Physiologically Based Pharmacokinetic Modeling to Predict the Impact of Liver Cirrhosis on Glucuronidation via UGT1A4 and UGT2B7/2B4-A Case Study with Midazolam.

Hepatic impairment, due to liver cirrhosis, decreases the activity of cytochrome P450 enzymes (CYPs). The use of physiologically based pharmacokinetic (PBPK) modeling to predict this effect for CYP substrates has been well-established, but the effect of cirrhosis on uridine-glucuronosyltransferase (UGT) activities is less studied and few PBPK models have been reported. UGT enzymes are involved in primary N-glucuronidation of midazolam and glucuronidation of 1'-OH-midazolam following CYP3A hydroxylation. In this study, Simcyp was used to establish PBPK models for midazolam, its primary metabolites midazolam-N-glucuronide (UGT1A4) and 1'-OH midazolam (CYP3A4/3A5), and the secondary metabolite 1'-OH-midazolam-O-glucuronide (UGT2B7/2B4), allowing to simulate the impact of liver cirrhosis on the primary and secondary glucuronidation of midazolam. The model was verified in noncirrhotic subjects before extrapolation to cirrhotic patients of Child-Pugh (CP) classes A, B, and C. Our model successfully predicted the exposures of midazolam and its metabolites in noncirrhotic and cirrhotic patients, with 86% of observed plasma concentrations within 5th-95th percentiles of predictions and observed geometrical mean of area under the plasma concentration curve between 0 hours to infinity and maximal plasma concentration within 0.7- to 1.43-fold of predictions. The simulated metabolic ratio defined as the ratio of the glucuronide metabolite AUC over the parent compound AUC (AUCglucuronide/AUCparent, metabolic ratio [MR]), was calculated for midazolam-N-glucuronide to midazolam (indicative of UGT1A4 activity) and decreased by 40% (CP A), 48% (CP B), and 75% (CP C). For 1'-OH-midazolam-O-glucuronide to 1'-OH-midazolam, the MR (indicative of UGT2B7/2B4 activity) dropped by 35% (CP A), 51% (CP B), and 64% (CP C). These predicted MRs were corroborated by the observed data. This work thus increases confidence in Simcyp predictions of the effect of liver cirrhosis on the pharmacokinetics of UGT1A4 and UGT2B7/UGT2B4 substrates. SIGNIFICANCE STATEMENT: This article presents a physiologically based pharmacokinetic model for midazolam and its metabolites and verifies the accurate simulation of pharmacokinetic profiles when using the Simcyp hepatic impairment population models. Exposure changes of midazolam-N-glucuronide and 1'-OH-midazolam-O-glucuronide reflect the impact of decreases in UGT1A4 and UGT2B7/2B4 glucuronidation activity in cirrhotic patients. The approach used in this study may be extended to verify the modeling of other uridine glucuronosyltransferase enzymes affected by liver cirrhosis.

PBPK Modelling for Drugs Cleared by Non-CYP Enzymes: State-of-the-Art and Future Perspectives.

Physiologically-based pharmacokinetic (PBPK) modeling has become the established method for predicting human pharmacokinetics (PK) and drug-drug interactions (DDI). The number of drugs cleared by non-CYP enzyme metabolism has increased steadily and to date, there is no consolidated overview of PBPK modeling for drugs cleared by non-CYP enzymes. This review aims to describe the state-of-the-art for PBPK modeling for drugs cleared via non-CYP enzymes, to identify successful strategies, to describe gaps and to provide suggestion to overcome them. To this end, we conducted a detailed literature search and found 58 articles published before the 1st of January 2023 containing 95 examples of clinical PBPK models for 62 non-CYP enzyme substrates. Reviewed articles covered the drug clearance by uridine 5'-diphospho-glucuronosyltransferases (UGTs), aldehyde oxidase (AO), flavin-containing monooxygenases (FMOs), sulfotransferases (SULTs) and carboxylesterases (CES), with UGT2B7, UGT1A9, CES1, FMO3 and AO being the enzymes most frequently involved. In vitro-in vivo extrapolation (IVIVE) of intrinsic clearance and the bottom-up PBPK modeling involving non-CYP enzymes remains challenging. We observed that the middle-out modeling approach was applied in 80% of the cases, with metabolism parameters optimized in 73% of the models. Our review could not identify a standardized approach used for model optimization based on clinical data, with manual optimization employed most frequently. Successful development of models for UGT2B7, UGT1A9, CES1, and FMO3 substrates provides a foundation for other drugs metabolized by these enzymes and guides the way forward in creating PBPK models for other enzymes in these families. Significance Statement Our review charts the rise of PBPK modeling for drugs cleared by non-CYP enzymes. Analyzing 58 articles and 62 non-CYP enzyme substrates, we found that UGTs, AO, FMOs, SULTs, and CES were the main enzyme families involved and that UGT2B7, UGT1A9, CES1, FMO3 and AO are the individual enzymes with the strongest PBPK modeling precedents. Approaches established for these enzymes can now be extended to additional substrates and to drugs metabolized by enzymes that are similarly well characterized.

