prediction of Hepatic Clearance of Organic Anion Transporting Polypeptide 1B3 (OATP1B3) Substrate Telmisartan by Glucuronidation Using In Vitro-In Vivo Extrapolation (IVIVE)

BACKGROUND AND OBJECTIVE

The prediction of pharmacokinetic parameters for drugs metabolised by cytochrome P450 enzymes has been the subject of active research for many years, while the application of in vitro-in vivo extrapolation (IVIVE) techniques for non-cytochrome P450 enzymes has not been thoroughly evaluated. There is still no established quantitative method for predicting hepatic clearance of drugs metabolised by uridine 5'-diphospho-glucuronosyltransferases (UGTs), not to mention those which undergo hepatic uptake. The objective of the study was to predict the human hepatic clearance for telmisartan based on in vitro metabolic stability and hepatic uptake results.

METHODS

Telmisartan was examined in liver systems, allowing to estimate intrinsic clearance (CLint, in vitro) based on the substrate disappearance rate with the use of liquid chromatography tandem mass spectrometry (LC-MS/MS) technique. Obtained CLint, in vitro values were corrected for corresponding unbound fractions. Prediction of human hepatic clearance was made from scaled unbound CLint, in vitro data with the use of the well-stirred model, and finally referenced to the literature value of observed clearance in humans, allowing determination of the essential scaling factors.

RESULTS

The in vitro scaled CLint, in vitro by UGT1A3 was assessed using three systems, human hepatocytes, liver microsomes, and recombinant enzymes. Obtained values were scaled and hepatic metabolism clearance was predicted, resulting in significant clearance underprediction. Utilization of the extended clearance concept (ECC) and hepatic uptake improved prediction of hepatic metabolism clearance. The scaling factors for hepatocytes, assessing the in vitro-in vivo difference, changed from sixfold difference to only twofold difference with the application of the ECC.

CONCLUSIONS

The study showed that taking into consideration hepatic uptake of a drug allows us to obtain satisfactory scaling factors, hence enabling the prediction of in vivo hepatic glucuronidation from in vitro data.

Improving In Vitro-In Vivo Extrapolation of Clearance Using Rat Liver Microsomes for Highly Plasma Protein-Bound Molecules

It is common practice in drug discovery and development to predict in vivo hepatic clearance from in vitro incubations with liver microsomes or hepatocytes using the well-stirred model (WSM). When applying the WSM to a set of approximately 3000 Novartis research compounds, 73% of neutral and basic compounds (extended clearance classification system [ECCS] class 2) were well-predicted within 3-fold. In contrast, only 44% (ECCS class 1A) or 34% (ECCS class 1B) of acids were predicted within 3-fold. To explore the hypothesis whether the higher degree of plasma protein binding for acids contributes to the in vitro-in vivo correlation (IVIVC) disconnect, 68 proprietary compounds were incubated with rat liver microsomes in the presence and absence of 5% plasma. A minor impact of plasma on clearance IVIVC was found for moderately bound compounds (fraction unbound in plasma [fup] ≥1%). However, addition of plasma significantly improved the IVIVC for highly bound compounds (fup <1%) as indicated by an increase of the average fold error from 0.10 to 0.36. Correlating fup with the scaled unbound intrinsic clearance ratio in the presence or absence of plasma allowed the establishment of an empirical, nonlinear correction equation that depends on fup Taken together, estimation of the metabolic clearance of highly bound compounds was enhanced by the addition of plasma to microsomal incubations. For standard incubations in buffer only, application of an empirical correction provided improved clearance predictions. SIGNIFICANCE STATEMENT: Application of the well-stirred liver model for clearance in vitro-in vivo extrapolation (IVIVE) in rat generally underpredicts the clearance of acids and the strong protein binding of acids is suspected to be one responsible factor. Unbound intrinsic in vitro clearance (CLint,u) determinations using rat liver microsomes supplemented with 5% plasma resulted in an improved IVIVE. An empirical equation was derived that can be applied to correct CLint,u-values in dependance of fraction unbound in plasma (fup) and measured CLint in buffer.

Application of a new MDCKII-MDR1 cell model to measure the extent of drug distribution in vitro at equilibrium for prediction of in vivo unbound brain-to-plasma drug distribution

INTRO

Reliable estimates of drug uptake from blood to brain parenchyma are crucial in CNS drug discovery and development. While in vivo Kp,uu,brain estimates are the gold standard for investigating brain drug disposition, animal usage is a limitation to high throughput application. This study investigates an in vitro model using P-gp expressing MDCKII-MDR1 cells for predicting in vivo brain drug penetration.

METHODS

In vitro equilibrium distribution studies were conducted in apical and basolateral solutions with high protein content to estimate Kp,brain and Kp,uu,brain values. The correlation between in vitro and in vivo Kp,brain values for a set of compounds was examined.

RESULTS

We observed a good correlation between in vitro and in vivo Kp,brain values (R2 = 0.69, Slope: 1.6), indicating that the in vitro model could predict in vivo drug brain penetration. The 'unilateral (Uni-L)' in vitro setup correctly classified 5 out of 5 unrestricted compounds and 3 out of 5 restricted compounds. Possible reasons for the observed disparities for some compounds have been discussed, such as difference in transport areas between in vitro and in vivo settings and effect of pH changes.

CONCLUSION

The in vitro assay setup developed in this study holds promise for predicting in vivo drug brain penetration in CNS drug discovery. The correlation between in vitro and in vivo Kp,brain values, underscores that the model may have potential for early-stage screening. With minor refinements, this in vitro approach could reduce the reliance on in vivo experiments, accelerating the pace of CNS drug discovery and promoting a more ethical research approach.

Avapritinib Carries the Risk of Drug Interaction via Inhibition of UDP-Glucuronyltransferase (UGT) 1A1

BACKGROUND

Avapritinib is the only drug for adult patients with PDGFRA exon 18 mutated unresectable or metastatic gastrointestinal stromal tumor (GIST). Although avapritinib has been approved by the FDA for four years, little is known about the risk of drug-drug interactions (DDIs) via UDP-glucuronyltransferases (UGTs) inhibition.

OBJECTIVE

The aim of the present study was to systematically evaluate the inhibitory effects of avapritinib against UGTs and to quantitatively estimate its potential DDIs risk in vivo.

