CYP3A4-based drug–drug interaction: CYP3A4 substrates’ pharmacokinetic properties and ketoconazole dose regimen effect

Exploring the Therapeutic Potential of Petiveria alliacea L. Phytochemicals: A Computational Study on Inhibiting SARS-CoV-2's Main Protease (Mpro)

The outbreak of SARS-CoV-2, also known as the COVID-19 pandemic, is still a critical risk factor for both human life and the global economy. Although, several promising therapies have been introduced in the literature to inhibit SARS-CoV-2, most of them are synthetic drugs that may have some adverse effects on the human body. Therefore, the main objective of this study was to carry out an in-silico investigation into the medicinal properties of Petiveria alliacea L. (P. alliacea L.)-mediated phytocompounds for the treatment of SARS-CoV-2 infections since phytochemicals have fewer adverse effects compared to synthetic drugs. To explore potential phytocompounds from P. alliacea L. as candidate drug molecules, we selected the infection-causing main protease (Mpro) of SARS-CoV-2 as the receptor protein. The molecular docking analysis of these receptor proteins with the different phytocompounds of P. alliacea L. was performed using AutoDock Vina. Then, we selected the three top-ranked phytocompounds (myricitrin, engeletin, and astilbin) as the candidate drug molecules based on their highest binding affinity scores of -8.9, -8.7 and -8.3 (Kcal/mol), respectively. Then, a 100 ns molecular dynamics (MD) simulation study was performed for their complexes with Mpro using YASARA software, computed RMSD, RMSF, PCA, DCCM, MM/PBSA, and free energy landscape (FEL), and found their almost stable binding performance. In addition, biological activity, ADME/T, DFT, and drug-likeness analyses exhibited the suitable pharmacokinetics properties of the selected phytocompounds. Therefore, the results of this study might be a useful resource for formulating a safe treatment plan for SARS-CoV-2 infections after experimental validation in wet-lab and clinical trials.

The influence of drug-induced metabolic enzyme activity inhibition and CYP3A4 gene polymorphism on aumolertinib metabolism

The purpose of this study is to clarify the drug interaction profile of aumolertinib, and the influence of CYP3A4 genetic polymorphism on aumolertinib metabolic characteristics. Through microsomal enzyme reactions, we screened 153 drugs and identified 15 that significantly inhibited the metabolism of aumolertinib. Among them, telmisartan and carvedilol exhibited potent inhibitory activities in rat liver microsomes (RLM) and human liver microsomes (HLM). In vivo, the pharmacokinetic parameters of aumolertinib, including AUC and Cmax, were significantly altered when co-administered with carvedilol, with a notable decrease in the clearance rate CLz/F. Interestingly, the pharmacokinetic parameters of the metabolite HAS-719 exhibited a similar trend as aumolertinib when co-administered. Mechanistically, both telmisartan and carvedilol exhibited a mixed-type inhibition on the metabolism of aumolertinib. Additionally, we used a baculovirus-insect cell expression system to prepare 24 recombinant CYP3A4 microsomes and obtained enzymatic kinetic parameters using aumolertinib as a substrate. Enzyme kinetic studies obtained the kinetic parameters of various CYP3A4 variant-mediated metabolism of aumolertinib. Based on the relative clearance rates, CYP3A4.4, 5, 7, 8, 9, 12, 13, 14, 17, 18, 19, 23, 24, 33, and 34 showed significantly lower clearance rates compared to the wild-type. Among the different CYP3A4 variants, the inhibitory potency of telmisartan and carvedilol on the metabolism of aumolertinib also varied. The IC50 values of telmisartan and carvedilol in CYP3A4.1 were 6.68 ± 1.76 μM and 0.60 ± 0.25 μM, respectively, whereas in CYP3A4.12, the IC50 exceeded 100 μM. Finally, we utilized adeno-associated virus to achieve liver-specific high expression of CYP3A4*1 and CYP3A4*12. In the group with high expression of the less active CYP3A4*12, the magnitude of the drug-drug interaction was significantly attenuated. In conclusion, CYP3A4 genetic polymorphism not only influences the pharmacokinetic characteristics of aumolertinib, but also the inhibitory potency of telmisartan and carvedilol on it.