Quantitative Cytochrome P450 3A4 Induction Risk Assessment Using Human Hepatocytes Complemented with Pregnane X Receptor-Activating Profiles.

Reliable in vitro to in vivo translation of cytochrome P450 (CYP) 3A4 induction potential is essential to support risk mitigation for compounds during pharmaceutical discovery and development. In this study, a linear correlation of CYP3A4 mRNA induction potential in human hepatocytes with the respective pregnane-X receptor (PXR) activation in a reporter gene assay using DPX2 cells was successfully demonstrated for 13 clinically used drugs. Based on this correlation, using rifampicin as a positive control, the magnitude of CYP3A4 mRNA induction for 71 internal compounds at several concentrations up to 10 µM (n = 90) was predicted within 2-fold error for 64% of cases with only a few false positives (19%). Furthermore, the in vivo area under the curve reduction of probe CYP substrates was reasonably predicted for eight marketed drugs (carbamazepine, dexamethasone, enzalutamide, nevirapine, phenobarbital, phenytoin, rifampicin, and rufinamide) using the static net effect model using both the PXR activation and CYP3A4 mRNA induction data. The liver exit concentrations were used for the model in place of the inlet concentrations to avoid false positive predictions and the concentration achieving twofold induction (F2) was used to compensate for the lack of full induction kinetics due to cytotoxicity and solubility limitations in vitro. These findings can complement the currently available induction risk mitigation strategy and potentially influence the drug interaction modeling work conducted at clinical stages. SIGNIFICANCE STATEMENT: The established correlation of CYP3A4 mRNA in human hepatocytes to PXR activation provides a clear cut-off to identify a compound showing an in vitro induction risk, complementing current regulatory guidance. Also, the demonstrated in vitro-in vivo translation of induction data strongly supports a clinical development program although limitations remain for drug candidates showing complex disposition pathways, such as involvement of auto-inhibition/induction, active transport and high protein binding.

Drug Design and Success of Prospective Mouse In Vitro-In Vivo Extrapolation (IVIVE) for Predictions of Plasma Clearance (CLp) from Hepatocyte Intrinsic Clearance (CLint).

Hepatocyte intrinsic clearance (CLint) and methods of in vitro-in vivo extrapolation (IVIVE) are often used to predict plasma clearance (CLp) in drug discovery. While the prediction success of this approach is dependent on the chemotype, specific molecular properties and drug design features that govern these outcomes are poorly understood. To address this challenge, we investigated the success of prospective mouse CLp IVIVE across 2142 chemically diverse compounds. Dilution scaling, which assumes that the free fraction in hepatocyte incubations (fu,inc) is governed by binding to the 10% of serum in the incubation medium, was used as our default CLp IVIVE approach. Results show that predictions of CLp are better for smaller (molecular weight (MW) < 500 Da), less polar (total polar surface area (TPSA) < 100 Å2, hydrogen bond donor (HBD) ≤1, hydrogen bond acceptor (HBA) ≤ 6), lipophilic (log D > 3), and neutral compounds, with low HBD count playing the key role. If compounds are classified according to their chemical space, predictions were good for compounds resembling central nervous system (CNS) drugs [average absolute fold error (AAFE) of 2.05, average fold error (AFE) of 0.90], moderate for classical druglike compounds (according to Lipinski, Veber, and Ghose guidelines; AAFE of 2.55; AFE of 0.68), and poor for nonclassical "beyond the rule of 5" compounds (AAFE of 3.31; AFE of 0.41). From the perspective of measured druglike properties, predictions of CLp were better for compounds with moderate-to-high hepatocyte CLint (>10 µL/min/106 cells), high passive cellular permeability (Papp > 100 nm/s), and moderate observed CLp (5-50 mL/min/kg). Influences of plasma protein binding (fu,p) and P-glycoprotein (Pgp) apical efflux ratio (AP-ER) were less pronounced. If the extended clearance classification system (ECCS) is applied, predictions were good for class 2 (Papp > 50 nm/s; neutral or basic; AAFE of 2.35; AFE of 0.70) and acceptable for class 1A compounds (AAFE of 2.98; AFE of 0.70). Classes 1B, 3 A/B, and 4 showed poor outcomes (AAFE > 3.80; AFE < 0.60). Functional groups trending toward weaker CLp IVIVE were esters, carbamates, sulfonamides, carboxylic acids, ketones, primary and secondary amines, primary alcohols, oxetanes, and compounds liable to aldehyde oxidase metabolism, likely due to multifactorial reasons. Multivariate analysis showed that multiple properties are relevant, combining together to define the overall success of CLp IVIVE. Our results indicate that the current practice of prospective CLp IVIVE is suitable only for CNS-like compounds and well-behaved classical druglike space (e.g., high permeability or ECCS class 2) without challenging functional groups. Unfortunately, based on existing mouse data, prospective CLp IVIVE for complex and nonclassical chemotypes is poor and hardly better than random guessing. This is likely due to complexities such as extrahepatic metabolism and transporter-mediated disposition which are poorly captured by this methodology. With small-molecule drug discovery increasingly evolving toward nonclassical and complex chemotypes, existing CLp IVIVE methodology will require improvement. While empirical correction factors may bridge the gap in the near future, improved and new in vitro assays, data integration models, and machine learning (ML) methods are increasingly needed to address this challenge and reduce the number of nonclinical pharmacokinetic (PK) studies.