METHODS

Recombinant human UGTs were employed to catalyze the glucuronidation of substrates in a range of concentrations of avapritinib. The kinetics analysis was performed to evaluate the inhibition types of avapritinib against UGTs. The quantitative prediction of DDIs was done using in vitro-in vivo extrapolation (IVIVE).

RESULTS

Avapritinib had a potent competitive inhibitory effect on UGT1A1. Quantitative prediction results showed that avapritinib administered at clinical doses might result in a 14.85% increase in area under the curve (AUC) of drugs primarily cleared by UGT1A1. Moreover, the Rgut value was calculated to be 18.44.

CONCLUSION

Avapritinib has the potential to cause intestinal DDIs via the inhibition of UGT1A1. Additional attention should be paid when avapritinib is coadministered with UGT1A1 substrates.

Drug-drug interaction prediction of ziritaxestat using a physiologically based enzyme and transporter pharmacokinetic network interaction model

Ziritaxestat, an autotaxin inhibitor, was under development for the treatment of idiopathic pulmonary fibrosis. It is a substrate of cytochrome P450 3A4 (CYP3A4) and P-glycoprotein and a weak inhibitor of the CYP3A4 and OATP1B1 pathways. We developed a physiologically based pharmacokinetic (PBPK) network interaction model for ziritaxestat that incorporated its metabolic and transporter pathways, enabling prediction of its potential as a victim or perpetrator of drug-drug interactions (DDIs). Concurrently, we evaluated CYP3A4 autoinhibition, including time-dependent inhibition. In vitro information and clinical data from healthy volunteer studies were used for model building and validation. DDIs with rifampin, itraconazole, voriconazole, pravastatin, and rosuvastatin were predicted, followed by validation against a test dataset. DDIs of ziritaxestat as a victim or perpetrator were simulated using the final model. Predicted-to-observed DDI ratios for the maximum plasma concentration (Cmax ) and the area under the plasma concentration-time curve (AUC) were within a two-fold ratio for both the metabolic and transporter-mediated simulated DDIs. The predicted impact of autoinhibition/autoinduction or time-dependent inhibition of CYP3A4 was a 12% decrease in exposure. Model-based predictions for ziritaxestat as a victim of DDIs with a moderate CYP3A4 inhibitor (fluconazole) suggested a 2.6-fold increase in the AUC of ziritaxestat, while multiple doses of a strong inhibitor (voriconazole) would increase the AUC by 15-fold. Efavirenz would yield a three-fold decrease in the AUC of ziritaxestat. As a perpetrator, ziritaxestat was predicted to increase the AUC of the CYP3A4 index substrate midazolam by 2.7-fold. An overarching PBPK model was developed that could predict DDI liability of ziritaxestat for both CYP3A4 and the transporter pathways.

Prediction of the Time to Reach Equilibrium for Improved Estimation of the Unbound Fraction of Compounds in Equilibrium Dialysis Using kinetic Modeling

Equilibrium dialysis (ED) is widely used in pharmacokinetics to determine the fraction of unbound (fu) compounds in plasma; however, the kinetics of drugs in the ED system with respect to their permeation across semi-permeable membranes has not been systemically studied. Here, the kinetics of the ED system, including the binding of drugs to plasma proteins, non-specific binding, and permeation across the membrane, was described to enable verification of the equilibrium, prediction of the time to reach equilibrium, and estimations of fu with data obtained during pre-equilibrium. Using data obtained during pre-equilibrium, the time to reach 90% equilibrium (t90%) and fu were estimated with reasonable accuracy. Notably, fu could be estimated reasonably well using one-time-point data for the calculation. Furthermore, the current modeling approach allowed concurrent estimations of fu and the decomposition rate of compounds that were metabolically unstable in the plasma. Reasonable metabolic rate constants were determined for cefadroxil and diltiazem, demonstrating the practicality of this method for determining kinetics related to fu characterization. Because the determination of fu of compounds with 'unfavorable' physicochemical properties is known to be experimentally challenging, the current method may be useful in determining the fu of compounds in vitro.

Assessing extent of brain penetration in vivo (Kp,uu,brain) in Göttingen minipig using a diverse set of reference drugs

The application of Göttingen minipigs for non-rodent pharmacokinetics (PK) and drug safety testing has seen a dramatic increase in recent years. The aim of this study was to determine the total and unbound brain-to-plasma ratios (Kp,brain and Kp,uu,brain) for a diverse set of reference compounds in female Göttingen minipigs and compare these with Kp,uu,brain values from other species to assess the suitability of Göttingen minipigs as a model for CNS drug safety testing and brain PK in clinical translation. The reference set consisted of 17 compounds with varying physico-chemical properties and included known human P-glycoprotein (P-gp) substrates. The results of the study showed, that minipig Kp,brain and Kp,uu,brain values for the tested compounds were in the range 0.03-86 and 0.02-2.4 (n = 3-4) respectively. The Kp,uu,brain values were comparable between minipig and rat for a large proportion of the compounds (71% within 2-fold, n = 17). Comparisons of brain penetration across several species for a subset of reference compounds revealed that minipig values were quite similar to those of rat, dog, monkey and human. The study highlighted that the largest Kp,uu,brain species differences were observed for compounds classified as transporter substrates (e.g. cimetidine, risperidone, Way-100635 and altanserin). In conclusion these brain penetration data add substantially to the available literature on PK and drug disposition for minipigs and support use of Göttingen minipig as a non-rodent drug safety model for CNS drug candidates and as a brain PK model for clinical translation.

New Dual Inhibitors of Bacterial Topoisomerases with Broad-Spectrum Antibacterial Activity and In Vivo Efficacy against Vancomycin-Intermediate Staphylococcus aureus

A new series of dual low nanomolar benzothiazole inhibitors of bacterial DNA gyrase and topoisomerase IV were developed. The resulting compounds show excellent broad-spectrum antibacterial activities against Gram-positive Enterococcus faecalis, Enterococcus faecium and multidrug resistant (MDR) Staphylococcus aureus strains [best compound minimal inhibitory concentrations (MICs): range, <0.03125-0.25 μg/mL] and against the Gram-negatives Acinetobacter baumannii and Klebsiella pneumoniae (best compound MICs: range, 1-4 μg/mL). Lead compound 7a was identified with favorable solubility and plasma protein binding, good metabolic stability, selectivity for bacterial topoisomerases, and no toxicity issues. The crystal structure of 7a in complex with Pseudomonas aeruginosa GyrB24 revealed its binding mode at the ATP-binding site. Expanded profiling of 7a and 7h showed potent antibacterial activity against over 100 MDR and non-MDR strains of A. baumannii and several other Gram-positive and Gram-negative strains. Ultimately, in vivo efficacy of 7a in a mouse model of vancomycin-intermediate S. aureus thigh infection was also demonstrated.

