Impact of ignoring extraction ratio when predicting drug-drug interactions, fraction metabolized, and intestinal first-pass contribution

Incorporation and Performance Verification of Hepatic Portal Blood Flow Shunting in Minimal and Full PBPK Models of Liver Cirrhosis

Patho-physiological changes in liver cirrhosis create portacaval shunts that allow blood flow to bypass the hepatic portal vein into the systemic circulation affecting drug pharmacokinetics (PKs). The objectives of this work were to implement a physiologically-based pharmacokinetic (PBPK) framework describing shunted blood flows in virtual patients with differing degrees of liver cirrhosis; and to assess the minimal and full PBPK model's performance using drugs with intermediate to high hepatic extraction. Single dose concentration-time profiles and PK parameters for oral ibrutinib, midazolam, propranolol, and buspirone were simulated in healthy volunteers (HVs) and subjects with cirrhosis (Child-Pugh severity score (CP-A, CP-B, or CP-C)). Model performance was verified by comparing predicted to observed fold-changes in PK parameters between HVs and cirrhotic subjects. The verified model was used to simulate the PK changes for simvastatin in patients with cirrhosis. The predicted area under the curve ratios (AUCCirr :AUCHV ) for ibrutinib were 3.38, 6.87, and 11.46 using the minimal PBPK model with shunt and 1.61, 2.58, and 4.33 without the shunt, these compared with observed values of 4.33, 8.14, and 9.04, respectively. For ibrutinib, propranolol, and buspirone, including a shunt in the PBPK model improved the prediction of the AUCCirr :AUCHV and maximum plasma concentration ratios (CmaxCirr :CmaxHV ). For midazolam, an intermediate extraction drug, the differences were less clear. Simulated simvastatin dose adjustments in cirrhosis suggested that 20 mg in CP-A and 10 mg in CP-B could be used clinically. A mechanistic model-informed understanding of the anatomic and pathophysiology of cirrhosis will facilitate improved dose prediction and adjustment in this vulnerable population.

Quantitative Prediction of OATP-Mediated Disposition and Biliary Clearance Using Human Liver Chimeric Mice

Drug biliary clearance (CLbile) in vivo is among the most difficult pharmacokinetic parameters to predict accurately and quantitatively because biliary excretion is influenced by metabolic enzymes, transporters, and passive diffusion across hepatocyte membranes. The purpose of this study is to demonstrate the use of Hu-FRG mice [Fah-/-/Rag2-/-/Il2rg-/- (FRG) mice transplanted with human-derived hepatocytes] to quantitatively predict human organic anion transporting polypeptide (OATP)-mediated drug disposition and CLbile To predict OATP-mediated disposition, six OATP substrates (atorvastatin, fexofenadine, glibenclamide, pitavastatin, pravastatin, and rosuvastatin) were administered intravenously to Hu-FRG and Mu-FRG mice (FRG mice transplanted with mouse hepatocytes) with or without rifampicin as an OATP inhibitor. We calculated the hepatic intrinsic clearance (CLh,int) and the change of hepatic clearance (CLh) caused by rifampicin (CLh ratio). We compared the CLh,int of humans with that of Hu-FRG mice and the CLh ratio of humans with that of Hu-FRG and Mu-FRG mice. For predicting CLbile, 20 compounds (two cassette doses of 10 compounds) were administered intravenously to gallbladder-cannulated Hu-FRG and Mu-FRG mice. We evaluated the CLbile and investigated the correlation of human CLbile with that of Hu-FRG and Mu-FRG mice. We found good correlations between humans and Hu-FRG mice in CLh,int (100% within threefold) and CLh ratio (R2 = 0.94). Moreover, we observed a much better relationship between humans and Hu-FRG mice in CLbile (75% within threefold). Our results suggest that OATP-mediated disposition and CLbile can be predicted using Hu-FRG mice, making them a useful in vivo drug discovery tool for quantitatively predicting human liver disposition. SIGNIFICANCE STATEMENT: OATP-mediated disposition and biliary clearance of drugs are likely quantitatively predictable using Hu-FRG mice. The findings can enable the selection of better drug candidates and the development of more effective strategies for managing OATP-mediated DDIs in clinical studies.