Evaluation of the drug disposition of RO7049389 with in vitro data and human mass balance supported by physiologically based pharmacokinetic modelling.

AIMS: RO7049389 (linvencorvir) is a developmental oral treatment for chronic hepatitis B virus infection. The aim of this work was to conduct mass balance (MB) and absolute bioavailability (BA) analyses in healthy volunteers, alongside in vitro evaluations of the metabolism of RO7049389 and a major circulating active metabolite M5 in human hepatocytes, and physiologically based pharmacokinetic (PBPK) modelling to refine the underlying drug disposition paradigm. METHODS: Participants in the clinical study (MB: Caucasian, male, n = 6; BA: Caucasian and Asian, male and female, n = 16, 8 in each ethnic groups) received oral [14 C] or unlabelled RO7049389 (600/1000 mg) followed by 100 µg intravenous [13 C]RO7049389. Metabolic pathways with fractions metabolized-obtained from the in vitro incubation results of 10 µM [14 C]RO7049389 and 1 µM M5 with (long-term cocultured) human hepatocytes in the absence and presence of the cytochrome P450 3A4 (CYP3A4) inhibitor itraconazole-were used to complement the PBPK models, alongside the clinical MB and BA data. RESULTS: The model performance in predicting the pharmacokinetic profiles of RO7049389 and M5 aligned with clinical observations in Caucasians and was also successfully applied to Asians. Accordingly, the drug disposition pathways for RO7049389 were postulated with newly characterized estimates of the fractions: biliary excretion by P-glycoprotein (~41%), direct glucuronidation via uridine 5'-diphosphoglucuronosyltransferase 1A3 (~11%), hexose conjugation (~6%), oxidation by CYP3A4 (~28%) and other oxidation reactions (~9%). CONCLUSION: These results support the ongoing clinical development program for RO7049389 and highlight the broader value of PBPK and MB analyses in drug development.

Accelerating Clinical Development of Idasanutlin through a Physiologically Based Pharmacokinetic Modeling Risk Assessment for CYP450 Isoenzyme-Related Drug-Drug Interactions.

Idasanutlin is a potent inhibitor of the p53-MDM2 interaction that enables reactivation of the p53 pathway, which induces cell cycle arrest and/or apoptosis in tumor cells expressing functional p53. It was investigated for the treatment of solid tumors and several hematologic indications such as relapsed/refractory acute myeloid leukemia, polycythemia vera, or non-Hodgkin lymphoma. For safety reasons, it cannot be given in healthy volunteers for drug-drug interaction (DDI) explorations. This triggered the need for in silico explorations on top of the one available CYP3A clinical DDI study with posaconazole in solid tumor patients. Idasanutlin's clearance is dependent on CYP3A4/2C8 forming its major circulating metabolite M4, with contributions from UGT1A3 and biliary excretion. Idasanutlin and M4 have low permeability, very low clearance, and extremely low unbound fraction in plasma (<0.001), which makes in vitro data showing inhibition on CYP3A4/2C8 enzymes challenging to translate to clinical relevance. Physiologically-based pharmacokinetic models of idasanutlin and M4 have been established to simulate perpetrator and victim DDI scenarios and to evaluate whether further DDI studies in oncology patients are necessary. Modeling indicated that idasanutlin and M4 would show no or weak clinical inhibition of selective CYP3A4/2C8 substrates. Co-administered strong CYP3A and CYP2C8 inhibitors might lead to weak or moderate idasanutlin exposure increases, and the strong inducer rifampicin might cause moderate exposure reduction. As the simulated idasanutlin systemic exposure changes would be within the range of observed intrinsic variability, the target population can take co-medications that are either CYP2C8/3A4 inhibitors or weak/moderate CYP2C8/3A4 inducers without dose adjustment. SIGNIFICANCE STATEMENT: Clinical trials for idasanutlin are restricted to cancer patients, which imposes practical, scientific, and ethical challenges on drug-drug interaction investigations. Furthermore, idasanutlin and its major circulating metabolite have very challenging profiles of absorption, distribution, metabolism and excretion including high protein binding, low permeability and a combination of different elimination pathways each with extremely low clearance. Nonetheless, physiologically-based pharmacokinetic models could be established and applied for drug-drug interaction risk assessment and were especially useful to provide guidance on concomitant medications in patients.