Inhibition of human UDP-glucuronosyltransferase enzyme by ripretinib: Implications for drug-drug interactions

Ripretinib, a tyrosine kinase inhibitor (TKI), is the first FDA approved fourth-line therapy for adults with advanced gastrointestinal stromal tumor (GIST). Studies have shown that several TKIs for treating GIST were potent inhibitors of human UDP- glucosyltransferase (UGTs) enzymes. However, whether ripretinib affects the activity of UGTs remains unclear. The aim of this study was to investigate the effects of ripretinib on major UGT isoforms, as well as to evaluate its potential drug-drug interactions (DDIs) risk caused by the inhibition of UGTs activities. The inhibitory effects and inhibition modes of ripretinib on UGTs were systematically evaluated using high-performance liquid chromatography (HPLC) and enzyme kinetic studies, respectively. Our data showed that ripretinib exhibited potent inhibition against UGT1A1, UGT1A3, UGT1A4, UGT1A7 and UGT1A8. Enzyme kinetic studies indicated that ripretinib was not only a competitive inhibitor of UGT1A1, UGT1A4 and UGT1A7, but also a noncompetitive inhibitor of UGT1A3, as well as a mixed inhibitor of UGT1A8. The prediction results of in vitro-in vivo extrapolation (IVIVE) demonstrated that ripretinib might bring the potential risk of DDIs when combined with substrates of UGT1A1, UGT1A3, UGT1A4, UGT1A7 or UGT1A8. Therefore, special attention should be paid when ripretinib is used in conjunction with other drugs metabolized by UGTs to avoid risk of DDIs in clinic.

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.

Data on ADME parameters of bisphenol A and its metabolites for use in physiologically based pharmacokinetic modelling

The paper presents the collection of physicochemical parameters of bisphenol A (BPA) and its sulfate (BPAS) and glucuronide (BPAG) conjugates, accompanied by data characterizing their absorption, distribution, metabolism and excretion (ADME) behavior following oral administration of BPA. The data were collected from open literature sources and publicly available databases. Additionally, data calculated by using the MarvinSketch 18.30.0 software or predicted by relevant QSAR models built in Simcyp® Simulator were also used. All data were analysed and are fit for purpose if necessary to ensure a reliable prediction of pharmacokinetics of BPA and its conjugates. The data selection process and reasoning for fitting is provided to allow critical assessment and to ensure data transparency. Finally, the sensitivity analysis was performed to assess the influence of the selected parameters on the PBPK model predictions.

Prediction of Drug-Drug-Gene Interaction Scenarios of (E)-Clomiphene and Its Metabolites Using Physiologically Based Pharmacokinetic Modeling

Clomiphene, a selective estrogen receptor modulator (SERM), has been used for the treatment of anovulation for more than 50 years. However, since (E)-clomiphene ((E)-Clom) and its metabolites are eliminated primarily via Cytochrome P450 (CYP) 2D6 and CYP3A4, exposure can be affected by CYP2D6 polymorphisms and concomitant use with CYP inhibitors. Thus, clomiphene therapy may be susceptible to drug-gene interactions (DGIs), drug-drug interactions (DDIs) and drug-drug-gene interactions (DDGIs). Physiologically based pharmacokinetic (PBPK) modeling is a tool to quantify such DGI and DD(G)I scenarios. This study aimed to develop a whole-body PBPK model of (E)-Clom including three important metabolites to describe and predict DGI and DD(G)I effects. Model performance was evaluated both graphically and by calculating quantitative measures. Here, 90% of predicted C_max and 80% of AUC_last values were within two-fold of the corresponding observed value for DGIs and DD(G)Is with clarithromycin and paroxetine. The model also revealed quantitative contributions of different CYP enzymes to the involved metabolic pathways of (E)-Clom and its metabolites. The developed PBPK model can be employed to assess the exposure of (E)-Clom and its active metabolites in as-yet unexplored DD(G)I scenarios in future studies.

Physiologically Based Pharmacokinetic Modeling To Guide Management of Drug Interactions between Elexacaftor-Tezacaftor-Ivacaftor and Antibiotics for the Treatment of Nontuberculous Mycobacteria

Nontuberculous mycobacteria (NTM) are the pathogens of concern in people with cystic fibrosis (pwCF) due to their association with deterioration of lung function. Treatment requires the use of a multidrug combination regimen, creating the potential for drug-drug interactions (DDIs) with cystic fibrosis transmembrane conductance regulator (CFTR)-modulating therapies, including elexacaftor, tezacaftor, and ivacaftor (ETI), which are eliminated mainly through cytochrome P450 (CYP) 3A-mediated metabolism. An assessment of the DDI risk for ETI coadministered with NTM treatments, including rifabutin, clofazimine, and clarithromycin, is needed to provide appropriate guidance on dosing.

Cabozantinib Carries the Risk of Drug-Drug Interactions via Inhibition of UDPglucuronosyltransferase (UGT) 1A9

BACKGROUND

Cabozantinib is a multiple receptor tyrosine kinases inhibitor (TKI) approved to treat progressive, metastatic medullary thyroid cancer, advanced renal cell carcinoma, and hepatocellular carcinoma. Drugdrug interactions (DDIs) for cabozantinib have been identified involving the role of cytochromes P450. Although the previous study reported that cabozantinib showed a slight inhibition of UDP-glucuronosyltransferase (UGT) 1A1 at the highest concentration tested, there are no reports on the potential for UGTs-mediated-DDIs. Hence, the current study aims to address this knowledge gap.

OBJECTIVE

This study aimed to investigate the inhibitory effect of cabozantinib on human UGTs and to quantitatively evaluate the DDI potential via UGT inhibition.

METHODS

The inhibitory effects of cabozantinib on UGTs were determined by measuring the formation rates for 4- methylumbelliferone (4-MU) glucuronide and trifluoperazine N-glucuronide using recombinant human UGT isoforms in the absence or presence of cabozantinib. Inhibition kinetic studies were conducted to determine the type of inhibition of cabozantinib on UGTs and the corresponding inhibition constant (Ki) value. In vitro-in vivo extrapolation (IVIVE) was further employed to predict the potential risk of DDI in vivo.