Pharmacokinetic, Pharmacodynamic, and Drug-Interaction Profile of Remdesivir, a SARS-CoV-2 Replication Inhibitor

Remdesivir (RDV, Veklury®) is a once-daily, nucleoside ribonucleic acid polymerase inhibitor of severe acute respiratory syndrome coronavirus 2 replication. Remdesivir has been granted approvals in several countries for use in adults and children hospitalized with severe coronavirus disease 2019 (COVID-19). Inside the cell, remdesivir undergoes metabolic activation to form the intracellular active triphosphate metabolite, GS-443902 (detected in peripheral blood mononuclear cells), and ultimately, the renally eliminated plasma metabolite GS-441524. This review discusses the pre-clinical pharmacology of RDV, clinical pharmacokinetics, pharmacodynamics/concentration-QT analysis, rationale for dose selection for treatment of patients with COVID-19, and drug-drug interaction potential based on available in vitro and clinical data in healthy volunteers. Following single-dose intravenous administration over 2 h of an RDV solution formulation across the dose range of 3-225 mg in healthy participants, RDV and its metabolites (GS-704277and GS-441524) exhibit linear pharmacokinetics. Following multiple doses of RDV 150 mg once daily for 7 or 14 days, major metabolite GS-441524 accumulates approximately 1.9-fold in plasma. Based on pharmacokinetic bridging from animal data and available human data in healthy volunteers, the RDV clinical dose regimen of a 200-mg loading dose on day 1 followed by 100-mg maintenance doses for 4 or 9 days was selected for further evaluation of pharmacokinetics and safety. Results showed high intracellular concentrations of GS-443902 suggestive of efficient conversion from RDV into the triphosphate form, and further supporting this clinical dosing regimen for the treatment of COVID-19. Mathematical drug-drug interaction liability predictions, based on in vitro and phase I data, suggest RDV has low potential for drug-drug interactions, as the impact of inducers or inhibitors on RDV disposition is minimized by the parenteral route of administration and extensive extraction. Using physiologically based pharmacokinetic modeling, RDV is not predicted to be a clinically significant inhibitor of drug-metabolizing enzymes or transporters in patients infected with COVID-19 at therapeutic RDV doses.

Disease-drug and drug-drug interaction in COVID-19: Risk and assessment

COVID-19 is announced as a global pandemic in 2020. Its mortality and morbidity rate are rapidly increasing, with limited medications. The emergent outbreak of COVID-19 prompted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) keeps spreading. In this infection, a patient's immune response plays pivotal role in the pathogenesis. This inflammatory factor was shown by its mediators that, in severe cases, reach the cytokine at peaks. Hyperinflammatory state may sparks significant imbalances in transporters and drug metabolic machinery, and subsequent alteration of drug pharmacokinetics may result in unexpected therapeutic response. The present scenario has accounted for the requirement for therapeutic opportunities to relive and overcome this pandemic. Despite the diminishing developments of COVID-19, there is no drug still approved to have significant effects with no side effect on the treatment for COVID-19 patients. Based on the evidence, many antiviral and anti-inflammatory drugs have been authorized by the Food and Drug Administration (FDA) to treat the COVID-19 patients even though not knowing the possible drug-drug interactions (DDI). Remdesivir, favipiravir, and molnupiravir are deemed the most hopeful antiviral agents by improving infected patient’s health. Dexamethasone is the first known steroid medicine that saved the lives of seriously ill patients. Some oligopeptides and proteins have also been using. The current review summarizes medication updates to treat COVID-19 patients in an inflammatory state and their interaction with drug transporters and drug-metabolizing enzymes. It gives an opinion on the potential DDI that may permit the individualization of these drugs, thereby enhancing the safety and efficacy.