Estimation of Fraction Metabolized by Cytochrome P450 Enzymes Using Long-Term Cocultured Human Hepatocytes.

Estimation of the fraction of a drug metabolized by individual hepatic CYP enzymes relative to hepatic metabolism (fm,CYP) or total clearance h as been challenging for low turnover compounds due to insufficient resolution of the intrinsic clearance (CLint) measurement in vitro and difficulties in quantifying the formation of low abundance metabolites. To overcome this gap, inhibition of drug depletion or selective metabolite formation for 7 marker CYP substrates was investigated using chemical inhibitors and a micro-patterned hepatocyte coculture system (HepatoPac). The use of 3 µM itraconazole was successfully validated for estimation of fm,CYP3A4 by demonstration of fm values within a 2-fold of in vivo estimates for 10 out of 13 CYP3A4 substrates in a reference set of marketed drugs. Other CYP3A4 inhibitors (ketoconazole and posaconazole) were not optimal for estimation of fm,CYP3A4 for low turnover compounds due to their high CLint. The current study also demonstrated that selective inhibition sufficient for fm calculation was achieved by inhibitors of CYP1A2 (20 µM furafylline), CYP2C8 (40 µM montelukast), CYP2C9 (40 µM sulfaphenazole), CYP2C19 [3 µM (-)N-3-benzyl-phenobarbital], and CYP2D6 (5 µM quinidine). Good estimation of fm,CYP2B6 was not possible in this study due to the poor selectivity of the tested inhibitor (20 µM ticlopidine). The approach verified in this study can result in an improved fm estimation that is aligned with the regulatory agencies' guidance and can support a victim drug-drug interaction risk assessment strategy for low clearance discovery and development drug candidates. SIGNIFICANCE STATEMENT: Successful qualification of a chemical inhibition assay for estimation of fraction metabolized requires chemical inhibitors that retain sufficient unbound concentrations over time in the incubates. The current cocultured hepatocyte assay enabled estimation of fraction metabolized, especially by CYP3A4, during the drug discovery phase where metabolite quantification methods may not be available. The method enables the assessment of pharmacokinetic variability and victim drug-drug interaction risks due to enzyme polymorphism or inhibition/induction with more confidence, especially for low clearance drug candidates.

Addressing Today's Absorption, Distribution, Metabolism, and Excretion (ADME) Challenges in the Translation of In Vitro ADME Characteristics to Humans: A Case Study of the SMN2 mRNA Splicing Modifier Risdiplam.

Small molecules that present complex absorption, distribution, metabolism, and elimination (ADME) properties can be challenging to investigate as potential therapeutics. Acquiring data through standard methods can yield results that are insufficient to describe the in vivo situation, which can affect downstream development decisions. Implementing in vitro-in vivo-in silico strategies throughout the drug development process is effective in identifying and mitigating risks while speeding up their development. Risdiplam (Evrysdi)-an orally bioavailable, small molecule approved by the US Food and Drug Administration and more recently by the European Medicines Agency for the treatment of patients ≥2 months of age with spinal muscular atrophy-is presented here as a case study. Risdiplam is a low-turnover compound whose metabolism is mediated through a non-cytochrome P450 enzymatic pathway. Four main challenges of risdiplam are discussed: predicting in vivo hepatic clearance, determining in vitro metabolites with regard to metabolites in safety testing guidelines, elucidating enzymes responsible for clearance, and estimating potential drug-drug interactions. A combination of in vitro and in vivo results was successfully extrapolated and used to develop a robust physiologically based pharmacokinetic model of risdiplam. These results were verified through early clinical studies, further strengthening the understanding of the ADME properties of risdiplam in humans. These approaches can be applied to other compounds with similar ADME profiles, which may be difficult to investigate using standard methods. SIGNIFICANCE STATEMENT: Risdiplam is the first approved, small-molecule, survival of motor neuron 2 mRNA splicing modifier for the treatment of spinal muscular atrophy. The approach taken to characterize the absorption, distribution, metabolism, and excretion (ADME) properties of risdiplam during clinical development incorporated in vitro-in vivo-in silico techniques, which may be applicable to other small molecules with challenging ADME. These strategies may be useful in improving the speed at which future drug molecules can be developed.

In vitro and clinical investigations to determine the drug-drug interaction potential of entrectinib, a small molecule inhibitor of neurotrophic tyrosine receptor kinase (NTRK).