RESULTS

Cabozantinib displayed potent inhibition of UGT1A1, 1A3, 1A4, 1A6, 1A7, 1A8, 1A9, 1A10, 2B7, and 2B15. Cabozantinib exhibited noncompetitive inhibition towards UGT1A1 and 1A3 and inhibition towards UGT1A7 and 1A9. The Ki,u values (mean ± standard deviation) were calculated to be 2.15±0.11 μM, 0.83±0.05 μM, 0.75±0.04 μM and 0.18 ± 0.10 μM for UGT1A1, 1A3, 1A7 and 1A9, respectively. Co-administration of cabozantinib at the clinically approved dose of 60 mg/day or 140 mg/day may result in approximately a 26% to 60% increase in the systemic exposure of drugs predominantly cleared by UGT1A9, implying a high risk of DDIs.

CONCLUSION

Cabozantinib has the potential to cause DDIs via the inhibition of UGT1A9; therefore, additional attention should be paid to the safety of the combined use of cabozantinib and drugs metabolized by UGT1A9.

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.

Enhancing Repair of Oxidative DNA Damage with Small-Molecule Activators of MTH1

Impaired DNA repair activity has been shown to greatly increase rates of cancer clinically. It has been hypothesized that upregulating repair activity in susceptible individuals may be a useful strategy for inhibiting tumorigenesis. Here, we report that selected tyrosine kinase (TK) inhibitors including nilotinib, employed clinically in the treatment of chronic myeloid leukemia, are activators of the repair enzyme Human MutT Homolog 1 (MTH1). MTH1 cleanses the oxidatively damaged cellular nucleotide pool by hydrolyzing the oxidized nucleotide 8-oxo-2'-deoxyguanosine (8-oxo-dG)TP, which is a highly mutagenic lesion when incorporated into DNA. Structural optimization of analogues of TK inhibitors resulted in compounds such as SU0448, which induces 1000 ± 100% activation of MTH1 at 10 μM and 410 ± 60% at 5 μM. The compounds are found to increase the activity of the endogenous enzyme, and at least one (SU0448) decreases levels of 8-oxo-dG in cellular DNA. The results suggest the possibility of using MTH1 activators to decrease the frequency of mutagenic nucleotides entering DNA, which may be a promising strategy to suppress tumorigenesis in individuals with elevated cancer risks.

Physiologically Based Pharmacokinetic Modeling to Describe the CYP2D6 Activity Score-Dependent Metabolism of Paroxetine, Atomoxetine and Risperidone

The cytochrome P450 2D6 (CYP2D6) genotype is the single most important determinant of CYP2D6 activity as well as interindividual and interpopulation variability in CYP2D6 activity. Here, the CYP2D6 activity score provides an established tool to categorize the large number of CYP2D6 alleles by activity and facilitates the process of genotype-to-phenotype translation. Compared to the broad traditional phenotype categories, the CYP2D6 activity score additionally serves as a superior scale of CYP2D6 activity due to its finer graduation. Physiologically based pharmacokinetic (PBPK) models have been successfully used to describe and predict the activity score-dependent metabolism of CYP2D6 substrates. This study aimed to describe CYP2D6 drug–gene interactions (DGIs) of important CYP2D6 substrates paroxetine, atomoxetine and risperidone by developing a substrate-independent approach to model their activity score-dependent metabolism. The models were developed in PK-Sim^®, using a total of 57 plasma concentration–time profiles, and showed good performance, especially in DGI scenarios where 10/12, 5/5 and 7/7 of DGI AUC_last ratios and 9/12, 5/5 and 7/7 of DGI C_max ratios were within the prediction success limits. Finally, the models were used to predict their compound’s exposure for different CYP2D6 activity scores during steady state. Here, predicted DGI AUC_ss ratios were 3.4, 13.6 and 2.0 (poor metabolizers; activity score = 0) and 0.2, 0.5 and 0.95 (ultrarapid metabolizers; activity score = 3) for paroxetine, atomoxetine and risperidone active moiety (risperidone + 9-hydroxyrisperidone), respectively.

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.

An HPLC-UV validated bioanalytical method for measurement of in vitro phase 1 kinetics of α-synuclein binding bifunctional compounds

Aggregates of the protein α-synuclein are associated with pathophysiology of Parkinson's disease and are present in Lewy Bodies found in the brains of Parkinson's patients. We previously demonstrated that bifunctional compounds composed of caffeine linked via a six carbon chain to either 1-aminoindan (C₈-6-I) or nicotine (C₈-6-N) bind α-synuclein and protect yeast cells from α-synuclein mediated toxicity.A critical step in development of positron emission tomography (PET) probes for neurodegenerative diseases is evaluation of their metabolic stability. We determined that C₈-6-I, and C₈-6-N both undergo phase 1 P450 metabolism in mouse, rat, and human liver microsomes. We utilised this metabolic information to guide the design of fluorinated analogues for use as PET probes and determined that the fluorine in ¹⁹F-C₈-6-I and ¹⁹F-C₈-6-N is stable to P450 enzymes.We have developed and validated an analytical HPLC-UV method following FDA and EMA guidelines to measure in vitro phase 1 kinetics of these compounds and determine their V_max, K_M and CL_int,u in mouse liver microsomes. We found that C₈-6-I and ¹⁹F-C₈-6-I have a two- to fourfold lower CL_int,u than C₈-6-N, and ¹⁹F-C₈-6-N. Our approach shows a simple, specific, and effective system to design and develop compounds as PET probes.

Daphnetin, a Coumarin in Genus Stellera Chamaejasme Linn: Chemistry, Bioactivity and Therapeutic Potential

Coumarins is a huge family of phenolic compounds containing a common structure of 2 H -1-benzopyran-2-one. Nowadays, more than 1,300 natural-based coumarins have been identified in a variety of plants, bacteria and fungi, many of them exhibited promising biomedical performance. Daphnetin (7,8-dihydroxycoumarin) is a typical coumarin associated with a couple of bioactivities such as anti-cancer, antibacterial, anti-inflammatory and anti-arthritis. In the treatment of diseases, it has been verified that daphnetin has outstanding therapeutic effects on diabetes, arthritis, transplant rejection, cancer and even on central nervous system diseases. Herein, we summarized the chemical synthetic methodologies, bioactivities, therapeutic potentials and structure-activity relationships of daphnetin and its derivatives. Hopefully, this review would be beneficial for the discovery of new coumarin-based biomedicine in the near future.

