Database analyses for the prediction of in vivo drug-drug interactions from in vitro data

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.

In vitro inhibitory effects of selumetinib on activity of human UDP-glucuronosyltransferases and prediction of in vivo drug-drug interactions

Selumetinib is an oral, effective, and selective tyrosine kinase inhibitor targeting mitogen-activated protein kinase 1 and 2 (MEK1/2), which is clinically active in multiple tumor types, such as neurofibromatosis type 1 (NF1), melanoma, gliomas and non-small cell lung cancer (NSCLC). The purpose of this article was to assess the effects of selumetinib on the activities of twelve human UDP-glucosyltransferases (UGTs) including UGT1A1, 1A3, 1A4, 1A6, 1A7, 1A8, 1A9, 1A10, 2B4, 2B7, 2B15, and 2B17, and its potential for inducing clinical drug-drug interactions (DDIs). The results demonstrated that selumetinib potently inhibited the activity of UGT2B7 through the mechanism of mixed inhibition with the inhibition constant value of 5.79 ± 0.65 μM. Furthermore, the plasma concentration of UGT2B7 substrate as the co-administered drug was predicted to be increased by at least 84 % when patients took selumetinib 75 mg twice daily, suggesting a high potential to induce clinical DDIs. Selumetinib exhibited weak inhibitory effects on other human UGTs and was unlikely to trigger off UGTs-mediated DDIs except for UGT2B7. Therefore, the combination of selumetinib with the substrate drug of UGT2B7 requires additional attention to avoid adverse events in clinical treatment.

Clinical Trial Data-Driven Risk Assessment of Drug-Drug Interactions: A Rapid and Accurate Decision-Making Tool

BACKGROUND

In clinical practice, the vast array of potential drug combinations necessitates swift and accurate assessments of pharmacokinetic drug-drug interactions (DDIs), along with recommendations for adjustments. Current methodologies for clinical DDI evaluations primarily rely on basic extrapolations from clinical trial data. However, these methods are limited in accuracy owing to their lack of a comprehensive consideration of various critical factors, including the inhibitory potency, dosage, and type of the inhibitor, as well as the metabolic fraction and intestinal availability of the substrate.

OBJECTIVE

This study aims to propose an efficient and accurate clinical pharmacokinetic-mediated DDI assessment tool, which comprehensively considers the effects of inhibitory potency and dosage of inhibitors, intestinal availability and fraction metabolized of substrates on DDI outcomes.

METHODS

This study focuses on DDIs caused by cytochrome P450 3A4 enzyme inhibition, utilizing extensive clinical trial data to establish a methodology to calculate the metabolic fraction and intestinal availability for substrates, as well as the concentration and inhibitory potency for inhibitors ( K i ork inact / K I ). These parameters were then used to predict the outcomes of DDIs involving 33 substrates and 20 inhibitors. We also defined the risk index for substrates and the potency index for inhibitors to establish a clinical DDI risk scale. The training set for parameter calculation consisted of 73 clinical trials. The validation set comprised 89 clinical DDI trials involving 53 drugs. which was used to evaluate the reliability of in vivo values of K i andk inact / K I , the accuracy of DDI predictions, and the false-negative rate of risk scale.

RESULTS

First, the reliability of the in vivo K i andk inact / K I values calculated in this study was assessed using a basic static model. Compared with values obtained from other methods, this study values showed a lower geometric mean fold error and root mean square error. Additionally, incorporating these values into the physiologically based pharmacokinetic-DDI model facilitated a good fitting of the C-t curves when the substrate's metabolic enzymes are inhibited. Second, area under the curve ratio predictions of studied drugs were within a 1.5 × margin of error in 81% of cases compared with clinical observations in the validation set. Last, the clinical DDI risk scale developed in this study predicted the actual risks in the validation set with only a 5.6% incidence of serious false negatives.

CONCLUSIONS

This study offers a rapid and accurate approach for assessing the risk of pharmacokinetic-mediated DDIs in clinical practice, providing a foundation for rational combination drug use and dosage adjustments.

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.

Exploring the impact of CYP2D6 and UGT2B7 gene-drug interactions, and CYP-mediated DDI on oxycodone and oxymorphone pharmacokinetics using physiologically-based pharmacokinetic modeling and simulation

Oxycodone is one of the most commonly used opioids to treat moderate to severe pain. It is metabolized mainly by CYP3A4 and CYP2D6, while only a small fraction of the dose is excreted unchanged into the urine. Oxymorphone, the metabolite primarily formed by CYP2D6, has a 40- to 60-fold higher mu-opioid receptor affinity than the parent compound. While CYP2D6-mediated gene-drug-interactions (GDIs) and drug-drug interactions (DDIs) are well-studied, they only account for a portion of the variability in oxycodone and oxymorphone exposure. The combined impact of CYP2D6-mediated GDIs and DDIs, CYP3A4-mediated DDIs, and UGT2B7 GDIs is not fully understood yet and hard to study in head-to-head clinical trials given the relatively large number of scenarios. Instead, we propose the use of a physiologically-based pharmacokinetic model that integrates available information on oxycodone's metabolism to characterize and predict the impact of DDIs and GDIs on the exposure of oxycodone and its major, pharmacologically-active metabolite oxymorphone. To this end, we first developed and verified a PBPK model for oxycodone and its metabolites using published clinical data. The verified model was then applied to determine the dose-exposure relationship of oxycodone and oxymorphone stratified by CYP2D6 and UGT2B7 phenotypes respectively, and administered perpetrators of CYP-based drug interactions. Our simulations demonstrate that the combination of CYP2D6 UM and a UGT2B7Y (268) mutation may lead to a 2.3-fold increase in oxymorphone exposure compared to individuals who are phenotyped as CYP2D6 NM / UGT2B7 NM. The extent of oxymorphone exposure increases up to 3.2-fold in individuals concurrently taking CYP3A4 inhibitors, such as ketoconazole. Inhibition of the CYP3A4 pathway results in a relative increase in the partial metabolic clearance of oxycodone to oxymorphone. Oxymorphone is impacted to a higher extent by GDIs and DDIs than oxycodone. We predict oxymorphone exposure to be highest in CYP2D6 UMs/UGT2B7 PMs in the presence of ketoconazole (strong CYP3A4 index inhibitor) and lowest in CYP2D6 PMs/UGT2B7 NMs in the presence of rifampicin (strong CYP3A4 index inducer) covering a 55-fold exposure range.

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.

Potential risk of drug-drug interactions of ponatinib via inhibition against human UDP-glucuronosyltransferases

Ponatinib is an efficient oral tyrosine kinase inhibitor (TKI) for T315I-positive Ph + ALL and T315I-positive chronic myeloid leukemia (CML) or BCR-ABL when no other TKIs can be prescribed. In this research, we evaluated the inhibitory effects of ponatinib on human recombinant UDP-glucuronosyltransferases (UGTs) and predicted the magnitude of potential drug-drug interaction (DDI) risk of co-treatment with ponatinib and UGTs substrates by using in vitro-in vivo extrapolation (IVIVE) method. Our study presented that ponatinib showed a broad-spectrum inhibition against UGTs. Particularly, ponatinib exhibited potent inhibitory effects towards UGT1A7, UGT1A1, and UGT1A9 with IC50 values of 0.37, 0.41, and 0.89 μM, respectively, which might lead to clinically significant DDI.