Background Entrectinib is a CNS-active, potent inhibitor of tyrosine receptor kinases A/B/C, ROS1 and anaplastic lymphoma kinase approved for use in patients with solid tumors. We describe the in vitro and clinical studies investigating potential entrectinib drug-drug interactions. Methods In vitro studies with human biomaterials assessed the enzymes involved in entrectinib metabolism, and whether entrectinib modulates the activity of the major cytochrome P450 (CYP) enzymes or drug transporter P-glycoprotein. Clinical studies investigated the effect of a strong CYP3A4 inhibitor (itraconazole) and inducer (rifampin) on single-dose entrectinib pharmacokinetics. The effect of entrectinib on sensitive probe substrates for CYP3A4 (midazolam) and P-glycoprotein (digoxin) were also investigated. Results Entrectinib is primarily metabolized by CYP3A4. In vitro, entrectinib is a CYP3A4/5 inhibitor (IC50 2 µM) and a weak CYP3A4 inducer. Entrectinib inhibited P-glycoprotein (IC50 1.33 µM) but is a poor substrate. In healthy subjects, itraconazole increased entrectinib Cmax and AUC by 73% and 504%, respectively, and rifampin decreased entrectinib Cmax and AUC by 56% and 77%, respectively. Single dose entrectinib did not affect midazolam AUC, although Cmax decreased by 34%. Multiple dose entrectinib increased midazolam AUC by 50% and decreased Cmax by 21%. Single dose entrectinib increased digoxin AUC and Cmax by 18% and 28%, respectively, but did not affect digoxin renal clearance. Conclusions Entrectinib is a CYP3A4 substrate and is sensitive to the effects of coadministered moderate/strong CYP3A4 inhibitors and strong inducers, and requires dose adjustment. Entrectinib is a weak inhibitor of CYP3A4 and P-glycoprotein and no dose adjustments are required with CYP3A4/P- glycoprotein substrates.Registration Number (Study 2) NCT03330990 (first posted online November 6, 2017) As studies 1 and 3 are phase 1 trials in healthy subjects, they are not required to be registered.

A translational strategy employing physiologically based modelling to predict the pharmacological active dose of RO7119929, an oral prodrug of a targeted cancer immunotherapy TLR7 agonist.

RO7119929 is being developed as an orally administered prodrug of the TLR7-specific agonist and active drug, RO7117418, for the treatment of patients with solid tumours.In this publication, we present a case study wherein the human pharmacokinetics and pharmacological active dose were prospectively predicted following oral administration of the prodrug.A simple translational pharmacokinetic-pharmacodynamic strategy was applied to predict the pharmacological active dose of the prodrug in human. In vivo studies in monkey showed that an unbound plasma exposure of active drug of 1.5 ng/mL elicited secretion of key serum pharmacodynamic cytokine and chemokine biomarkers in monkey. This threshold of 1.5 ng/mL was close to the minimum effective concentration of active drug required to induce cytokine secretion in human peripheral blood mononuclear cells (3 ng/mL).Measured in vitro physicochemical and biochemical properties of the prodrug and active drug were applied as input parameters in physiologically based pharmacokinetic models to predict the pharmacokinetics of active drug after oral dosing of the prodrug in humans. Then, using the PBPK model, a dose which delivered an unbound plasma Cmax in line with the target pharmacodynamic threshold of 1.5 ng/mL was found. This defined the lowest pharmacologically active dose as 3 mg.The prodrug entered the clinic in 2020 in patients with primary or secondary liver cancers. Clear pharmacodynamic, transient, and dose-dependent cytokine induction was observed at prodrug doses > 1 mg.

Current practices for QSP model assessment: an IQ consortium survey.

Quantitative Systems Pharmacology (QSP) modeling is increasingly applied in the pharmaceutical industry to influence decision making across a wide range of stages from early discovery to clinical development to post-marketing activities. Development of standards for how these models are constructed, assessed, and communicated is of active interest to the modeling community and regulators but is complicated by the wide variability in the structures and intended uses of the underlying models and the diverse expertise of QSP modelers. With this in mind, the IQ Consortium conducted a survey across the pharmaceutical/biotech industry to understand current practices for QSP modeling. This article presents the survey results and provides insights into current practices and methods used by QSP practitioners based on model type and the intended use at various stages of drug development. The survey also highlights key areas for future development including better integration with statistical methods, standardization of approaches towards virtual populations, and increased use of QSP models for late-stage clinical development and regulatory submissions.

Application of the Extended Clearance Classification System (ECCS) in Drug Discovery and Development: Selection of Appropriate In Vitro Tools and Clearance Prediction.