Time-dependent enzyme inactivation: Numerical analyses of in vitro data and prediction of drug-drug interactions

Cytochrome P450 (CYP) enzyme kinetics often do not conform to Michaelis-Menten assumptions, and time-dependent inactivation (TDI) of CYPs displays complexities such as multiple substrate binding, partial inactivation, quasi-irreversible inactivation, and sequential metabolism. Additionally, in vitro experimental issues such as lipid partitioning, enzyme concentrations, and inactivator depletion can further complicate the parameterization of in vitro TDI. The traditional replot method used to analyze in vitro TDI datasets is unable to handle complexities in CYP kinetics, and numerical approaches using ordinary differential equations of the kinetic schemes offer several advantages. Improvement in the parameterization of CYP in vitro kinetics has the potential to improve prediction of clinical drug-drug interactions (DDIs). This manuscript discusses various complexities in TDI kinetics of CYPs, and numerical approaches to model these complexities. The extrapolation of CYP in vitro TDI parameters to predict in vivo DDIs with static and dynamic modeling is discussed, along with a discussion on current gaps in knowledge and future directions to improve the prediction of DDI with in vitro data for CYP catalyzed drug metabolism.

In vitro inhibitory effects of kaempferitrin on human liver cytochrome P450 enzymes

Context: Kaempferitrinis (KF) is a bioactive flavonoid and possesses numerous pharmacological activities. However, whether KF affects the activity of human liver cytochrome P450 (CYP) enzymes remains unclear. Objective: This study investigates the effects of KF on eight major CYP isoforms in human liver microsomes (HLMs). Materials and methods: In vitro, HLMs were used to investigate the inhibitory effects of KF (100 μM) on the eight human liver CYP isoforms (i.e., 1A2, 3A4, 2A6, 2E1, 2D6, 2C9, 2C19, and 2C8), and corresponding probe substrates were used. Enzyme kinetic studies (0-50 μM of KF) were conducted to determine the inhibition mode of KF on CYP enzymes. Results: The results showed that KF inhibited the activity of CYP1A2, 3A4, and 2C9, with IC₅₀ values of 20.56, 13.87, and 14.62 μM, respectively, but that other CYP isoforms were not affected. Enzyme kinetic studies showed that KF was not only a noncompetitive inhibitor of CYP3A4, but also a competitive inhibitor of CYP1A2 and 2C9, with Ki values of 7.11, 10.24, and 7.58 μM, respectively. In addition, KF is a time-dependent inhibitor for CYP3A4 with K_I/K_inact value of 10.85/0.036 min/μM. Discussion: The in vitro studies of KF with CYP isoforms indicate that KF has the potential to cause pharmacokinetic drug interactions with other co-administered drugs metabolized by CYP1A2, 3A4, and 2C9. Conclusion: It is recommended that KF should not be used with other drugs metabolized by CYP1A2, 3A4, and 2C9. Further clinical studies are needed to evaluate the significance of this interaction.

Comparison of the inhibition potentials of icotinib and erlotinib against human UDP-glucuronosyltransferase 1A1

UDP-glucuronosyltransferase 1A1 (UGT1A1) plays a key role in detoxification of many potentially harmful compounds and drugs. UGT1A1 inhibition may bring risks of drug–drug interactions (DDIs), hyperbilirubinemia and drug-induced liver injury. This study aimed to investigate and compare the inhibitory effects of icotinib and erlotinib against UGT1A1, as well as to evaluate their potential DDI risks via UGT1A1 inhibition. The results demonstrated that both icotinib and erlotinib are UGT1A1 inhibitors, but the inhibitory effect of icotinib on UGT1A1 is weaker than that of erlotinib. The IC₅₀ values of icotinib and erlotinib against UGT1A1-mediated NCHN-O-glucuronidation in human liver microsomes (HLMs) were 5.15 and 0.68 μmol/L, respectively. Inhibition kinetic analyses demonstrated that both icotinib and erlotinib were non-competitive inhibitors against UGT1A1-mediated glucuronidation of NCHN in HLMs, with the K_i values of 8.55 and 1.23 μmol/L, respectively. Furthermore, their potential DDI risks via UGT1A1 inhibition were quantitatively predicted by the ratio of the areas under the concentration–time curve (AUC) of NCHN. These findings are helpful for the medicinal chemists to design and develop next generation tyrosine kinase inhibitors with improved safety, as well as to guide reasonable applications of icotinib and erlotinib in clinic, especially for avoiding their potential DDI risks via UGT1A1 inhibition.