Modeling the complexity of drug-drug interactions: A physiologically-based pharmacokinetic study of Lenvatinib with Schisantherin A/Schisandrin A

BACKGROUND

Lenvatinib's efficacy as a frontline targeted therapy for radioactive iodine-refractory thyroid carcinoma and advanced hepatocellular carcinoma owes to its inhibition of multiple tyrosine kinases. However, as a CYP3A4 substrate, lenvatinib bears susceptibility to pharmacokinetic modulation by co-administered agents. Schisantherin A (STA) and schisandrin A (SIA) - bioactive lignans abundant in the traditional Chinese medicinal Wuzhi Capsule - act as CYP3A4 inhibitors, engendering the potential for drug-drug interactions (DDIs) with lenvatinib.

METHODS

To explore potential DDIs between lenvatinib and STA/SIA, we developed a physiologically-based pharmacokinetic (PBPK) model for lenvatinib and used it to construct a DDI model for lenvatinib and STA/SIA. The model was validated with clinical trial data and used to predict changes in lenvatinib exposure with combined treatment.

RESULTS

Following single-dose administration, the predicted area under the plasma concentration-time curve (AUC) and maximum plasma concentrations (Cmax) of lenvatinib increased 1.00- to 1.03-fold and 1.00- to 1.01-fold, respectively, in the presence of STA/SIA. Simulations of multiple-dose regimens revealed slightly greater interactions, with lenvatinib AUC0-t and Cmax increasing up to 1.09-fold and 1.02-fold, respectively.

CONCLUSION

Our study developed the first PBPK and DDI models for lenvatinib as a victim drug. STA and SIA slightly increased lenvatinib exposure in simulations, providing clinically valuable information on the safety of concurrent use. Given the minimal pharmacokinetic changes, STA/SIA are unlikely to interact with lenvatinib through pharmacokinetic alterations synergistically but rather may enhance efficacy through inherent anti-cancer efficacy of STA/ SIA.

Prediction of Cytochrome P450 Inhibition Using a Deep Learning Approach and Substructure Pattern Recognition

Cytochrome P450 (CYP) is a family of enzymes that are responsible for about 75% of all metabolic reactions. Among them, CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 participate in the metabolism of most drugs and mediate many adverse drug reactions. Therefore, it is necessary to estimate the chemical inhibition of Cytochrome P450 enzymes in drug discovery and the food industry. In the past few decades, many computational models have been reported, and some provided good performance. However, there are still several issues that should be resolved for these models, such as single isoform, models with unbalanced performance, lack of structural characteristics analysis, and poor availability. In the present study, the deep learning models based on python using the Keras framework and TensorFlow were developed for the chemical inhibition of each CYP isoform. These models were established based on a large data set containing 85715 compounds extracted from the PubChem bioassay database. On external validation, the models provided good AUC values with 0.97, 0.94, 0.94, 0.96, and 0.94 for CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4, respectively. The models can be freely accessed on the Web server named CYPi-DNNpredictor (cypi.sapredictor.cn), and the codes for the model were made open source in the Supporting Information. In addition, we also analyzed the structural characteristics of chemicals with CYP450 inhibition and detected the structural alerts (SAs), which should be responsible for the inhibition. The SAs were also made available online, named CYPi-SAdetector (cypisa.sapredictor.cn). The models can be used as a powerful tool for the prediction of CYP450 inhibitors, and the SAs should provide useful information for the mechanisms of Cytochrome P450 inhibition.

Cannabidiol Inhibits In Vitro Human Liver Microsomal Metabolism of Remdesivir

Introduction: The year 2020 began with the world being flounced with a wave of novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) disease, named COVID-19. Based on promising pre-clinical and clinical data, remdesivir (RDV) was the first drug to receive FDA approval and so far, it is the most common therapy for treatment of SARS-CoV-2/MERS-CoV. However, following intravenous administration, RDV metabolizes majorly by human liver carboxylesterase 1 (CES1) and marginally by the CYP3A4 enzyme in merely less than an hour. Its resultant active metabolite is a hydrophilic nucleoside with very limited accumulation within lung tissues. Therefore, there is a need to investigate strategies to overcome such premature metabolism issues and improve the antiviral efficacy of RDV at the target site. Objective: Considering the major CES1-mediated metabolism of RDV on systemic administration, we intend to explore the remarkable CES1 plus CYP3A4 inhibitory activity of cannabidiol (CBD) against in vitro microsomal metabolism of RDV to indicate its therapeutic potential as an adjuvant to RDV in the treatment and management of COVID-19. Methods: We investigated the in vitro human liver microsomal metabolism of RDV in the presence of two potential CES1 inhibitors-CBD and nelfinavir, and two standard CYP3A4 inhibitors-ritonavir (RITO) and cyclosporin A. The microsomal metabolism assay was further validated by using a well-characterized CYP3A4-selective substrate, midazolam (MDZ), in the presence of CBD and RITO. Results: Our findings depicted that RDV was rapidly and completely metabolized by human liver microsomes within 60 min. Coincubation with CBD substantially reduced microsomal metabolism of RDV and prolonged its in vitro half-life from 8.93 to 31.07 min. CBD showed significantly higher inhibition of RDV compared with known CES1 and CYP3A4 inhibitors. Inhibition of MDZ metabolism by CBD and RITO further validated the assay. Conclusions: The current study strongly suggests that CBD significantly inhibits human liver microsomal metabolism of RDV and extends its in vitro half-life. Thus, concomitant administration of CBD with RDV intravenous injection could be a promising strategy to prevent premature metabolism in COVID-19 patients.