In vitro to in vivo extrapolation (IVIVE) to predict human hepatic clearance, including metabolism and transport, requires extensive experimental resources. In addition, there may be technical challenges to measure low clearance values. Therefore, prospective identification of rate-determining step(s) in hepatic clearance through application of the Extended Clearance Classification System (ECCS) could be beneficial for optimal compound characterization. IVIVE for hepatic intrinsic clearance (CLint,h) prediction is conducted for a set of 36 marketed drugs with low-to-high in vivo clearance, which are substrates of metabolic enzymes and active uptake transporters in the liver. The compounds were assigned to the ECCS classes, and CLint,h, estimated with HepatoPac (a micropatterned hepatocyte coculture system), was compared with values calculated based on suspended hepatocyte incubates. An apparent permeability threshold (apical to basal) of 50 nm/s in LLC-PK1 cells proved optimal for ECCS classification. A reasonable performance of the IVIVE for compounds across multiple classes using HepatoPac was achieved (with 2-3-fold error), except for substrates of uptake transporters (class 3b), for which scaling of uptake clearance using plated hepatocytes is more appropriate. Irrespective of the ECCS assignment, metabolic clearance can be estimated well using HepatoPac. The validation and approach elaborated in the present study can result in proposed decision trees for the selection of the optimal in vitro assays guided by ECCS class assignment, to support compound optimization and candidate selection. SIGNIFICANCE STATEMENT: Characterization of the rate-determining step(s) in hepatic elimination could be on the critical path of compound optimization during drug discovery. This study demonstrated that HepatoPac and plated hepatocytes are suitable tools for the estimation of metabolic and active uptake clearance, respectively, for a larger set of marketed drugs, supporting a comprehensive strategy to select optimal in vitro tools and to achieve Extended Clearance Classification System-dependent in vitro to in vivo extrapolation for human clearance prediction.

A Study of the Effect of Cyclosporine on Fevipiprant Pharmacokinetics and its Absolute Bioavailability Using an Intravenous Microdose Approach.

This drug-drug interaction study determined the effect of cyclosporine, an inhibitor of organic anion transporting polypeptide (OATP) 1B3 and P-gp, on the pharmacokinetics (PK) of fevipiprant, an oral, highly selective, competitive antagonist of the prostaglandin D2 receptor 2 and a substrate of the two transporters. The concomitant administration of an intravenous microdose of stable isotope-labeled fevipiprant provided the absolute bioavailability of fevipiprant as well as mechanistic insights into its PK and sensitivity to drug interactions. Liquid chromatography-mass spectrometry/mass spectrometry was used to measure plasma and urine concentrations. Geometric mean ratios [90% confidence interval (CI)] for oral fevipiprant with or without cyclosporine were 3.02 (2.38, 3.82) for C max, 2.50 (2.17, 2.88) for AUClast, and 2.35 (1.99, 2.77) for AUCinf The geometric mean ratios (90% CI) for fevipiprant intravenous microdose with or without cyclosporine were 1.04 (0.86, 1.25) for C max, 2.04 (1.83, 2.28) for AUClast, and 1.95 (1.76, 2.16) for AUCinf The absolute bioavailability for fevipiprant was approximately 0.3 to 0.4 in the absence and 0.5 in the presence of cyclosporine. The intravenous microdose allowed differentiation between systemic and presystemic effects of cyclosporine on fevipiprant, demonstrating a small (approximately 1.2-fold) presystemic effect of cyclosporine and a larger (approximately twofold) effect on systemic elimination of fevipiprant. Uptake by OATP1B3 appears to be the rate-limiting step in the hepatic elimination of fevipiprant, whereas P-gp does not have a relevant effect on oral absorption. SIGNIFICANCE STATEMENT: The drug interaction investigated here with cyclosporine, an inhibitor of several drug transporters, provides a refined quantitative understanding of the role of active transport processes in liver and intestine for the absorption and elimination of fevipiprant as well as the basis to assess the need for dose adjustment in the presence of transporter inhibitors. The applied intravenous microdose approach presents a strategy to maximize learnings from a trial, limit the number and duration of clinical trials, and enhance mechanistic drug-drug interaction understanding.

Assessment of the pulmonary CYP1A1 metabolism of mavoglurant (AFQ056) in rat.

1. AFQ056 phenotyping results indicate that CYP1A1 is responsible for the formation of the oxidative metabolite, M3. In line with the predominant assumption that CYP1A1 is mainly expressed in extrahepatic tissues, only traces of M3 were detected in hepatic systems. The aim of this study was to investigate the pulmonary CYP1A1 mediated metabolism of AFQ056 in rat. 2. Western blot analysis confirmed that CYP1A1 is expressed in rat lung albeit at low levels. M3 formation was clearly observed in recombinant rat CYP1A1, lung microsomes and lung tissue slices and was strongly inhibited by ketoconazole in the incubations. As CYP3A4 and CYP2C9 metabolites were only observed at trace levels, we concluded that the reduced M3 formation was due to CYP1A1 inhibition. 3. AFQ056 lung clearance (CLlung) as estimated from in vitro data was predicted to be negligible (<1% pulmonary blood flow). This was confirmed by in vivo experiments where intravenous and intra-arterial dosing to rats failed to show significant pulmonary extraction. 4. While rat lung may make a contribution to the formation of M3, it is unlikely to be the only organ involved in this process and further experiments are required to investigate the potential metabolic elimination routes for AFQ056.