In vitro effects of opicapone on activity of human UDP-glucuronosyltransferases isoforms

Catechol-O-methyltransferase (COMT) inhibitors are widely used as an add-on treatment to levodopa in adults with Parkinson's disease. It has been evidenced that the second-generation COMT inhibitors entacapone and tolcapone are potent inhibitors on human UDP-glucosyltransferases (UGTs), while the effect of the third-generation COMT inhibitor opicapone on human UGTs activities is unclear. The purpose of this study is to systemically investigate the effects of opicapone on human UGTs activities, and also to assess the potential risk of drug-drug interactions (DDIs) associated with opicapone. Our results indicated that opicapone is a broad-spectrum inhibitor of UGTs. Particularly, opicapone exhibited potent inhibition against UGT1A1, 1A7, 1A8, 1A9, and 1A10, with a range of inhibition constant K_i values of 1.31-10.58 µM. Furthermore, the DDI risk was quantitatively predicted by using the in vitro-in vivo extrapolation (IVIVE). The prediction suggested that co-administration of opicapone at 25 mg/day or 50 mg/day with drugs primarily cleared by hepatic UGT1A9 or intestinal UGT1A1, 1A7, 1A8, 1A9, or 1A10 might result in potential DDI via inhibition of intestinal or hepatic UGTs.

Evaluation of the Success of High-Throughput Physiologically Based Pharmacokinetic (HT-PBPK) Modeling Predictions to Inform Early Drug Discovery

Minimizing in vitro and in vivo testing in early drug discovery with the use of physiologically based pharmacokinetic (PBPK) modeling and machine learning (ML) approaches has the potential to reduce discovery cycle times and animal experimentation. However, the prediction success of such an approach has not been shown for a larger and diverse set of compounds representative of a lead optimization pipeline. In this study, the prediction success of the oral (PO) and intravenous (IV) pharmacokinetics (PK) parameters in rats was assessed using a “bottom-up” approach, combining in vitro and ML inputs with a PBPK model. More than 240 compounds for which all of the necessary inputs and PK data were available were used for this assessment. Different clearance scaling approaches were assessed, using hepatocyte intrinsic clearance and protein binding as inputs. In addition, a novel high-throughput PBPK (HT-PBPK) approach was evaluated to assess the scalability of PBPK predictions for a larger number of compounds in drug discovery. The results showed that bottom-up PBPK modeling was able to predict the rat IV and PO PK parameters for the majority of compounds within a 2- to 3-fold error range, using both direct scaling and dilution methods for clearance predictions. The use of only ML-predicted inputs from the structure did not perform well when using in vitro inputs, likely due to clearance miss predictions. The HT-PBPK approach produced comparable results to the full PBPK modeling approach but reduced the simulation time from hours to seconds. In conclusion, a bottom-up PBPK and HT-PBPK approach can successfully predict the PK parameters and guide early discovery by informing compound prioritization, provided that good in vitro assays are in place for key parameters such as clearance.

Physiologically Based Pharmacokinetic (PBPK) Modeling of Clopidogrel and Its Four Relevant Metabolites for CYP2B6, CYP2C8, CYP2C19, and CYP3A4 Drug–Drug–Gene Interaction Predictions

The antiplatelet agent clopidogrel is listed by the FDA as a strong clinical index inhibitor of cytochrome P450 (CYP) 2C8 and weak clinical inhibitor of CYP2B6. Moreover, clopidogrel is a substrate of—among others—CYP2C19 and CYP3A4. This work presents the development of a whole-body physiologically based pharmacokinetic (PBPK) model of clopidogrel including the relevant metabolites, clopidogrel carboxylic acid, clopidogrel acyl glucuronide, 2-oxo-clopidogrel, and the active thiol metabolite, with subsequent application for drug–gene interaction (DGI) and drug–drug interaction (DDI) predictions. Model building was performed in PK-Sim^® using 66 plasma concentration-time profiles of clopidogrel and its metabolites. The comprehensive parent-metabolite model covers biotransformation via carboxylesterase (CES) 1, CES2, CYP2C19, CYP3A4, and uridine 5′-diphospho-glucuronosyltransferase 2B7. Moreover, CYP2C19 was incorporated for normal, intermediate, and poor metabolizer phenotypes. Good predictive performance of the model was demonstrated for the DGI involving CYP2C19, with 17/19 predicted DGI AUC_last and 19/19 predicted DGI C_max ratios within 2-fold of their observed values. Furthermore, DDIs involving bupropion, omeprazole, montelukast, pioglitazone, repaglinide, and rifampicin showed 13/13 predicted DDI AUC_last and 13/13 predicted DDI C_max ratios within 2-fold of their observed ratios. After publication, the model will be made publicly accessible in the Open Systems Pharmacology repository.

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.

Prediction of Drug-Drug Interaction Between Dabrafenib and Irinotecan via UGT1A1-Mediated Glucuronidation

BACKGROUND

Dabrafenib and irinotecan are two drugs that can be utilized to treat melanoma. A previous in vivo study has shown that dabrafenib enhances the antitumor activity of irinotecan in a xenograft model with unclear mechanism.

OBJECTIVES

This study aims to investigate the inhibition of dabrafenib on SN-38 (the active metabolite of irinotecan) glucuronidation, trying to elucidate the possible mechanism underlying the synergistic effect and to provide a basis for further development and optimization of this combination in clinical research.

METHODS

Recombinant human uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) and human liver microsomes (HLMs) were employed to catalyze the glucuronidation of SN-38 in vitro. Inhibition kinetic analysis and quantitative prediction study were combined to predict drug-drug interaction (DDI) potential in vivo.

RESULTS

Dabrafenib noncompetitively inhibited SN-38 glucuronidation in pooled HLMs and recombinant UGT1A1 with unbound inhibitor constant (K_i,u) values of 12.43 ± 0.28 and 3.89 ± 0.40 μM, respectively. Based on the in vitro K_i,u value and estimation of kinetic parameters, dabrafenib administered at 150 mg twice daily may result in about a 1-2% increase in the area under the curve (AUC) of SN-38 in vivo. However, the ratios of intra-enterocyte concentration of dabrafenib to K_i,u ([I]_gut/K_i,u) are 2.73 and 8.72 in HLMs and recombinant UGT1A1, respectively, indicating a high risk of intestinal DDI when dabrafenib was used in combination with irinotecan.