The anti-SARS-CoV-2 activity of novel 9, 10-dihydrophenanthrene derivatives: an insight into molecular docking, ADMET analysis, and molecular dynamics simulation

Originating in Wuhan, the COVID-19 pandemic wave has had a profound impact on the global healthcare system. In this study, we used a 2D QSAR technique, ADMET analysis, molecular docking, and dynamic simulations to sort and evaluate the performance of thirty-nine bioactive analogues of 9,10-dihydrophenanthrene. The primary goal of the study is to use computational approaches to create a greater variety of structural references for the creation of more potent SARS-CoV-2 3Clpro inhibitors. This strategy is to speed up the process of finding active chemicals. Molecular descriptors were calculated using 'PaDEL' and 'ChemDes' software, and then redundant and non-significant descriptors were eliminated by a module in 'QSARINS ver. 2.2.2'. Subsequently, two statistically robust QSAR models were developed by applying multiple linear regression (MLR) methods. The correlation coefficients obtained by the two models are 0.89 and 0.82, respectively. These models were then subjected to internal and external validation tests, Y-randomization, and applicability domain analysis. The best model developed is applied to designate new molecules with good inhibitory activity values against severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). We also examined various pharmacokinetic properties using ADMET analysis. Then, through molecular docking simulations, we used the crystal structure of the main protease of SARS-CoV-2 (3CLpro/Mpro) in a complex with the covalent inhibitor "Narlaprevir" (PDB ID: 7JYC). We also supported our molecular docking predictions with an extended molecular dynamics simulation of a docked ligand-protein complex. We hope that the results obtained in this study can be used as good anti-SARS-CoV-2 inhibitors.

A Physiologically Based Pharmacokinetic Model of Ketoconazole and Its Metabolites as Drug-Drug Interaction Perpetrators

The antifungal ketoconazole, which is mainly used for dermal infections and treatment of Cushing's syndrome, is prone to drug-food interactions (DFIs) and is well known for its strong drug-drug interaction (DDI) potential. Some of ketoconazole's potent inhibitory activity can be attributed to its metabolites that predominantly accumulate in the liver. This work aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model of ketoconazole and its metabolites for fasted and fed states and to investigate the impact of ketoconazole's metabolites on its DDI potential. The parent-metabolites model was developed with PK-Sim^® and MoBi^® using 53 plasma concentration-time profiles. With 7 out of 7 (7/7) DFI AUC_last and DFI C_max ratios within two-fold of observed ratios, the developed model demonstrated good predictive performance under fasted and fed conditions. DDI scenarios that included either the parent alone or with its metabolites were simulated and evaluated for the victim drugs alfentanil, alprazolam, midazolam, triazolam, and digoxin. DDI scenarios that included all metabolites as reversible inhibitors of CYP3A4 and P-gp performed best: 26/27 of DDI AUC_last and 21/21 DDI C_max ratios were within two-fold of observed ratios, while DDI models that simulated only ketoconazole as the perpetrator underperformed: 12/27 DDI AUC_last and 18/21 DDI C_max ratios were within the success limits.