Verification of a physiologically based pharmacokinetic model of ritonavir to estimate drug-drug interaction potential of CYP3A4 substrates.

Ritonavir is one of several ketoconazole alternatives used to evaluate strong CYP3A4 inhibition potential in clinical drug-drug interaction (DDI) studies. In this study, four physiologically based pharmacokinetic (PBPK) models of ritonavir as an in vivo time-dependent inhibitor of CYP3A4 were created and verified for oral doses of 20, 50, 100 and 200 mg using the fraction absorbed (Fa ) and oral clearance (CLoral ) values reported in the literature, because transporter and CYP enzyme reaction phenotyping data were not available. The models were used subsequently to predict and compare the magnitude of the AUC increase in nine reference DDI studies evaluating the effect of ritonavir at steady-state on midazolam (CYP3A4 substrate) exposure. Midazolam AUC and Cmax ratios were predicted within 2-fold of the respective observations in seven studies. Simulations of the hepatic and gut CYP3A4 abundance after multiple oral dosing of ritonavir indicated that a 3-day treatment with ritonavir 100 mg twice daily is sufficient to reach maximal CYP3A4 inhibition and subsequent systemic exposure increase of a CYP3A4 substrate, resulting in the reliable estimation of fm,CYP3A4 . The ritonavir model was submitted as part of the new drug application for Kisqali® (ribociclib) and accepted by health authorities.

Esterase phenotyping in human liver in vitro: specificity of carboxylesterase inhibitors.

1. Esterases may play a major role in the clearance of drugs with functional groups amenable to hydrolysis, particularly in the case of ester prodrugs. To understand the processes involved in the elimination of such drugs, it is necessary to determine the esterases involved. However, the tools currently available for this enzyme phenotyping are relatively scarce. 2. The work was aimed at summarizing the selectivity of esterase inhibitors for carboxylesterases 1 and 2 (CES1 and CES2) in the human liver to clarify their suitability for esterase phenotyping. Eserine, at around 10 µM, was found to be a highly specific CES2 inhibitor, whereas other esterase inhibitors turned out less selective. When used together with tacrine, which inhibits cholinesterases but not CES, and ethylenediaminetetraacetic acid (inhibitor of paraoxonases), the involvement of the hydrolyzing esterases in the hepatic clearance of a drug can be elucidated. 3. The second approach to esterase phenotyping is based on data from recombinant or isolated esterases, together with relative activity factors, which relate their activities to those of the same enzymes in subcellular fractions. 4. These two approaches will help to characterize the hydrolytic metabolism of drug candidates in a similar manner as practiced routinely for the oxidative metabolism by cytochrome P450 enzymes.

PBPK Modeling of Entrectinib and Its Active Metabolite to Derive Dose Adjustments in Pediatric Populations Co-Administered with CYP3A4 Inhibitors.

Physiologically based pharmacokinetic (PBPK) models of entrectinib and its equipotent metabolite, M5, were established in healthy adult subjects and extrapolated to pediatric patients to predict increases in steady-state systemic exposure on co-administration of strong and moderate CYP3A4 inhibitors (itraconazole at 5 mg/kg, erythromycin at 7.5-12.5 mg/kg and fluconazole at 3-12 mg/kg, respectively). Adult model establishment involved the optimization of fraction metabolized by CYP3A4 (0.92 for entrectinib and 0.98 for M5) using data from an itraconazole DDI study. This model captured well the exposure changes of entrectinib and M5 seen in adults co-administered with the strong CYP3A4 inducer rifampicin. In pediatrics, reasonable prediction of entrectinib and M5 pharmacokinetics in ≧2 year olds was achieved when using the default models for physiological development and enzyme ontogenies. However, a two to threefold misprediction of entrectinib and M5 exposures was seen in <2 year olds which may be due to missing mechanistic understanding of gut physiology and/or protein binding in very young children. Model predictions for ≧2 year olds showed that entrectinib AUC(0-t) was increased by approximately sevenfold and five to threefold by strong and high-moderate and low-moderate CYP3A4 inhibitors, respectively. Based on these victim DDI predictions, dose adjustments for entrectinib when given concomitantly with strong and moderate CYP3A4 inhibitors in pediatric subjects were recommended. These simulations informed the approved entrectinib label without the need for additional clinical pharmacology studies.

The Activity of Members of the UDP-Glucuronosyltransferase Subfamilies UGT1A and UGT2B is Impaired in Patients with Liver Cirrhosis.