CONCLUSION

Dabrafenib is a potent noncompetitive inhibitor of UGT1A1 and may bring potential risk of DDI when combined with irinotecan.

Potential herb-drug interaction risk of thymoquinone and phenytoin

Thymoquinone is a main bioactive compound of Nigella sativa L. (N.sativa), which has been used for clinical studies in the treatment of seizures due to its beneficial neuroprotective activity and antiepileptic effects. It has been evidenced that thymoquinone may inhibit the activity of cytochrome P450 2C9 (CYP2C9). However, little is known about the effect of thymoquinone or N.sativa on the pharmacokinetic behavior of phenytoin, a second-line drug widely used in the management of status epilepticus. In this study, we systematically investigated the risk of the potential pharmacokinetic drug interaction between thymoquinone and phenytoin. The inhibitory effect of thymoquinone on phenytoin hydroxylation activity by CYP2C9 was determined using UPLC-MS/MS by measuring the formation rates for p-hydroxyphenytoin (p-HPPH). The potential for drug-interaction between thymoquinone and phenytoin was quantitatively predicted by using in vitro-in vivo extrapolation (IVIVE). Our data demonstrated that thymoquinone displayed effective inhibition against phenytoin hydroxylation activity. Enzyme kinetic studies showed that thymoquinone exerted a competitive inhibition against phenytoin hydroxylation with a K_i value of 4.45 ± 0.51 μM. The quantitative prediction from IVIVE suggested that the co-administration of thymoquinone (>18 mg/day) or thymoquinone-containing herbs (N.sativa > 1 g/day or N.sativa oil >1 g/day) might result in a clinically significant herb-drug interactions. Additional caution should be taken when thymoquinone or thymoquinone-containing herbs are co-administered with phenytoin, which may induce unexpected potential herb-drug interactions via the inhibition of CYP2C9.

INTERSYSTEM EXTRAPOLATION FACTORS (ISEF) ARE SUBSTRATE-DEPENDENT FOR CYP3A4: IMPACT ON CYTOCHROME P450 REACTION PHENOTYPING

The use of intersystem extrapolation factors (ISEF) is required for the quantitative scaling of drug metabolism data generated in individually expressed cytochrome P450 enzymes when estimating fractional contribution to metabolism by P450 enzymes in vivo (f_m,_CYP). For successful prediction of f_m, ISEF values must be universal across all substrates for any individual enzyme. In this study, ISEF values were generated for ten CYP3A4 selective substrates using a common source of recombinant heterologously expressed CYP3A4 and a pool of human liver microsomes. The resulting ISEF values for CYP3A4 were substrate-dependent and ranged 8-fold, with the highest value generated from intrinsic clearance of midazolam depletion (0.36) and the lowest from quinidine depletion (0.044). Application of these ISEF values for estimation of the fractional contribution of CYP3A4 and CYP2C19 to omeprazole clearance yielded values that ranged from 0.21-0.63 and 0.37-0.79, respectively, as compared to back-extrapolated in vivo f_m values of 0.27 (CYP3A4) and 0.85 (CYP2C19) from clinical pharmacokinetic data. For risperidone, estimated f_m values for CYP3A4 and CYP2D6 ranged from 0.87-0.98 and 0.02-0.13, respectively, as compared to in vivo values of 0.36 (CYP3A4) and 0.63-0.88 (CYP2D6), showing that the importance of CYP3A4 was over-estimated and the importance of CYP2D6 under-estimated. Overall, these findings suggest that ISEF values for CYP3A4 can vary with the marker substrate used to derive them, thereby reducing the effectiveness of the approach of using metabolism data from rCYP3A4 with ISEF values for the prediction of f_m values in vivo. Significance Statement Intersystem extrapolation factors (ISEF) are utilized for assigning fractional contributions of individual enzymes to drug clearance (f_m) from drug metabolism data generated in recombinant P450s. The present data shows that ISEF values for cytochrome P4503A4 vary with the substrate. This can lead to variable and erroneous prediction of f_m.

Evaluation of ADMET PredictorTM in early discovery DMPK project work

A dataset consisting of measured values for LogD, solubility, metabolic stability in human liver microsomes (HLM) and Caco-2 permeability was used to evaluate the prediction models for lipophilicity (S+LogD), water solubility (S+Sw_pH), metabolic stability in HLM (CYP_HLM_Clint), intestinal permeability (S+Peff) and P-gp substrate identification (P-gp substrate) in the software ADMET Predictor^TM (AP) from Simulations Plus. The dataset consisted of a total of 4794 compounds, with at least data from metabolic stability determinations in HLM, from multiple discovery projects at Medivir. Our evaluation shows that the global AP models can be used for categorization of high and low values based on predicted results for metabolic stability in HLM and intestinal permeability, and to give good predictions of LogD (R²=0.79), guiding the synthesis of new compounds and for prioritzing in vitro ADME experiments. The model seems to overpredict solubility for the Medivir compounds, however. We also used the in-house datasets to build local models for LogD, solubility, metabolic stability and permeability by using artificial neural network (ANN) models in the optional Modeler^TM module of AP. Predictions of the test sets were performed with both the global and the local models and the R² value for linear regression for predicted versus measured HLM CL_int based on logarithmic data was 0.72 for the in-house model and 0.53 for the AP model. The improved predictions with the local models are likely explained both by the specific chemical space of the Medivir dataset and lab specific assay conditions for parameters which require biological assay systems. Significance Statement AP is useful early in projects for predicting and categorizing LogD, metabolic stability and permeability, to guide the synthesis of new compounds and for prioritizing in vitro ADME experiments. The building of local in-house prediction models with the optional AP Modeler Module can give improved prediction success since these models are built on data from the same experimental setup and can also be based on compounds with similar structures.