Impact of Multiple Concomitant CYP3A Inhibitors on Venetoclax Pharmacokinetics: A PBPK and Population PK-Informed Analysis

Venetoclax is an approved, orally bioavailable, B-cell lymphoma type 2 (BCL-2) inhibitor that is primarily metabolized by cytochrome P450 3A (CYP3A). Polypharmacy is common in patients undergoing treatment for hematological malignancies such as acute myeloid leukemia or chronic lymphocytic leukemia, and although venetoclax exposure has been well characterized with 1 concomitant CYP3A inhibitor, complex drug-drug interactions (DDIs) involving more than 1 inhibitor have not been systematically evaluated. Here, we aimed to describe the potential impact of multiple concomitant CYP3A inhibitors on venetoclax pharmacokinetics (PK) using physiologically based pharmacokinetic (PBPK) and population PK modeling. The modeling approaches were informed by clinical data in the presence of single or multiple CYP3A inhibitors, and the effects of 1 or more inhibitors were systematically considered within these modeling frameworks. The PBPK modeling approach was independently validated against clinical data involving more than 1 CYP3A inhibitor along with CYP3A substrates other than venetoclax. Both approaches indicated that combining a strong CYP3A inhibitor with another competitive CYP3A inhibitor does not seem to result in any additional increase in venetoclax exposure, beyond what would be expected with a strong inhibitor alone. This suggests that the current dose reductions recommended for venetoclax would be appropriate even when 2 or more CYP3A inhibitors are taken concomitantly. However, the results indicate that the involvement of time-dependent inhibition might lead to additional inhibitory effects over and above the effect of a single strong CYP3A inhibitor. Thus, the clinical management of such interactions must consider the underlying mechanism of the interactions.

Changes in Alprazolam Metabolism by CYP3A43 Mutants

Alprazolam is a triazolobenzodiazepine which is most commonly used in the short-term management of anxiety disorders, often in combination with antipsychotics. The four human members of the CYP3A subfamily are mainly responsible for its metabolism, which yields the main metabolites 4-hydroxyalprazolam and α-hydroxyalprazolam. We performed a comparison of alprazolam metabolism by all four CYP3A enzymes upon recombinant expression in the fission yeast Schizosaccharomyces pombe. CYP3A4 and CYP3A5 show the highest 4-hydroxyalprazolam production rates, while CYP3A5 alone is the major producer of α-hydroxyalprazolam. For both metabolites, CYP3A7 and CYP3A43 show lower activities. Computational simulations rationalize the difference in preferred oxidation sites observed between the exemplary enzymes CYP3A5 and CYP3A43. Investigations of the alprazolam metabolites formed by three previously described CYP3A43 mutants (L293P, T409R, and P340A) unexpectedly revealed that they produce 4-hydroxy-, but not α-hydroxyalprazolam. Instead, they all also make a different metabolite, which is 5-N-O alprazolam. With respect to 4-hydroxyalprazolam, the mutants showed fourfold (T409R) to sixfold (L293P and P340A) higher production rates compared to the wild-type (CYP3A43.1). In the case of 5-N-O alprazolam, the production rates were similar for the three mutants, while no formation of this metabolite was found in the wild-type incubation.

Development of Physiology Based Pharmacokinetic Model to Predict the Drug Interactions of Voriconazole and Venetoclax

PURPOSE

Venetoclax (VEN), an anti-tumor drug that is a substrate of cytochrome P450 3A enzyme (CYP3A4), is used to treat leukemia. Voriconazole (VCZ) is an antifungal medication that inhibits CYP3A4. The goal of this study is to predict the effect of VCZ on VEN exposure.

METHOD

Two physiological based pharmacokinetics (PBPK) models were developed for VCZ and VEN using the bottom-up and top-down method. VCZ model was also developed to describe the effect of CYP2C19 polymorphism on its pharmacokinetics (PK). The reversible inhibition constant (Ki) of VCZ for CYP3A4 was calibrated using drug-drug interaction (DDI) data of midazolam and VCZ. The clinical verified VCZ and VEN model were used to predict the DDI of VCZ and VEN at clinical dosing scenario.

RESULT

VCZ model predicted VCZ exposure in the subjects of different CYP2C19 genotype and DDI related fold changes of sensitive CYP3A substrate with acceptable prediction error. VEN model can capture PK of VEN with acceptable prediction error. The DDI PBPK model predicted that VCZ increased the exposure of VEN by 4.5-9.6 fold. The increase in VEN exposure by VCZ was influenced by subject's CYP2C19 genotype. According to the therapeutic window, VEN dose should be reduced to 100 mg when co-administered with VCZ.

CONCLUSION

The PBPK model developed here could support individual dose adjustment of VEN and DDI risk assessment. Predictions using the robust PBPK model confirmed that the 100 mg dose adjustment is still applicable in the presence of VCZ with high inter-individual viability.