BACKGROUND AND OBJECTIVE: The impact of liver cirrhosis on the activity of UDP-glucuronosyltransferases (UGTs) is currently not well characterized. We investigated the glucuronidation capacity and glucuronide accumulation in patients with liver cirrhosis. METHODS: We administered the Basel phenotyping cocktail (caffeine, efavirenz, flurbiprofen, omeprazole, metoprolol, midazolam) to patients with liver cirrhosis (n = 16 Child A, n = 15 Child B, n = 5 Child C) and n = 12 control subjects and obtained pharmacokinetic profiles of substrates and primary metabolites and their glucuronides. RESULTS: Caffeine and its metabolite paraxanthine were only slightly glucuronidated. The metabolic ratio (AUCglucuronide/AUCparent, MR) was not affected for caffeine but decreased by 60% for paraxanthine glucuronide formation in Child C patients. Efavirenz was not glucuronidated whereas 8-hydroxyefavirenz was efficiently glucuronidated. The MR of 8-hydroxyefavirenz-glucuronide formation increased three-fold in Child C patients and was negatively correlated with the glomerular filtration rate. Flurbiprofen and omeprazole were not glucuronidated. 4-Hydroxyflurbiprofen and 5-hydroxyomeprazole were both glucuronidated but the corresponding MRs for glucuronide formation were not affected by liver cirrhosis. Metoprolol, but not α-hydroxymetoprolol, was glucuronidated, and the MR for metoprolol-glucuronide formation dropped by 60% in Child C patients. Both midazolam and its metabolite 1'-hydroxymidazolam underwent glucuronidation, and the corresponding MRs for glucuronide formation dropped by approximately 80% in Child C patients. No relevant glucuronide accumulation occurred in patients with liver cirrhosis. CONCLUSIONS: Detailed analysis revealed that liver cirrhosis may affect the activity of UGTs of the UGT1A and UGT2B subfamilies according to liver function. Clinically significant glucuronide accumulation did not occur in the population investigated. CLINICAL TRIAL REGISTRATION: NCT03337945.

Industry Perspective on Therapeutic Peptide Drug-Drug Interaction Assessments During Drug Development: A European Federation of Pharmaceutical Industries and Associations White Paper.

Drug-drug interaction (DDI) assessments are well defined in health authority guidelines for small molecule drugs, and US Food and Drug Administration (FDA) draft guidance is now available for therapeutic proteins. However, there are currently no regulatory guidelines outlining DDI assessments for therapeutic peptides, which poses significant uncertainty and challenges during drug development for this heterogenous class of molecules. A cross-industry peptide DDI working group consisting of experts from 10 leading companies was formed under the sponsorship of the European Federation of Pharmaceutical Industries and Associations. We aimed to capture the range of DDI studies undertaken for peptide drugs by (i) anonymously surveying relevant companies involved in peptide drug development to better understand DDI study type/timing currently performed and (ii) compiling a database containing in vitro / clinical DDI data from submission packages for recently approved peptide drugs. Our analyses highlight significant gaps and uncertainty in the field. For example, the reported timing of in vitro peptide DDI studies, if performed, vary substantially across responding companies from early research to phase III. Nearly all in vitro cytochrome P450 / transporter inhibition studies reported in the survey were negative. For the few positive hits reported, no clinical follow-up studies were performed, questioning the clinical relevance of these findings. Furthermore, available submission packages reveal DDI likelihood is low for peptides >2 kDa, making it reasonable to adopt a risk-based approach during drug development for larger peptides. By benchmarking the landscape of peptide DDI activities across the industry, we set the stage for future discussions with health authorities on harmonizing peptide DDI approaches.

Dose Adjustment in Patients with Liver Cirrhosis - Comparison of Two Different Modeling Approaches.

Failure to perform adequate dose adjustment in patients with liver cirrhosis may be associated with increased toxicity. We compared the prediction of area under the curve (AUC) and clearance for the six compounds of the Basel phenotyping cocktail (caffeine, efavirenz, flurbiprofen, omeprazole, metoprolol, and midazolam) using a well-known physiology-based pharmacokinetic approach (physiologically-based pharmacokinetic [PBPK] approach, Simcyp) and a novel top-down method based on the systemic clearance in healthy volunteers adjusted for markers of liver and renal dysfunction ("top-down approach"). With few exceptions, plasma concentration-time curves were accurately predicted by the PBPK approach. In comparison to the measured AUC and clearance of these drugs in patients with liver cirrhosis and healthy controls, except for efavirenz, the estimates of both approaches were within two standard deviations of the mean for total and free drug concentrations. For both approaches, a correction factor for dose adjustment in patients with liver cirrhosis could be calculated for the drugs administered. AUCs calculated using the adjusted doses were comparable to the AUCs measured in control subjects, with slightly more accurate predictions generated by the PBPK approach. For drugs with a free fraction < 50%, predictions using free drug concentrations were more accurate than with total drug concentrations. In conclusion, both methods provided good qualitative predictions of the changes by liver cirrhosis in the pharmacokinetics of the six compounds investigated. The top-down approach is easier to implement but the PBPK approach predicted changes in drug exposure more accurately than the top-down approach and provided reliable estimates for plasma concentrations.