Fluorescence-Based High-Throughput Assays for Investigating Cytochrome P450 Enzyme-Mediated Drug-Drug Interactions

The cytochrome P450 enzymes (CYPs), a group of heme-containing enzymes, catalyze oxidative metabolism of a wide range of drugs and xenobiotics, as well as different endogenous molecules. Strong inhibition of human CYPs is the most common cause of clinically associated pharmacokinetic drug-drug/herb-drug interactions (DDIs/HDIs), which may result in serious adverse drug reactions, even toxicity. Accurate and rapid assessing of the inhibition potentials on CYP activities for therapeutic agents is crucial for the prediction of clinically relevant DDIs/HDIs. Over the past few decades, significant efforts have been invested into developing optical substrates for the human CYPs, generating a variety of powerful tools for high-throughput assays to detect CYP activities in biologic specimens and for screening of CYP inhibitors. This minireview focuses on recent advances in optical substrates developments for human CYPs, as well as their applications in screening CYP inhibitors and DDIs/HDIs studies. The examples for rational design and optimization of highly specific optical substrates for the target CYP enzyme, as well as applications in investigating CYP-mediated DDIs, are illustrated. Finally, the challenges and future perspectives in this field are proposed. Collectively, this review summarizes the reported optical-based biochemical assays for highly efficient CYP activities detection, which strongly facilitated the discovery of CYP inhibitors and the investigations on CYP-mediated DDIs. SIGNIFICANCE STATEMENT: Optical substrates for cytochrome P450 enzymes (CYPs) have emerged as powerful tools for the construction of high-throughput assays for screening of CYP inhibitors. This mini-review covers the advances and challenges in the development of highly specific optical substrates for sensing human CYP isoenzymes, as well as their applications in constructing fluorescence-based high-throughput assays for investigating CYP-mediated drug-drug interactions.

Predicting the Effect of Renal Function on Systemic Clearance: Is a simple scaling method sufficient?

PURPOSE

To employ a simple scaling method to predict systemic or oral clearance for drugs that are primarily renally cleared knowing the fraction eliminated in urine (f_e) and a patient's renal function relative to healthy controls (S_GFR).

METHODS

Observations evaluating drug clearance as a function of creatinine clearance for renally cleared drugs (f_e >0.3) were obtained from literature sources. The analysis comprised of 82 unique drugs from 124 studies including 31 drugs with replicate studies. A simple scaler for renal function was employed and compared to the linear regression of available data. For drugs in which replicate studies were available, the ability of the linear regression (Cl vs Cl_CR) from one pharmacokinetic study was used to predict observations from an assigned replicate and compared to the scaling approach.

RESULTS

For patients categorized as severe kidney disease (Cl_CR fixed at 20 ml/min), the scalar tended to over predict some observations, but 92% of the predictions were within 50 - 200% of the observed data. For drugs with available replicates, the scalar was as good or better in predicting the influence of Cl_CR on systemic clearance from a separate study when comparing against the linear regression approach.

CONCLUSION

A scaling approach to account for alterations in drug clearance appears to have its advantages and represents a simple and generalizable method for guiding dose adjustments in patients with decreased renal function for drugs that are renally cleared (f_e >0.3). In addition to its use in clinical practice, validation of this approach may have implications in facilitating more efficient drug development processes for designing dose-adjusted pharmacokinetic studies in patients with renal disease.

Inhibition of human sulfotransferases (SULTs) by per- and polyfluoroalkyl substances (PFASs) and structure-activity relationship

Per- and polyfluoroalkyl substances (PFASs) are a family of highly fluorinated aliphatic substances widely used in industrial and commercial applications. This study aims to determine the inhibition of PFASs towards sulfotransferases (SULTs) activity, and trying to explain the toxicity mechanism of PFASs. In vitro recombinant SULTs-catalyzed sulfation of p-nitrophenol (PNP) was utilized as a probe reaction. The incubation system was consisted of PFASs, SULTs, PNP, 3'-phosphoadenosine-5'-phosphosulfate, MgCl₂ and Tris-HCl buffer. Ultra-performance liquid chromatography was employed for analysis of the metabolites. All tested PFASs showed inhibition towards SULTs. The longer the carbon chain length of the PFASs terminated with -COOH, the higher is its capability of inhibiting SULT1A3. PFASs with -SO₃H had a relatively higher ability to inhibit SULT1A3 activity than those with -COOH, -I and -OH. The inhibition kinetic parameter was 2.16 and 1.42 μM for PFOS-SULT1A1, PFTA-SULT1B1. In vitro in vivo extrapolation showed that the concentration of PFOS and PFTA in human matrices might be higher than the threshold for inducing inhibition of SULTs. Therefore, PFASs could interfere with the metabolic pathways catalyzed by SULTs in vivo. All these results will help to understand the toxicity of PFASs from the perspective of metabolism.

General Framework to Quantitatively Predict Pharmacokinetic Induction Drug-Drug Interactions Using In Vitro Data

INTRODUCTION

Metabolic inducers can expose people with polypharmacy to adverse health outcomes. A limited fraction of potential drug-drug interactions (DDIs) have been or can ethically be studied in clinical trials, leaving the vast majority unexplored. In the present study, an algorithm has been developed to predict the induction DDI magnitude, integrating data related to drug-metabolising enzymes.

METHODS

The area under the curve ratio (AUC_ratio) resulting from the DDI with a victim drug in the presence and absence of an inducer (rifampicin, rifabutin, efavirenz, or carbamazepine) was predicted from various in vitro parameters and then correlated with the clinical AUC_ratio (N = 319). In vitro data including fraction unbound in plasma, substrate specificity and induction potential for cytochrome P450s, phase II enzymes and uptake, and efflux transporters were integrated. To represent the interaction potential, the in vitro metabolic metric (IVMM) was generated by combining the fraction of substrate metabolised by each hepatic enzyme of interest with the corresponding in vitro fold increase in enzyme activity (E) value for the inducer.

RESULTS

Two independent variables were deemed significant and included in the algorithm: IVMM and fraction unbound in plasma. The observed and predicted magnitudes of the DDIs were categorised accordingly: no induction, mild, moderate, and strong induction. DDIs were assumed to be well classified if the predictions were in the same category as the observations, or if the ratio between these two was < 1.5-fold. This algorithm correctly classified 70.5% of the DDIs.

CONCLUSION

This research presents a rapid screening tool to identify the magnitude of potential DDIs utilising in vitro data which can be highly advantageous in early drug development.

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.

Prediction of herb-drug interactions involving consumption of furanocoumarin-mixtures and cytochrome P450 1A2-mediated caffeine metabolism inhibition in humans

Herb-drug interactions (HDI) has become important due to the increasing popularity of natural health product consumption worldwide. HDI is difficult to predict as botanical drugs usually contain complex phytochemical-mixtures, which interact with drug metabolism. Currently, there is no specific pharmacological tool to predict HDI since almost all in vitro-in vivo-extrapolation (IVIVE) Drug-Drug Interaction (DDI) models deal with one inhibitor-drug and one victim-drug. The objectives were to modify-two IVIVE models for the prediction of in vivo interaction between caffeine and furanocoumarin-containing herbs, and to confirm model predictions by comparing the DDI predictive results with actual human data. The models were modified to predict in vivo herb-caffeine interaction using the same set of inhibition constants but different integrated dose/concentration of furanocoumarin mixtures in the liver. Different hepatic inlet inhibitor concentration ([I]_H) surrogates were used for each furanocoumarin. In the first (hybrid) model, the [I]_H was predicted using the concentration-addition model for chemical-mixtures. In the second model, the [I]_H was calculated by adding individual furanocoumarins together. Once [I]_H values were determined, the models predicted an area-under-curve-ratio (AUCR) value of each interaction. The results indicate that both models were able to predict the experimental AUCR of herbal products reasonably well. The DDI model approaches described in this study may be applicable to health supplements and functional foods also.