HLM-beads: Rapid Assessment of Nonspecific Binding to Human Liver Microsomes Using Magnetizable Beads

In early drug development, drug-drug interaction risk is routinely assessed using human liver microsomes (HLMs). Nonspecific binding of drugs to HLMs can affect the determination of accurate enzyme parameters (K_m, K_i, K_I). Previously, we described a novel in vitro model consisting of HLMs bound to magnetizable beads [HLM-magnetizable-beads system (HLM-beads)]. The HLM-beads enable rapid separation of HLMs from incubation media by applying a magnetic field. Here, HLM-beads were further characterized and evaluated as a tool to assess HLM nonspecific binding of small molecules. The free fractions (f_u,mic) of 13 compounds (chosen based on their pKa values) were determined using HLM-beads under three HLM concentrations (0.025, 0.50, and 1.0 mg/ml) and compared with those determined by equilibrium dialysis. Most f_u,mic values obtained using HLM-beads were within 0.5- to 2-fold of the values determined using equilibrium dialysis. The highest fold difference were observed for high binders itraconazole and BIRT2584 (1.9- to 2.9-fold), as the pronounced adsorption of these compounds to the equilibrium dialysis apparatus interfered with their f_u,mic determination. Correlation and linear regression analysis of the f_u,mic values generated using HLM-beads and equilibrium dialysis was conducted. Overall, a good correlation of f_u,mic values obtained by the two methods were observed, as the r and R² values from correlational analysis and linear regression analysis were >0.9 and >0.89, respectively. These studies demonstrate that HLM-beads can produce comparable f_u,mic values as determined by equilibrium dialysis while reducing the time required for this type of study from hours to only 10 minutes and compound apparatus adsorption. SIGNIFICANCE STATEMENT: This work introduces a new method of rapidly assessing nonspecific microsomal binding using human liver microsomes bound to magnetizable beads.

Islatravir Is Not Expected to Be a Victim or Perpetrator of Drug-Drug Interactions via Major Drug-Metabolizing Enzymes or Transporters

Islatravir (MK-8591) is a nucleoside reverse transcriptase translocation inhibitor in development for the treatment and prevention of HIV-1. The potential for islatravir to interact with commonly co-prescribed medications was studied in vitro. Elimination of islatravir is expected to be balanced between adenosine deaminase-mediated metabolism and renal excretion. Islatravir did not inhibit uridine diphosphate glucuronosyltransferase 1A1 or cytochrome p450 (CYP) enzymes CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, or 3A4, nor did it induce CYP1A2, 2B6, or 3A4. Islatravir did not inhibit hepatic transporters organic anion transporting polypeptide (OATP) 1B1, OATP1B3, organic cation transporter (OCT) 1, bile salt export pump (BSEP), multidrug resistance-associated protein (MRP) 2, MRP3, or MRP4. Islatravir was neither a substrate nor a significant inhibitor of renal transporters organic anion transporter (OAT) 1, OAT3, OCT2, multidrug and toxin extrusion protein (MATE) 1, or MATE2K. Islatravir did not significantly inhibit P-glycoprotein and breast cancer resistance protein (BCRP); however, it was a substrate of BCRP, which is not expected to be of clinical significance. These findings suggest islatravir is unlikely to be the victim or perpetrator of drug-drug interactions with commonly co-prescribed medications, including statins, diuretics, anti-diabetic drugs, proton pump inhibitors, anticoagulants, benzodiazepines, and selective serotonin reuptake inhibitors.

Inhibition of human UDP-glucuronosyltransferase enzyme by Dabrafenib: Implications for drug-drug interactions

Dabrafenib is a novel small molecule tyrosine kinase inhibitor (TKI) which is used to treat metastatic melanoma. The aim of this research was to survey the effects of dabrafenib on human UDP-glucuronosyltransferases (UGTs) and to evaluate the risk of drug-drug interactions (DDIs). The formation rates for 4-methylumbelliferone (4-MU) glucuronide and trifluoperazine-glucuronide in 12 recombinant human UGT isoforms with or without dabrafenib were measured and HPLC was used to investigate the inhibitory effects of dabrafenib on UGTs. Inhibition kinetic studies were also conducted. In vitro-in vivo extrapolation approaches were further used to predict the risk of DDI potentials of dabrafenib via inhibition of UGTs. Our data indicated that dabrafenib had a broad inhibitory effect on 4-MU glucuronidation by inhibiting the activities of UGTs, especially on UGT1A1, UGT1A7, UGT1A8, and UGT1A9, and dabrafenib could increase the area under the curve of co-administered drugs. Dabrafenib is a strong inhibitor of several UGTs and the co-administration of dabrafenib with drugs primarily metabolized by UGT1A1, 1A7, 1A8 or 1A9 may induce potential DDIs.

Contribution of Extrahepatic Aldehyde Oxidase Activity to Human Clearance

Aldehyde oxidase (AOX) is a soluble, cytosolic enzyme that metabolizes various N-heterocyclic compounds and organic aldehydes. It has wide tissue distribution with highest levels found in liver, kidney, and lung. Human clearance projections of AOX substrates by in vitro assessments in isolated liver fractions (cytosol, S9) and even hepatocytes have been largely underpredictive of clinical outcomes. Various hypotheses have been suggested as to why this is the case. One explanation is that extrahepatic AOX expression contributes measurably to AOX clearance and is at least partially responsible for the often observed underpredictions. Although AOX expression has been confirmed in several extrahepatic tissues, activities therein and potential contribution to overall human clearance have not been thoroughly studied. In this work, the AOX enzyme activity using the S9 fractions of select extrahepatic human tissues (kidney, lung, vasculature, and intestine) were measured using carbazeran as a probe substrate. Measured activities were scaled to a whole-body clearance using best-available parameters and compared with liver S9 fractions. Here, the combined scaled AOX clearance obtained from the kidney, lung, vasculature, and intestine is very low and amounted to <1% of liver. This work suggests that AOX metabolism from extrahepatic sources plays little role in the underprediction of activity in human. One of the notable outcomes of this work has been the first direct demonstration of AOX activity in human vasculature. SIGNIFICANCE STATEMENT: This work demonstrates aldehyde oxidase (AOX) activity is measurable in a variety of extrahepatic human tissues, including vasculature, yet activities and potential contributions to human clearance are relatively low and insignificant when compared with the liver. Additionally, the modeling of the tissue-specific in vitro kinetic data suggests that AOX may be influenced by the tissue it resides in and thus show different affinity, activity, and modified activity over time.

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.