Inhibition of human CYP3A4 and CYP3A5 enzymes by gomisin C and gomisin G, two lignan analogs derived from Schisandra chinensis

Gomisin C (GC) and gomisin G (GG) are two lignan analogs isolated from the Traditional Chinese Medicine Schisandra chinensis which possesses multiple pharmacological activities. However, the potential herb-drug interactions (HDI) between these lignans and other drugs through inhibiting human cytochrome P450 3A4 (CYP3A4) and CYP3A5 remains unclear. In the present study, the inhibitory action of GC and GG on CYP3A4 and CYP3A5 were investigated. The results demonstrated that both GC and GG strongly inhibited CYP3A-mediated midazolam 1'-hydroxylation, nifedipine oxidation and testosterone 6β-hydroxylation. Notably, the inhibitory intensity of GC towards CYP3A4 was stronger than CYP3A5 when using midazolam and nifedipine as substrates. While inhibition of GC towards CYP3A5 was weaker than CYP3A4 when using testosterone as substrate. In contrast, GG showed a stronger inhibitory activity on CYP3A5 than CYP3A4 without substrate-dependent behavior. In addition, docking simulations indicated that the π-π interaction between CYP3A4 and GC, and hydrogen-bond interaction between CYP3A5 and GG might result in their different inhibitory actions. Furthermore, the AUC of drugs metabolized by CYP3A was estimated to increase by 8%-321% and 2%-3190% in the presence of GC and GG, respectively. These findings strongly suggested that GC and GG showed high HDI potentials, and the position of methylenedioxy group determined their different inhibitory effect towards CYP3A4 and CYP3A5, which are of significance for the application of Schisandra chinensis-containing herbs.

Comparison of the inhibitory effects of tolcapone and entacapone against human UDP-glucuronosyltransferases

Tolcapone and entacapone are two potent catechol-O-methyltransferase (COMT) inhibitors with a similar skeleton and displaying similar pharmacological activities. However, entacapone is a very safe drug used widely in the treatment of Parkinson's disease, while tolcapone is only in limited use for Parkinson's patients and needs careful monitoring of hepatic functions due to hepatotoxicity. This study aims to investigate and compare the inhibitory effects of entacapone and tolcapone on human UDP-glucosyltransferases (UGTs), as well as to evaluate the potential risks from the view of drug-drug interactions (DDI). The results demonstrated that both tolcapone and entacapone exhibited inhibitory effects on UGT1A1, UGT1A7, UGT1A9 and UGT1A10. In contrast to entacapone, tolcapone exhibited more potent inhibitory effects on UGT1A1, UGT1A7, and UGT1A10, while their inhibitory potentials against UGT1A9 were comparable. It is noteworthy that the inhibition constants (Ki) of tolcapone and entacapone against bilirubin-O-glucuronidation in human liver microsomes (HLM) are determined as 0.68μM and 30.82μM, respectively, which means that the inhibition potency of tolcapone on UGT1A1 mediated bilirubin-O-glucuronidation in HLM is much higher than that of entacapone. Furthermore, the potential risks of tolcapone or entacapone via inhibition of human UGT1A1 were quantitatively predicted by the ratio of the areas under the plasma drug concentration-time curve (AUC). The results indicate that tolcapone may result in significant increase in AUC of bilirubin or the drugs primarily metabolized by UGT1A1, while entacapone is unlikely to cause a significant DDI through inhibition of UGT1A1.

Evaluation of drug-drug interactions for oncology therapies: in vitro-in vivo extrapolation model-based risk assessment

AIMS

Understanding drug-drug interactions (DDI) is a critical part of the drug development process as polypharmacy has become commonplace in many therapeutic areas including the cancer patient population. The objectives of this study were to investigate cytochrome P450 (CYP)-mediated DDI profiles available for therapies used in the oncology setting and evaluate how models based on in vitro-in vivo extrapolation performed in predicting CYP-mediated DDI risk.

METHODS

A dataset of 125 oncology therapies was collated using drug label and approval history information, incorporating in vitro and clinical PK data. The predictive accuracy of the basic and net effect mechanistic static models was assessed using this oncology drug dataset, for both victim and perpetrator potential of CYP3A-mediated DDI.