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.

Do AutoML-Based QSAR Models Fulfill OECD Principles for Regulatory Assessment? A 5-HT1A Receptor Case

The drug discovery and development process requires a lot of time, financial, and workforce resources. Any reduction in these burdens might benefit all stakeholders in the healthcare domain, including patients, government, and companies. One of the critical stages in drug discovery is a selection of molecular structures with a strong affinity to a particular molecular target. The possible solution is the development of predictive models and their application in the screening process, but due to the complexity of the problem, simple and statistical models might not be sufficient for practical application. The manuscript presents the best-in-class predictive model for the serotonin 1A receptor affinity and its validation according to the Organization for Economic Co-operation and Development guidelines for regulatory purposes. The model was developed based on a database with close to 9500 molecules by using an automatic machine learning tool (AutoML). The model selection was conducted based on the Akaike information criterion value and 10-fold cross-validation routine, and later good predictive ability was confirmed with an additional external validation dataset with over 700 molecules. Moreover, the multi-start technique was applied to test if an automatic model development procedure results in reliable results.

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.

Case report: Medical cannabis-warfarin drug-drug interaction

AIM

A case of an 85-year-old patient with concurrent use of warfarin and medical cannabis containing delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD) is described. Warfarin continues to be a cornerstone of anticoagulation treatment despite the recent addition of FDA-approved anticoagulant agents. It is well known that warfarin has numerous drug interactions; however, much remains unknown about its interaction with THC and CBD. A literature review was conducted to identify documented cases of possible interactions between cannabis and warfarin. The case reports we identified noted that cannabis may potentially increase warfarin's effect. Therefore, we aimed to determine why an effect was not seen on our patient's warfarin dose despite daily use of medical cannabis.

CASE

This case report describes an 85-year-old patient who despite starting an oromucosal medical cannabis regimen of THC and CBD (which provided 0.3 mg of THC and 5.3 mg CBD once daily and an additional 0.625 mg of THC and 0.625 mg CBD once daily as needed) had minimal INR fluctuations from October 2018 to September 2019.

CONCLUSION

Despite the introduction and use of medical cannabis therapy, with both THC and CBD components, an elderly patient with concurrent warfarin use did not see major INR fluctuations, in contrast to published literature. The potential for warfarin and THC/CBD interactions may be dependent on route of administration and dose of the cannabis product.

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.

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.

Comparison of the drug-drug interactions potential of ibrutinib and acalabrutinib via inhibition of UDP-glucuronosyltransferase

Ibrutinib and acalabrutinib are two Bruton's tyrosine kinase (BTK) inhibitors which have gained Food and Drug Administration (FDA) approval for the treatment of various B cell malignancies. Herein, we investigated the effects of the two drugs on UDP-glucuronosyltransferase (UGT) activities to evaluate their potential risk for drug-drug interactions (DDIs) via UGT inhibition. Our data indicated that ibrutinib exerted broad inhibition on most of UGTs, including a potent competitive inhibition against UGT1A1 with a K_i value of 0.90 ± 0.03 μM, a noncompetitive inhibition against UGT1A3 and UGT1A7 with K_i values of 0.88 ± 0.03 μM and 2.52 ± 0.23 μM, respectively, while acalabrutinib only exhibited weak UGT inhibition towards all tested UGT isoforms. DDI risk prediction suggested that the inhibition against UGT1A1 and UGT1A3 by ibrutinib might bring a potential DDIs risk, while acalabrutinib was unlikely to trigger clinically significant UGT-mediated DDIs due to its weak effects. Our study raises an alarm bell about potential DDI risk associated with ibrutinib, however, the extrapolation from in vitro data to in vivo drug interactions should be taken with caution, and additional systemic study is needed.

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

Belinostat is a pan-histone deacetylase (HDAC) inhibitor which recently approved for the treatment of relapsed/refractory Peripheral T-cell lymphomas (PTCL). To assess drug-drug interactions (DDIs) potential of belinostat via inhibition of UDP-glucuronosyltransferases (UGTs), the effects of belinostat on UGTs activities were investigated using the non-selective probe substrate 4-methylumbelliferone (4-MU) and trifluoperazine (TFP) by UPLC-MS/MS. Belinostat exhibited a wide range of inhibition against UGTs activities, particularly a potent non-competitive inhibition against UGT1A3, and weak inhibition against UGT1A1, 1A7, 1A8, 2B4 and 2B7. Further, in vitro-in vivo extrapolation (IVIVE) approaches were used to predict the risk of DDI arising from inhibition of UGTs. Our data indicate that the intravenous infusion of belinostat at clinical available dose can contribute a significant increase to the AUC of co-administrated drugs primarily cleared by UGT1A3 or UGT1A1, which will result in potential DDIs. In contrast, oral administrated belinostat is unlikely to cause significant DDIs through inhibition of glucuronidation.

Comparative Assessment of Extrapolation Methods Based on the Conventional Free Drug Hypothesis and Plasma Protein-Mediated Hepatic Uptake Theory for the Hepatic Clearance Predictions of Two Drugs Extensively Bound to Both the Albumin And Alpha-1-Acid Glycoprotein

Bteich and coworkers recently demonstrated in a companion manuscript (J Pharm Sci 109: https://doi.org/10.1016/j.xphs.2020.07.003) that a protein-mediated hepatic uptake have occurred in an isolated perfused rat liver (IPRL) model for two drugs (Perampanel; PER and Fluoxetine; FLU) that bind extensively to the albumin (ALB) and alpha-1-acid glycoprotein (AGP). However, to our knowledge, there is no quantitative model available to predict the impact of a plasma protein-mediated hepatic uptake on the extent of hepatic clearance (CLh) for a drug binding extensively to these two proteins. Therefore, the main objective was to predict the corresponding CLh, which is an extension of the companion manuscript. The method consisted of extrapolating the intrinsic clearance from the unbound fraction measured in the perfusate or the unbound fraction extrapolated to the surface of the hepatocyte membrane by adapting an existing model of protein-mediated hepatic uptake (i.e., the fu_p-adjusted model) to include a binding ratio between the ALB and AGP. This new approach showed a relevant improvement compared to the free drug hypothesis particularly for FLU that showed the highest degree of ALB-mediated uptake. Overall, this study is a first step towards the development of predictive methods of CLh by considering the binding to ALB and AGP.