In vitro inhibition of human UDP-glucuronosyltransferase (UGT) 1A1 by osimertinib, and prediction of in vivo drug-drug interactions

Osimertinib is the only third-generation epidermal growth factor receptor tyrosine-kinase inhibitor (EGFR-TKI) approved by Food and Drug Administration (FDA). This study aimed to know the inhibitory effect of osimertinib on human UDP-glucosyltransferases (UGTs) and human liver microsomes (HLMs), as well as to identify its potential to cause drug-drug interaction (DDI) arising from the modulation of UGT activity. High inhibitory effect of osimertinib was shown towards UGT1A1, 1A3, 1A6, 1A7, 1A8, 1A10, 2B7 and 2B15. Especially, osimertinib exhibited competitive inhibition against UGT1A1 with a K_i,u of 0.87 ± 0.12 μM. It also noncompetitively inhibited SN-38 glucuronidation in pooled HLMs with a K_i,u of 3.32 ± 0.25 μM. Results from quantitative prediction study indicated that osimertinib administered at 80 mg/day may result in a 4.83 % increase in the AUC of drugs mainly metabolized by UGT1A1, implying low risk of DDI via liver metabolism. However, the ratios of [I]_gut/K_i,u are much higher than 11 in HLMs and recombinant UGT1A1, indicating a risk for interaction in intestine. The effects of osimertinib on intestinal UGT should be paid more attention on to avoid unnecessary clinical DDI risks.

Investigation into MAO B-Mediated Formation of CC112273, a Major Circulating Metabolite of Ozanimod, in Humans and Preclinical Species: Stereospecific Oxidative Deamination of (S)-Enantiomer of Indaneamine (RP101075) by MAO B

Ozanimod, recently approved for treating relapsing multiple sclerosis, produced a disproportionate, active, MAO B-catalyzed metabolite (CC112273) that showed remarkable interspecies differences and led to challenges in safety testing. This study explored the kinetics of CC112273 formation from its precursor RP101075. Incubations with human liver mitochondrial fractions revealed K _Mapp, V _max, and intrinsic clearance (Cl_int) for CC112273 formation to be 4.8 μM, 50.3 pmol/min/mg protein, and 12 μl/min/mg, respectively, whereas Michaelis-Menten constant (K _M) with human recombinant MAO B was 1.1 μM. Studies with liver mitochondrial fractions from preclinical species led to K _Mapp, V _max, and Cl_int estimates of 3.0, 35, and 33 μM, 80.6, 114, 37.3 pmol/min/mg, and 27.2, 3.25, and 1.14 μl/min/mg in monkey, rat, and mouse, respectively, and revealed marked differences between rodents and primates, primarily attributable to differences in the K _M Comparison of Cl_int estimates revealed monkey to be ∼2-fold more efficient and the mouse and rat to be 11- and 4-fold less efficient than humans in CC112273 formation. The influence of stereochemistry on MAO B-mediated oxidation was also investigated using the R-isomer of RP101075 (RP101074). This showed marked selectivity toward catalysis of the S-isomer (RP101075) only. Docking into MAO B crystal structure suggested that although both the isomers occupied its active site, only the orientation of RP101075 presented the C-H on the α-carbon that was ideal for the C-H bond cleavage, which is a requisite for oxidative deamination. These studies explain the basis for the observed interspecies differences in the metabolism of ozanimod as well as the substrate stereospecificity for formation of CC112273. SIGNIFICANCE STATEMENT: This study evaluates the enzymology and the species differences of the major circulating metabolite of ozanimod, CC112273. Additionally, the study also explores the influence of stereochemistry on MAO B-catalyzed reactions. The study is of significance to the DMD readers given that this oxidation is catalyzed by a non-cytochrome P450 enzyme, and that marked species difference and notable stereospecificity was observed in MAO B-catalyzed biotransformation when the indaneamine enantiomers were used as substrates.

Discovery and Characterization of the Biflavones From Ginkgo biloba as Highly Specific and Potent Inhibitors Against Human Carboxylesterase 2

Human carboxylesterase 2 (CES2), one of the most abundant hydrolases distributed in the small intestine, has been validated as a key therapeutic target to ameliorate the intestinal toxicity caused by irinotecan. This study aims to discover efficacious CES2 inhibitors from natural products and to characterize the inhibition potentials and inhibitory mechanisms of the newly identified CES2 inhibitors. Following high-throughput screening and evaluation of the inhibition potency of more than 100 natural products against CES2, it was found that the biflavones isolated from Ginkgo biloba displayed extremely potent CES2 inhibition activities and high specificity over CES1 (>1000-fold). Further investigation showed that ginkgetin, bilobetin, sciadopitysin and isoginkgetin potently inhibited CES2-catalyzed hydrolysis of various substrates, including the CES2 substrate-drug irinotecan. Notably, the inhibition potentials of four biflavones against CES2 were more potent than that of loperamide, a marketed anti-diarrhea agent used for alleviating irinotecan-induced intestinal toxicity. Inhibition kinetic analyses demonstrated that ginkgetin, bilobetin, sciadopitysin and isoginkgetin potently inhibited CES2-catalyzed fluorescein diacetate hydrolysis via a reversible and mixed inhibition manner, with K _i values of less than 100 nM. Ensemble docking and molecular dynamics revealed that these biflavones could tightly and stably bind on the catalytic cavity of CES2 via hydrogen bonding and π-π stacking interactions, while the interactions with CES1 were awfully poor. Collectively, this study reports that the biflavones isolated from Ginkgo biloba are potent and highly specific CES2 inhibitors, which offers several promising lead compounds for developing novel anti-diarrhea agent to alleviate irinotecan-induced diarrhea.

Systematic evaluation of structure-property relationships and pharmacokinetics in 6-(hetero)aryl-substituted matched pair analogs of amiloride and 5-(N,N-hexamethylene)amiloride

The K+-sparing diuretic amiloride elicits anticancer activities in multiple animal models. During our recent medicinal chemistry campaign aiming to identify amiloride analogs with improved properties for potential use in cancer, we discovered novel 6-(hetero)aryl-substituted amiloride and 5-(N,N-hexamethylene)amiloride (HMA) analogs with up to 100-fold higher potencies than the parent compounds against urokinase plasminogen activator (uPA), one of amiloride's putative anticancer targets, and no diuretic or antikaliuretic effects. Here, we report the systematic evaluation of structure-property relationships (lipophilicity, aqueous solubility and in vitro metabolic stability in human and mouse liver microsomes) in twelve matched pair analogs selected from our 6-substituted amiloride and HMA libraries. Mouse plasma stability, plasma protein binding, Caco-2 cell permeability, cardiac ion channel activity and pharmacokinetics in mice (PO and IV) and rats (IV) are described alongside amiloride and HMA comparators for a subset of the four most promising matched-pair analogs. The findings combined with earlier uPA activity/selectivity and other data ultimately drove selection of two analogs (AA1-39 and AA1-41) that showed efficacy in separate mouse cancer metastasis studies.