RESULTS

The incidence of CYP3A-mediated interaction potential was 47%, 22% and 11% for substrates, inhibitors and inducers, respectively. The basic models for precipitants gave conservative predictions with no false negatives, whilst the mechanistic static models provided reasonable quantitative predictions (2.3-3-fold error). Further analysis revealed that incorporating DDI at the level of the intestine was in most cases over-predicting interaction magnitude due to overestimates of the rate and extent of oral absorption of the precipitant. Quantifying victim DDI potential was also demonstrated using fmCYP3A estimates from ketoconazole clinical DDI studies to predict the magnitude of interaction on co-administration with the CYP3A inducer, rifampicin (1.6-3.3 fold error).

CONCLUSIONS

This work illustrates the utility and limitations of current DDI risk assessment approaches applied to a range of contemporary anti-cancer agents, and discusses the implications for therapeutic combination strategies.

Lack of indinavir effects on methadone disposition despite inhibition of hepatic and intestinal cytochrome P4503A (CYP3A)

BACKGROUND

Methadone disposition and pharmacodynamics are highly susceptible to interactions with antiretroviral drugs. Methadone clearance and drug interactions have been attributed to cytochrome P4503A4 (CYP3A4), but actual mechanisms are unknown. Drug interactions can be clinically and mechanistically informative. This investigation assessed effects of the protease inhibitor indinavir on methadone pharmacokinetics and pharmacodynamics, hepatic and intestinal CYP3A4/5 activity (using alfentanil), and intestinal transporter activity (using fexofenadine).

METHODS

Twelve healthy volunteers underwent a sequential crossover. On three consecutive days they received oral alfentanil plus fexofenadine, intravenous alfentanil, and intravenous plus oral (deuterium-labeled) methadone. This was repeated after 2 weeks of indinavir. Plasma and urine analytes were measured by mass spectrometry. Opioid effects were measured by miosis.

RESULTS

Indinavir significantly inhibited hepatic and first-pass CYP3A activity. Intravenous alfentanil systemic clearance and hepatic extraction were reduced to 40-50% of control, apparent oral clearance to 30% of control, and intestinal extraction decreased by half, indicating 50% and 70% inhibition of hepatic and first-pass CYP3A activity. Indinavir increased fexofenadine area under the plasma concentration-time curve 3-fold, suggesting significant P-glycoprotein inhibition. Indinavir had no significant effects on methadone plasma concentrations, methadone N-demethylation, systemic or apparent oral clearance, renal clearance, hepatic extraction or clearance, or bioavailability. Methadone plasma concentration-effect relationships were unaffected by indinavir.

CONCLUSIONS

Despite significant inhibition of hepatic and intestinal CYP3A activity, indinavir had no effect on methadone N-demethylation and clearance, suggesting little or no role for CYP3A in clinical disposition of single-dose methadone. Inhibition of gastrointestinal transporter activity had no influence of methadone bioavailability.

Predictive utility of in vitro rifampin induction data generated in fresh and cryopreserved human hepatocytes, Fa2N-4, and HepaRG cells

Rifampin is a potent inducer of CYP3A4 in vitro and precipitates numerous drug-drug interactions (DDIs) when coadministered with CYP3A4 substrates. In the current study, we have critically assessed reported rifampin in vitro CYP3A4 induction data in Fa2N-4, HepaRG, and cryopreserved or primary human hepatocytes, using either CYP3A4 mRNA or probe substrate metabolism as induction endpoints. An in vivo data base of intravenously administered victim drugs (assuming hepatic induction only) was collated (n = 18) to assess the predictive utility of these in vitro systems and to optimize rifampin in vivo E(max). In addition, the effect of substrate hepatic extraction ratio on prediction accuracy was investigated using prediction boundaries proposed recently (Drug Metab Dispos 39:170-173). Incorporation of hepatic extraction ratio in the prediction model resulted in accurate prediction of 89% of intravenous induction DDIs (n = 18), regardless of the in vitro system or induction endpoint (mRNA or CYP3A4 activity). Effects of in vitro parameters from different cellular systems, and optimized in vivo E(max), on the prediction of 21 oral DDIs were assessed. Use of mRNA data resulted in pronounced overprediction across all systems, with 86 to 100% of DDIs outside the acceptable prediction limits; in contrast, CYP3A4 activity predicted up to 62% of the oral DDIs within limits. Although prediction accuracy of oral DDIs was improved when using intravenous optimized rifampin E(max), >35% of DDIs were incorrectly assigned, suggesting potential differential E(max) between intestine and liver. Implications of the findings and recommendations for prediction of rifampin DDIs are discussed.