Predicting the Potential for Cannabinoids to Precipitate Pharmacokinetic Drug Interactions via Reversible Inhibition or Inactivation of Major Cytochromes P450

Cannabis is used for both recreational and medicinal purposes. The most abundant constituents are the cannabinoids - cannabidiol (CBD, nonpsychoactive) and (-)-trans-Δ⁹-tetrahydrocannabinol (THC, psychoactive). Both have been reported to reversibly inhibit or inactivate cytochrome P450 (CYPs) enzymes. However, the low aqueous solubility, microsomal protein binding, and nonspecific binding to labware were not considered, potentially leading to an underestimation of CYPs inhibition potency. Therefore, the binding-corrected reversible (IC_50,u) and irreversible (K _I,u ) inhibition potency of each cannabinoid toward major CYPs were determined. The fraction unbound of CBD and THC in the incubation mixture was 0.12 ± 0.04 and 0.05 ± 0.02, respectively. The IC_50,u for CBD toward CYP1A2, 2C9, 2C19, 2D6, and 3A was 0.45 ± 0.17, 0.17 ± 0.03, 0.30 ± 0.06, 0.95 ± 0.50, and 0.38 ± 0.11 µM, respectively; the IC_50,u for THC was 0.06 ± 0.02, 0.012 ± 0.001, 0.57 ± 0.22, 1.28 ± 0.25, and 1.30 ± 0.34 µM, respectively. Only CBD showed time-dependent inactivation (TDI) of CYP1A2, 2C19, and CYP3A, with inactivation efficiencies (k _inact/K _I,u) of 0.70 ± 0.34, 0.11 ± 0.06, and 0.14 ± 0.04 minutes^-1 µM^-1, respectively. A combined (reversible inhibition and TDI) mechanistic static model populated with these data predicted a moderate to strong pharmacokinetic interaction risk between orally administered CBD and drugs extensively metabolized by CYP1A2/2C9/2C19/2D6/3A and between orally administered THC and drugs extensively metabolized by CYP1A2/2C9/3A. These predictions will be extended to a dynamic model using physiologically based pharmacokinetic modeling and simulation and verified with a well-designed clinical cannabinoid-drug interaction study. SIGNIFICANCE STATEMENT: This study is the first to consider the impact of limited aqueous solubility, nonspecific binding to labware, or extensive binding to incubation protein shown by cannabidiol (CBD) and delta-9-tetrahydrocannabinol (THC) on their true cytochrome P450 inhibitory potency. A combined mechanistic static model predicted a moderate to strong pharmacokinetic interaction risk between orally administered CBD and drugs extensively metabolized by CYP1A2, 2C9, 2C19, 2D6, or 3A and between orally administered THC and drugs extensively metabolized by CYP1A2, 2C9, or 3A.

Assessment of Inhibition of Bovine Hepatic Cytochrome P450 by 43 Commercial Bovine Medicines Using a Combination of In Vitro Assays and Pharmacokinetic Data from the Literature

BACKGROUND

There has been a lack of information about the inhibition of bovine medicines on bovine hepatic CYP450 at their commercial doses and dosing routes.

OBJECTIVE

The aim of this work was to assess the inhibition of 43 bovine medicines on bovine hepatic CYP450 using a combination of in vitro assay and Cmax values from pharmacokinetic studies with their commercial doses and dosing routes in the literature.

METHODS

Those drugs were first evaluated through a single point inhibitory assay at 3 μM in bovine liver microsomes for six specific CYP450 metabolisms, phenacetin o-deethylation, coumarin 7- hydroxylation, tolbutamide 4-hydroxylation, bufuralol 1-hydroxylation, chlorzoxazone 6-hydroxylation and midazolam 1'-hydroxylation. When the inhibition was greater than 20% in the assay, IC50 values were then determined. The potential in vivo bovine hepatic CYP450 inhibition by those drugs was assessed using a combination of the IC50 values and in vivo Cmax values from pharmacokinetic studies at their commercial doses and administration routes in the literature.

RESULTS

Fifteen bovine medicines or metabolites showed in vitro inhibition on one or more bovine hepatic CYP450 metabolisms with different IC50 values. Desfuroylceftiour (active metabolite of ceftiofur), nitroxinil and flunixin have the potential to inhibit one of the bovine hepatic CYP450 isoforms in vivo at their commercial doses and administration routes. The rest of the bovine medicines had low risks of in vivo bovine hepatic CYP450 inhibition.

CONCLUSION

This combination of in vitro assay and in vivo Cmax data provides a good approach to assess the inhibition of bovine medicines on bovine hepatic CYP450.

Potential for pharmacokinetic interactions between Schisandra sphenanthera and bosutinib, but not imatinib: in vitro metabolism study combined with a physiologically-based pharmacokinetic modelling approach

AIMS

This study aimed to investigate the potential interaction between Schisandra sphenanthera, imatinib and bosutinib combining in vitro and in silico methods.

METHODS

In vitro metabolism of imatinib and bosutinib using recombinant enzymes and human liver microsomes were investigated in the presence and absence of Schisandra lignans. Physiologically-based pharmacokinetic (PBPK) models for the lignans accounting for reversible and mechanism-based inhibitions and induction of CYP3A enzymes were built in the Simcyp Simulator (version 17) and evaluated for their capability to predict interactions with midazolam and tacrolimus. Their potential effect on systemic exposures of imatinib and bosutinib were predicted using PBPK in silico simulations.

RESULTS

Schisantherin A and schisandrol B, but not schisandrin A, potently inhibited CYP3A4-mediated metabolism of imatinib and bosutinib. All three compounds showed a strong reversible inhibition on CYP2C8 enzyme with k_i of less than 0.5 μmol L^-1 . The verified PBPK models were able to describe the increase in systemic exposure of midazolam and tacrolimus due to co-administration of S. sphenanthera, consistent with the reported changes in the corresponding clinical interaction study (AUC ratio of 2.0 vs 2.1 and 2.4 vs 2.1, respectively). The PBPK simulation predicted that at recommended dosing regimens of S. sphenanthera, co-administration would result in an increase in bosutinib exposure (AUC ratio 3.0) but not in imatinib exposure.

CONCLUSION

PBPK models for Schisandra lignans were successfully developed. Interaction between imatinib and Schisandra lignans was unlikely to be of clinical importance. Conversely, S. sphenanthera at a clinically-relevant dose results in a predicted three-fold increase in bosutinib systemic exposure.

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.

Association between clinically relevant toxicities of pazopanib and sunitinib and the use of weak CYP3A4 and P-gp inhibitors

PURPOSE

Sunitinib and pazopanib, two tyrosine kinase inhibitors (TKI), may be targets of potential pharmacokinetic drug-drug interactions (P-PK-DDIs). While strong cytochrome P4503A (CYP3A4) inhibitors or inducers should cause a clinically relevant modification in plasma TKI concentrations, the effect of weak inhibitors is unknown. The objective of this study was to evaluate the association between weak P-PK-DDI and clinically relevant toxicity in real life.

PATIENTS AND METHODS

This was a single-center retrospective study including patients treated with sunitinib or pazopanib for any malignancies, for whom a PK-DDI analysis was performed before starting TKI. The primary endpoint was the correlation between P-PK-DDIs and a dose decrease after 1 month of treatment. The secondary endpoint was the correlation between PK-DDIs and drug withdrawal due to toxicity.

RESULTS

Seventy-six patients were assessed. A P-PK-DDI with weak CYP3A4 or P-gp inhibition was found in 14 patients. In patients with P-PK-DDI or without, the dose was reduced during the first month in 57.1% and 17.7% (p = 0.003) and the drug withdrawn in 42.8% and 11.3% (p = 0.011), respectively. In multivariate analysis, a significant correlation was found between P-PK-DDI (CYP3A4 and P-gp inhibitors) and dose reduction, and between drug withdrawal and PK-DDI (CYP3A4 inhibitors).

CONCLUSION

P-PK-DDI was correlated with dose reduction and drug withdrawal due to toxicity. The causality of this relationship warrants to be assessed; therefore, therapeutic drug monitoring is necessary in patients treated with TKI.

Physiologically based pharmacokinetic modelling of oxycodone drug-drug interactions

Oxycodone is an opioid analgesic with several pharmacologically active metabolites and relatively narrow therapeutic index. Cytochrome P450 (CYP) 3A4 and CYP2D6 play major roles in the metabolism of oxycodone and its metabolites. Thus, inhibition and induction of these enzymes may result in substantial changes in the exposure of both oxycodone and its metabolites. In this study, a physiologically based pharmacokinetic (PBPK) model was built using GastroPlus™ software for oxycodone, two primary metabolites (noroxycodone, oxymorphone) and one secondary metabolite (noroxymorphone). The model was built based on literature and in house in vitro and in silico data. The model was refined and verified against literature clinical data after oxycodone administration in the absence of drug-drug interactions (DDI). The model was further challenged with simulations of oxycodone DDI with CYP3A4 inhibitors ketoconazole and itraconazole, CYP3A4 inducer rifampicin and CYP2D6 inhibitor quinidine. The magnitude of DDI (AUC ratio) was predicted within 1.5-fold error for oxycodone, within 1.8-fold and 1.3-4.5-fold error for the primary metabolites noroxycodone and oxymorphone, respectively, and within 1.4-4.5-fold error for the secondary metabolite noroxymorphone, when compared to the mean observed AUC ratios. This work demonstrated the capability of PBPK model to simulate DDI of the administered compounds and the formed metabolites of both DDI victim and perpetrator. However, the predictions for the formed metabolites tend to be associated with higher uncertainty than the predictions for the administered compound. The oxycodone model provides a tool for forecasting oxycodone DDI with other CYP3A4 and CYP2D6 DDI perpetrators that may be co-administered with oxycodone.

Pterostilbene supplements carry the risk of drug interaction via inhibition of UDP-glucuronosyltransferases (UGT) 1A9 enzymes

Pterostilbene (PT) is a natural stilbene common in small berries and food supplements, possessing numerous pharmacological activities. However, whether PT can affect the activities of UDP-glucuronosyltransferases (UGT) enzymes remains unclear. The aim of the present study was to investigate the effect of PT on UGT activities and to quantitatively evaluate the food-drug interaction potential due to UGT inhibition. Our data indicated that PT exhibited potent inhibition against HLM, UGT1A6, UGT1A9, UGT2B7, and UGT2B15, moderate inhibition against UGT1A1, UGT1A3, UGT1A8, and UGT2B4, negligible inhibition against UGT1A4, UGT1A7, UGT1A10, and UGT2B17. Further kinetic investigation demonstrated that PT exerted potent noncompetitive inhibition 4-MU glucuronidation by UGT1A9, with IC₅₀ and K_i values of 0.92 μM and 0.52 ± 0.04 μM, respectively. Quantitative prediction study suggested that coadministration of PT supplements at 100 mg/day or higher doses may result in at least a 50% increase in the AUC of drugs predominantly cleared by UGT1A9. Thus, the coadministration of PT supplements and drugs primarily cleared by UGT1A9 may result in potential drug interaction, and precautions should be taken when coadministration of PT supplements and drugs metabolized by UGT1A9.

Differential regulation of intestinal and hepatic CYP3A by 1α,25-dihydroxyvitamin D3 : Effects on in vivo oral absorption and disposition of buspirone in rats

1α,25-Dihydroxyvitamin D₃ (also called 1,25(OH)₂ D₃ or calcitriol) is the biologically active form of vitamin D, which functions as a ligand to the vitamin D receptor (VDR). It was previously reported that intestinal cytochrome P450 3A (CYP3A) expression was altered by 1,25(OH)₂ D₃ -mediated VDR activation. However, to clarify whether the change in CYP3A subfamily expression by VDR activation can affect metabolic function, further evidence is needed to prove the effect of 1,25(OH)₂ D₃ treatment on CYP3A-mediated drug metabolism and pharmacokinetics. Here, we report the effects of 1,25(OH)₂ D₃ on CYP3A activity and in vivo pharmacokinetics of buspirone in Sprague-Dawley rats. CYP3A mRNA expression and CYP3A-mediated testosterone metabolism were enhanced in the intestine but were unaffected in the livers of rats treated with 1,25(OH)₂ D₃ . Notably, the oral pharmacokinetic profile of buspirone (CYP3A substrate drug) and 6'-hydroxybuspirone (major active metabolite of buspirone formed via CYP3A-mediated metabolism) was significantly altered, while its intravenous pharmacokinetic profile was not affected by 1,25(OH)₂ D₃ treatment. To the best of our knowledge, this study provides the first reported data regarding the effects of 1,25(OH)₂ D₃ treatment on the in vivo pharmacokinetics of intravenous and oral buspirone in rats, by the differential modulation of hepatic and intestinal CYP3A activity. Our present results could lead to further studies in clinically significant CYP3A-mediated drug-nutrient interactions with 1,25(OH)₂ D₃ , including 1,25(OH)₂ D₃ -buspirone interaction. Preclinical Research & Development.

Mechanisms and Clinical Significance of Pharmacokinetic-Based Drug-Drug Interactions with Drugs Approved by the U.S. Food and Drug Administration in 2017

Pharmacokinetic-based drug-drug interaction (DDI) data for drugs approved by the U.S. Food and Drug Administration in 2017 (N = 34) were analyzed using the University of Washington Drug Interaction Database. The mechanisms and clinical relevance of these interactions were characterized based on information from new drug application reviews. CYP3A inhibition and induction explained most of the observed drug interactions (new drugs as victims or as perpetrators), and transporters mediated about half of all DDIs, alone or with enzymes. Organic anion transporting polypeptide (OATP)1B1/1B3 played a significant role, mediating more than half of the drug interactions with area under the time-plasma curve (AUC) changes ≥5-fold. As victims, five new drugs were identified as sensitive substrates: abemeciclib, midostaurin, and neratinib for CYP3A and glecaprevir and voxilaprevir for OATP1B1/1B3. As perpetrators, three drugs were considered strong inhibitors: ribociclib for CYP3A, glecaprevir/pibrentasvir for OATP1B1/1B3, and sofosbuvir/velpatasvir/voxilaprevir for OATP1B1/1B3 and breast cancer resistance protein. No strong inducer of enzymes or transporters was identified. DDIs with AUC changes ≥5-fold and almost all DDIs with AUC changes 2- to 5-fold had dose recommendations in their respective drug labels. A small fraction of DDIs with exposure changes <2-fold had a labeling impact, mostly related to drugs with narrow therapeutic indices. As with drugs approved in recent years, all drugs found to be sensitive substrates or strong inhibitors of enzymes or transporters were among oncology or antiviral treatments, suggesting a serious risk of DDIs in these patient populations for whom effective therapy is already complex because of polytherapy.

The impact of proton pump inhibitors on the pharmacokinetics of voriconazole in vitro and in vivo

Voriconazole (VRC) and proton pump inhibitors (PPIs) have similar metabolic pathways. The objectives of the study are to evaluate the impact of PPIs on the pharmacokinetics of VRC. Human liver microsomes model was applied to assess the inhibitory effects of PPIs on the metabolism of VRC in vitro. A retrospective study was also carried out to explore the relationship between the plasma VRC trough concentrations and PPIs uses. Patients were divided into six groups: control (n = 166), lansoprazole (LAN, n = 38), esomeprazole (ESO, n = 19), omeprazole (OME, n = 45), pantoprazole (PAN, n = 43), and ilaprazole (ILA, n = 38) groups. All five PPIs showed concentration-dependent inhibitory effects on the VRC metabolism in human liver microsomes, among which LAN, OME and ESO were three of the most potent inhibitors. Consistently, co-administered with LAN, OME and ESO significantly increased the plasma VRC trough levels (p <  0.05), whereas there was no significant association between VRC concentrations and PAN or ILA use. Interestingly, patients in the PPIs groups were more likely to reach the therapeutic VRC range of 1-5.5 μg/mL in steady state when compared with control patients (75-81% VS 69%). In conclusion, although all PPIs showed inhibitory effects on the VRC metabolism in vitro, only LAN, OME and ESO significantly increased VRC plasma concentrations. This study should be helpful for choice of the type of PPIs for patients administered with VRC.