A quantitative framework and strategies for management and evaluation of metabolic drug-drug interactions in oncology drug development: new molecular entities as object drugs

This article outlines general strategies for the management and evaluation of pharmacokinetic drug-drug interactions (DDIs) resulting from perturbation of clearance of investigational anticancer drug candidates by concomitantly administered agents in a drug development setting, with a focus on drug candidates that cannot be evaluated in first-in-human studies in healthy subjects. A risk level classification is proposed, based on quantitative integration of knowledge derived from preclinical drug-metabolism studies evaluating the projected percentage contribution [f(i)(%)] of individual molecular determinants (e.g. cytochrome P450 isoenzymes) to the overall human clearance of the investigational agent. The following classification is proposed with respect to susceptibility to DDIs with metabolic inhibitors: a projected maximum DDI expected to result in a ≤1.33-fold increase in exposure, representing a low level of risk; a projected maximum DDI expected to result in a >1.33-fold but <2-fold increase in exposure, representing a moderate level of risk; and a projected maximum DDI expected to result in a ≥2-fold increase in exposure, representing a potentially high level of risk. For DDIs with metabolic inducers, the following operational classification is proposed, based on the sum of the percentage contributions of enzymes that are inducible via a common mechanism to the overall clearance of the investigational drug: <<25%, representing a low level of risk; <50%, representing a moderate level of risk; and ≥50%, representing a potentially high level of risk. To ensure patient safety and to minimize bias in determination of the recommended phase II dose (RP2D), it is recommended that strong and moderate inhibitors and inducers of the major contributing enzyme are excluded in phase I dose-escalation studies of high-risk compounds, whereas exclusion of strong inhibitors and inducers of the contributing enzyme(s) is recommended as being sufficient for moderate-risk compounds. For drugs that will be investigated in diseases such as glioblastoma, where there may be relatively frequent use of enzyme-inducing antiepileptic agents (EIAEDs), a separate dose-escalation study in this subpopulation is recommended to define the RP2D. For compounds in the high-risk category, if genetic deficiencies in the activity of the major drug-metabolizing enzyme are known, it is recommended that poor metabolizers be studied separately to define the RP2D for this subpopulation. Whereas concomitant medication exclusion criteria that are utilized in the phase I dose-escalation studies will probably also need to be maintained for high-risk compounds in phase II studies unless the results of a clinical DDI study indicate the absence of a clinically relevant interaction, these exclusion criteria can potentially be relaxed beyond phase I for moderate-risk compounds, if supported by the nature of clinical toxicities and the understanding of the therapeutic index in phase I. Adequately designed clinical DDI studies will not only inform potential relaxation of concomitant medication exclusion criteria in later-phase studies but, importantly, will also inform the development of pharmacokinetically derived dose-modification guidelines for use in clinical practice when coupled with adequate safety monitoring, as illustrated in the prescribing guidance for many recently approved oncology therapeutics.

Complex drug interactions of HIV protease inhibitors 1: inactivation, induction, and inhibition of cytochrome P450 3A by ritonavir or nelfinavir

Conflicting drug-drug interaction (DDI) studies with the HIV protease inhibitors (PIs) suggest net induction or inhibition of intestinal or hepatic CYP3A. As part of a larger DDI study in healthy volunteers, we determined the effect of extended administration of two PIs, ritonavir (RTV) or nelfinavir (NFV), or the induction-positive control rifampin on intestinal and hepatic CYP3A activity as measured by midazolam (MDZ) disposition after a 14-day treatment with the PI in either staggered (MDZ ∼12 h after PI) or simultaneous (MDZ and PI coadministered) manner. Oral and intravenous MDZ areas under the plasma concentration-time curves were significantly increased by RTV or NFV and were decreased by rifampin. Irrespective of method of administration, RTV decreased net intestinal and hepatic CYP3A activity, whereas NFV decreased hepatic but not intestinal CYP3A activity. The magnitude of these DDIs was more accurately predicted using PI CYP3A inactivation parameters generated in sandwich-cultured human hepatocytes rather than human liver microsomes.