Human hepatocytes and cytochrome P450-selective inhibitors predict variability in human drug exposure more accurately than human recombinant P450s

BACKGROUND AND PURPOSE

Drugs metabolically eliminated by several enzymes are less vulnerable to variable compound exposure in patients due to drug-drug interactions (DDI) or if a polymorphic enzyme is involved in their elimination. Therefore, it is vital in drug discovery to accurately and efficiently estimate and optimize the metabolic elimination profile.

EXPERIMENTAL APPROACH

CYP3A and/or CYP2D6 substrates with well described variability in vivo in humans due to CYP3A DDI and CYP2D6 polymorphism were selected for assessment of fraction metabolized by each enzyme (fmCYP ) in two in vitro systems: (i) human recombinant P450s (hrP450s) and (ii) human hepatocytes combined with selective P450 inhibitors. Increases in compound exposure in poor versus extensive CYP2D6 metabolizers and by the strong CYP3A inhibitor ketoconazole were mathematically modelled and predicted changes in exposure were compared with in vivo data.

KEY RESULTS

Predicted changes in exposure were within twofold of reported in vivo values using fmCYP estimated in human hepatocytes and there was a strong linear correlation between predicted and observed changes in exposure (r2  = 0.83 for CYP3A, r2  = 0.82 for CYP2D6). Predictions using fmCYP in hrP450s were not as accurate (r2  = 0.55 for CYP3A, r2  = 0.20 for CYP2D6).

CONCLUSIONS AND IMPLICATIONS

The results suggest that variability in human drug exposure due to DDI and enzyme polymorphism can be accurately predicted using fmCYP from human hepatocytes and CYP-selective inhibitors. This approach can be efficiently applied in drug discovery to aid optimization of candidate drugs with a favourable metabolic elimination profile and limited variability in patients.

The Inhibitory Effect of Telmisartan on the Metabolism of Arachidonic Acid by CYP2C9 and CYP2C8: An in Vitro Study

Epoxyeicosatorienoic acids (EETs) are generated from arachidonic acid (AA) by CYPs. EETs comprise four regioisomers (14,15-, 11,12-, 8,9-, and 5,6-EET). EETs show potent physiological effects, including vasodilation, anti-inflammation, myocardial preconditioning, and anti-platelet aggregation effects. We recently demonstrated that telmisartan, one of angiotensin II receptor blockers, inhibits AA metabolism by CYP enzymes, including CYP2C8, CYP2C9, and CYP2J2. We conducted studies of AA metabolism using recombinant CYP enzymes to estimate the inhibition constant and the type of inhibition by telmisartan of CYP2C9 and CYP2C8. The contribution ratio (CR) of each CYP enzyme was investigated using human liver microsomes. Dixon and Lineweaver-Burk plots indicated that telmisartan is a mixed inhibitor of both CYP2C9 and CYP2C8; telmisartan did not show a time-dependent inhibition toward these CYP enzymes. Based on the CRs, both CYP2C9 and CYP2C8 are the key enzymes in the metabolism of AA in the human liver. Uptake of telmisartan in the liver by organic anion transporting polypeptide (OATP) 1B3 and the non-linear metabolism in gastrointestinal tract augment the potential of the drug to inhibit the CYP enzymes in the liver.

In vitro assessment of competitive and time-dependent inhibition of the nevirapine metabolism by nortriptyline in rats

Nevirapine (NVP) is a non-nucleoside reverse transcriptase inhibitor of human immunodeficiency virus type 1 (HIV-1) widely used as a component of High Active Antiretroviral Therapy (HAART) since it is inexpensive, readily absorbed after oral administration and non-teratogenic. In the present work, the mechanism of a previously described pharmacokinetic interaction between NVP and the antidepressant drug nortriptyline (NT) was studied using rat hepatic microsomes. The obtained results showed a competitive inhibition of the NVP metabolism by NT. The three main NVP metabolites (2-OH-NVP, 3-OH-NVP and 12-OH-NVP) where competitively inhibited with similar inhibitory constant values (K_i = 4.01, 3.97 and 4.40 μM, respectively). Time-dependent inhibition of the NVP metabolism was also detected, with a 2.5-fold reduction in the IC₅₀ values of NT for 2-, 3-, and 12-OH-NVP formation when NT was preincubated with the microsomal suspension in the presence of an NADPH-generating system. A concentration-dependent inhibition of the formation of NVP metabolites by the main NT metabolite (10-OH-NT) was also observed, however, the inhibitory potency of 10-OH-NT was much lower than that of the parent drug. The apparent hepatic intrinsic clearance of NVP determined in these in vitro experiments was used to predict the in vivo clearance of NVP using the "well-stirred" and the "parallel-tube" models, resulting in values close to those previously observed in vivo clearance. Finally, a good prediction of the increase in the plasma concentrations of NVP when co-administered with NT was obtained employing the inhibitory constant of NT determined in vitro and the estimated plasma concentration of NT entering the liver.

[Quantitative Prediction of Drug-Drug Interaction Caused by CYP Inhibition and Induction from In Vivo Data and Its Application in Daily Clinical Practices-Proposal for the Pharmacokinetic Interaction Significance Classification System (PISCS)]

　Drug-drug interactions (DDIs) can affect the clearance of various drugs from the body; however, these effects are difficult to sufficiently evaluate in clinical studies. This article outlines our approach to improving methods for evaluating and providing drug information relative to the effects of DDIs. In a previous study, total exposure changes to many substrate drugs of CYP caused by the co-administration of inhibitor or inducer drugs were successfully predicted using in vivo data. There are two parameters for the prediction: the contribution ratio of the enzyme to oral clearance for substrates (CR), and either the inhibition ratio for inhibitors (IR) or the increase in clearance of substrates produced by induction (IC). To apply these predictions in daily pharmacotherapy, the clinical significance of any pharmacokinetic changes must be carefully evaluated. We constructed a pharmacokinetic interaction significance classification system (PISCS) in which the clinical significance of DDIs was considered in a systematic manner, according to pharmacokinetic changes. The PISCS suggests that many current 'alert' classifications are potentially inappropriate, especially for drug combinations in which pharmacokinetics have not yet been evaluated. It is expected that PISCS would contribute to constructing a reliable system to alert pharmacists, physicians and consumers of a broad range of pharmacokinetic DDIs in order to more safely manage daily clinical practices.

Bush mint (Hyptis suaveolens) and spreading hogweed (Boerhavia diffusa) medicinal plant extracts differentially affect activities of CYP1A2, CYP2D6 and CYP3A4 enzymes

ETHNO-PHARMACOLOGICAL RELEVANCE

Hyptis suaveolens (L) Poit and Boerhavia diffusa Linn are medicinal herbal plants commonly found in the tropics and sub-tropics. They are used to treat various conditions among them boils, dyslipidaemia, eczema, malaria, jaundice and gonorrhoea. Thus, the herbal medicinal extracts are now found as part of some commercial herbal formulations. There has not been adequate characterization of these medicinal herbs on their effects on drug metabolising enzymes.

AIM OF THE STUDY

To investigate the effects of extracts of Hyptis suaveolens (HS) and Boerhavia diffusa (BD) on activity of drug metabolising enzymes, CYP1A2, CYP2D6 and CYP3A4, as well predict their potential for herb-drug interaction. A secondary aim was to identify constituent compounds such as polyphenolics, in the crude extract preparations of Hyptis suaveolens and Boerhavia diffusa and measure them for activity.

MATERIALS AND METHODS

CYP450 inhibition assays using recombinant CYP450 (rCYP) and fluorescence screening employing individual isozymes (CYP1A2, CYP2D6 and CYP3A4) were used to determine reversible- and time-dependent inhibition (TDI) profiles of extracts of Hyptis suaveolens and Boerhavia diffusa. Inhibition kinetic parameters, K_i and K_inact were also estimated. UPLC-MS employing a Synapt G2 (ESI negative) coupled to a PDA detector was used to identify polyphenolic compounds in crude extracts of Hyptis suaveolens and Boerhavia diffusa.

RESULTS

The inhibitory potency of Hyptis suaveolens and Boerhavia diffusa extracts varied among the different enzymes, with CYP1A2 (3.68 ± 0.10µg/mL) being the least inhibited by HS compared to CYP2D6 (1.39 ± 0.01µg/mL) and CYP3A4 (2.36 ± 0.57µg/mL). BD was most potent on CYP3A4 (7.36 ± 0.94µg/mL) compared to both CYP2D6 (17.79 ± 1.02µg/mL) and CYP1A2 (9.48 ± 0.78µg/mL). Extracts of Hyptis suaveolens and Boerhavia diffusa exhibited TDIs on all CYPs. The most prominent phenolic candidates identified in both medicinal herbs using UPLC-MS analysis included caffeic acid, rutin, quercetin, citric acid, ferulic acid and gluconic acid. These phenolic compounds are thought to potentially give HS and BD their therapeutic effects and inhibitory characteristics affecting CYP450 activities. In vivo predictions showed the potential for HS and BD extracts to cause significant interactions if co-administered with other medications.

CONCLUSIONS

The study reveals that crude aqueous extracts of HS and BD potentially inhibit drug metabolising isozymes CYP1A2, CYP2D6 and CYP3A4 in a reversible and time-dependent manner. Thus care should be taken when these extracts are co-administered with drugs that are substrates of CYP1A2, CYP2D6 and CYP3A4.

The effect of lycopene on cytochrome P450 isoenzymes and P-glycoprotein by using human liver microsomes and Caco-2 cell monolayer model

Lycopene is widely used as a dietary supplement. However, the effects of lycopene on cytochrome P450 (CYP) enzymes or P-glycoprotein (P-gp) are not comprehensive. The present study was performed to investigate the effects of lycopene on the CYP enzymes and P-gp activity. A cocktail method was used to evaluate the activities of CYP3A4, CYP2C9, CYP2C19, CYP2D6 and CYP2E1. Caco-2 cell monolayer model was carried out to assay lycopene on P-gp activity. The results indicated that lycopene had a moderate inhibitory effect on CYP2E1, with IC50 value of 43.65 μM, whereas no inhibitory effects on CYP3A4, CYP2C19, CYP2D6 and CYP2E1, with IC50 values all over 100 μM. In addition, lycopene showed almost no inhibitory effect on rhodamine-123 efflux and uptake (p > .05), indicated no effects on P-gp activity. In conclusion, there should be required attention when lycopene are coadministered with other drugs that are metabolised by CYP2E1.

Translational High-Dimensional Drug Interaction Discovery and Validation Using Health Record Databases and Pharmacokinetics Models

Polypharmacy increases the risk of drug-drug interactions (DDIs). Combining epidemiological studies with pharmacokinetic modeling, we detected and evaluated high-dimensional DDIs among 30 frequent drugs. Multidrug combinations that increased the risk of myopathy were identified in the US Food and Drug Administration Adverse Event Reporting System (FAERS) and electronic medical record (EMR) databases by a mixture drug-count response model. CYP450 inhibition was estimated among the 30 drugs in the presence of 1 to 4 inhibitors using in vitro / in vivo extrapolation. Twenty-eight three-way and 43 four-way DDIs had significant myopathy risk in both databases and predicted increases in the area under the concentration-time curve ratio (AUCR) >2-fold. The high-dimensional DDI of omeprazole, fluconazole, and clonidine was associated with a 6.41-fold (FAERS) and 18.46-fold (EMR) increased risk of myopathy local false discovery rate (<0.005); the AUCR of omeprazole in this combination was 9.35. The combination of health record informatics and pharmacokinetic modeling is a powerful translational approach to detect high-dimensional DDIs.

Hepatic transporter drug-drug interactions: an evaluation of approaches and methodologies

INTRODUCTION

Drug-drug interactions (DDIs) continue to account for 5% of hospital admissions and therefore remain a major regulatory concern. Effective, quantitative prediction of DDIs will reduce unexpected clinical findings and encourage projects to frontload DDI investigations rather than concentrating on risk management ('manage the baggage') later in drug development. A key challenge in DDI prediction is the discrepancies between reported models. Areas covered: The current synopsis focuses on four recent influential publications on hepatic drug transporter DDIs using static models that tackle interactions with individual transporters and in combination with other drug transporters and metabolising enzymes. These models vary in their assumptions (including input parameters), transparency, reproducibility and complexity. In this review, these facets are compared and contrasted with recommendations made as to their application. Expert opinion: Over the past decade, static models have evolved from simple [I]/k_i models to incorporate victim and perpetrator disposition mechanisms including the absorption rate constant, the fraction of the drug metabolised/eliminated and/or clearance concepts. Nonetheless, models that comprise additional parameters and complexity do not necessarily out-perform simpler models with fewer inputs. Further, consideration of the property space to exploit some drug target classes has also highlighted the fine balance required between frontloading and back-loading studies to design out or 'manage the baggage'.

Combined effect of telmisartan and fluvastatin on arachidonic acid metabolism in human liver microsomes

1. Epoxyeicosatrienoic acids (EETs), metabolites of arachidonic acid (AA) via cytochrome P450s, have a protective effect on the cardiovascular system involving vasodilation. We have previously demonstrated that telmisartan (TEL) inhibits EETs production from AA in vitro. 2. The objectives of the study were to examine the inhibitory effect of fluvastatin (FLU), an inhibitor of CYP2C9, and the combined effect of TEL and FLU on the production of EETs using human liver microsomes. The combined effect of TEL and FLU was evaluated using two methods, the fixed concentration method and the fixed ratio method. 3. FLU significantly reduced total eicosanoids (sum of EETs and their subsequent metabolites dihydroxyeicosatrienoic acids) production at > 0.25 µM. The results of the fixed concentration method indicated that the addition of the other inhibitor resulted in significant reduction of the production of total eicosanoids in a concentration-dependent manner. In the fixed ratio method, the combination of TEL and FLU over all concentration ratios tested did not produce a horizontal shift in the dose response curves. 4. Our results showing an additive combined effect of TEL and FLU on AA metabolism, suggest that concomitant treatment with TEL and FLU would theoretically affect the vascular tone mediated by EETs from AA.

Physiologically based pharmacokinetic modeling of tea catechin mixture in rats and humans

Although green tea (Camellia sinensis) (GT) contains a large number of polyphenolic compounds with anti-oxidative and anti-proliferative activities, little is known of the pharmacokinetics and tissue dose of tea catechins (TCs) as a chemical mixture in humans. The objectives of this study were to develop and validate a physiologically based pharmacokinetic (PBPK) model of tea catechin mixture (TCM) in rats and humans, and to predict an integrated or total concentration of TCM in the plasma of humans after consuming GT or Polyphenon E (PE). To this end, a PBPK model of epigallocatechin gallate (EGCg) consisting of 13 first-order, blood flow-limited tissue compartments was first developed in rats. The rat model was scaled up to humans by replacing its physiological parameters, pharmacokinetic parameters and tissue/blood partition coefficients (PCs) with human-specific values. Both rat and human EGCg models were then extrapolated to other TCs by substituting its physicochemical parameters, pharmacokinetic parameters, and PCs with catechin-specific values. Finally, a PBPK model of TCM was constructed by linking three rat (or human) tea catechin models together without including a description for pharmacokinetic interaction between the TCs. The mixture PBPK model accurately predicted the pharmacokinetic behaviors of three individual TCs in the plasma of rats and humans after GT or PE consumption. Model-predicted total TCM concentration in the plasma was linearly related to the dose consumed by humans. The mixture PBPK model is able to translate an external dose of TCM into internal target tissue doses for future safety assessment and dose-response analysis studies in humans. The modeling framework as described in this paper is also applicable to the bioactive chemical in other plant-based health products.

Predictions of bisphenol A hepatic clearance in the isolated perfused rat liver (IPRL): impact of albumin binding and of co-administration with naproxen

1. This study aimed (i) to characterise hepatic clearance (CL) of bisphenol A (BPA) and naproxen (NAP) administered alone or in binary mixtures to highlight the influence of a binding to albumin (ALB) using an isolated perfused rat liver (IPRL) system; and (ii) to compare results of prediction algorithms with measured clearance rates. 2. The IPRL system and liver microsomes were used to determine the metabolic constants of BPA and NAP either in the presence or absence of ALB. In this study, the IPRL was used as proxy for the in vivo situation. Accordingly, diverse in vitro-to-in vivo and in vivo-to-in vivo extrapolations (IVIVEs) were made to predict CL of BPA determined in situ/in vivo with ALB from metabolic data determined without ALB by using different binding correction methods (i.e., direct and conventional scaling as well as a novel scaling considering an ALB-facilitated uptake mechanism). 3. The addition of ALB significantly influenced the liver kinetics of BPA and NAP either administered alone or in binary mixtures, which was reflected in the Michaelis-Menten constants. Analysis of concomitant exposures of BPA and NAP gave a fully competitive inhibition. Furthermore, the IVIVE method based on the ALB-facilitated uptake mechanism provided the most accurate predictions of CL_{in vivo} as compared with the other IVIVE methods when the impact of ALB is considered. 4. Our findings support the notion that high binding to ALB reduces the biotransformation of BPA and NAP when administered alone or in mixtures in the IPRL system. However, the free drug concentration in liver in vivo is probably higher than expected since the IVIVE method based on a potential ALB-facilitated uptake mechanism is the most robust prediction method. Overall, this study should improve the physiologically-based pharmacokinetic (PBPK) modelling of chemical-drug interactions.

Predicting Inhibitory Drug—Drug Interactions and Evaluating Drug Interaction Reports Using Inhibition Constants

OBJECTIVE:

To review the use of inhibitory constants (Ki) determined from in vitro experiments in the prediction of the significance of inhibitory drug—drug interactions (DDIs).

DATA SOURCES:

Searches of MEDLINE (1966—August 2004) and manual review of journals, conference proceedings, reference textbooks, and Web sites were performed using the key search terms cytochrome P450, drug—drug interaction, inhibition constant, and Ki.

STUDY SELECTION AND DATA EXTRACTION:

All articles identified from the data sources were evaluated, and information deemed relevant was included for this review.

DATA SYNTHESIS:

The cytochrome P450 isoenzymes factor prominently in the explanation of numerous DDIs. Although the regulation of these enzymes by one drug can affect the pharmacokinetics of other drugs, the consequences may not necessarily be significant either in terms of pharmacokinetic or clinical outcomes. Yet, many DDI monographs originate as unconfirmed case reports that implicate the influence of one drug on the CYP-mediated metabolism of another, and these often uncorroborated mechanisms can eventually become regarded as dogma. One consequence of this process is the overprediction of potentially important DDIs. The pharmaceutical industry, Food and Drug Administration, and pharmaceutical scientists have developed a strategy for predicting the significance of inhibitory DDIs at the earliest possible stages of drug development based on a new chemical entity's Ki value, determined in vitro.

CONCLUSIONS:

We suggest that the use of Ki values of drugs purported to behave as CYP inhibitors be incorporated in the assessment of case reports that ascribe DDIs to inhibition of metabolism of one drug by another.

An S-warfarin and AZD1981 interaction: in vitro and clinical pilot data suggest the N-deacetylated amino acid metabolite as the primary perpetrator

AIM

AZD1981 is an orally bioavailable chemoattractant receptor-homologous molecule expressed on Th2 cells (CRTh2) receptor antagonist progressed to phase II trials for the treatment of allergic asthma. Previously performed in vitro human hepatocyte incubations identified N-deacetylated AZD1981 as a primary metabolite. We report on metabolite exposure from a clinical excretion balance, on in vitro studies performed to determine the likelihood of a metabolite-dependent drug-drug interaction (DDI) and on a clinical warfarin DDI study. The aim was to demonstrate that N-deacetylated AZD1981 is responsible for the observed interaction.

METHODS

The excretion and biotransformation of [¹⁴ C]-AZD1981 were studied in healthy male volunteers, and subsequently in vitro cytochrome P450 (CYP) inhibition and hepatocyte uptake investigations were carried out with metabolites and the parent drug. A clinical DDI study using coadministered twice-daily 100 mg and 400 mg AZD1981 with 25 mg warfarin was performed.

RESULTS

The excretion balance study showed N-deacetylated AZD1981 to be the most abundant metabolite present in plasma. In vitro data revealed the metabolite to be a weak CYP2C9 time-dependent inhibitor, subject to more active hepatic uptake than the parent molecule. Clinically, the S-warfarin area under the plasma concentration-time curve increased, on average, 1.4-fold [95% confidence interval (CI) 1.22, 1.50] and 2.4-fold (95% CI 2.11, 2.64) after 100 mg (n = 13) and 400 mg (n = 11) AZD1981 administration, respectively. In vitro CYP inhibition and hepatocyte uptake data were used to explain the interaction.

CONCLUSIONS

N-deacetylated AZD1981 can be added to the small list of drug metabolites reported as sole contributors to clinical drug-drug interactions, with weak time-dependent inhibition exacerbated by efficient hepatic uptake being the cause.

Quantitative Prediction of Drug-Drug Interactions Involving Inhibitory Metabolites in Drug Development: How Can Physiologically Based Pharmacokinetic Modeling Help?

This subteam under the Drug Metabolism Leadership Group (Innovation and Quality Consortium) investigated the quantitative role of circulating inhibitory metabolites in drug-drug interactions using physiologically based pharmacokinetic (PBPK) modeling. Three drugs with major circulating inhibitory metabolites (amiodarone, gemfibrozil, and sertraline) were systematically evaluated in addition to the literature review of recent examples. The application of PBPK modeling in drug interactions by inhibitory parent-metabolite pairs is described and guidance on strategic application is provided.