The Role of Cytochrome P450 Enzymes in COVID-19 Pathogenesis and Therapy

Coronavirus disease 2019 (COVID-19) has become a new public health crisis threatening the world. Dysregulated immune responses are the most striking pathophysiological features of patients with severe COVID-19, which can result in multiple-organ failure and death. The cytochrome P450 (CYP) system is the most important drug metabolizing enzyme family, which plays a significant role in the metabolism of endogenous or exogenous substances. Endogenous CYPs participate in the biosynthesis or catabolism of endogenous substances, including steroids, vitamins, eicosanoids, and fatty acids, whilst xenobiotic CYPs are associated with the metabolism of environmental toxins, drugs, and carcinogens. CYP expression and activity are greatly affected by immune response. However, changes in CYP expression and/or function in COVID-19 and their impact on COVID-19 pathophysiology and the metabolism of therapeutic agents in COVID-19, remain unclear. In this analysis, we review current evidence predominantly in the following areas: firstly, the possible changes in CYP expression and/or function in COVID-19; secondly, the effects of CYPs on the metabolism of arachidonic acid, vitamins, and steroid hormones in COVID-19; and thirdly, the effects of CYPs on the metabolism of therapeutic COVID-19 drugs.

Functional evaluation of vandetanib metabolism by CYP3A4 variants and potential drug interactions in vitro

AIM

To investigate the enzymatic properties of cytochrome P450 3A4 (CYP3A4) variants and their ability to metabolize vandetanib (VNT) in vitro, and to study potential drug interactions in combination with VNT.

METHOD

Recombinant CYP3A4 cell microsomes were prepared using a Bac-to-Bac baculovirus expression system. Enzymatic reactions were carried out, and the metabolites were determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).

RESULTS

The activities of 27 CYP3A4 variants were determined to assess the degree of VNT metabolism that occurred. Analysis indicated that there was enhanced intrinsic clearance (V_max/K_m, CLint) for eight variants (CYP3A4.2, 3, 9, 15, 16, 29, 32, and 33), while there was a significant decrease in CYP3A4.5, 7, 8, 10-14, 17-20, 23, 24, 28, 31, and 34. Compared with CYP3A4.1, no significant differences were found for CYP3A4.6 and 30. Furthermore, the relative clearances were compared between VNT and cabozantinib, which were all metabolized by CYP3A4 with the same indications. When combined with ketoconazole, which is a CYP inhibitor, obvious differences were observed in the potency of VNT between different variants, including CYP3A4.2, 15, and 18.

CONCLUSION

This comprehensive assessment of CYP3A4 variants provides significant insights into the allele-specific metabolism of VNT and drug interactions in vitro. We hope that these comprehensive data will provide references and predictions for the clinical application of VNT.

Development of Robust Quantitative Structure-Activity Relationship Models for CYP2C9, CYP2D6, and CYP3A4 Catalysis and Inhibition

Cytochrome P450 enzymes are responsible for the metabolism of >75% of marketed drugs, making it essential to identify the contributions of individual cytochromes P450 to the total clearance of a new candidate drug. Overreliance on one cytochrome P450 for clearance levies a high risk of drug-drug interactions; and considering that several human cytochrome P450 enzymes are polymorphic, it can also lead to highly variable pharmacokinetics in the clinic. Thus, it would be advantageous to understand the likelihood of new chemical entities to interact with the major cytochrome P450 enzymes at an early stage in the drug discovery process. Typical screening assays using human liver microsomes do not provide sufficient information to distinguish the specific cytochromes P450 responsible for clearance. In this regard, we experimentally assessed the metabolic stability of ∼5000 compounds for the three most prominent xenobiotic metabolizing human cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4, and used the data sets to develop quantitative structure-activity relationship models for the prediction of high-clearance substrates for these enzymes. Screening library included the NCATS Pharmaceutical Collection, comprising clinically approved low-molecular-weight compounds, and an annotated library consisting of drug-like compounds. To identify inhibitors, the library was screened against a luminescence-based cytochrome P450 inhibition assay; and through crossreferencing hits from the two assays, we were able to distinguish substrates and inhibitors of these enzymes. The best substrate and inhibitor models (balanced accuracies ∼0.7), as well as the data used to develop these models, have been made publicly available (https://opendata.ncats.nih.gov/adme) to advance drug discovery across all research groups. SIGNIFICANCE STATEMENT: In drug discovery and development, drug candidates with indiscriminate cytochrome P450 metabolic profiles are considered advantageous, since they provide less risk of potential issues with cytochrome P450 polymorphisms and drug-drug interactions. This study developed robust substrate and inhibitor quantitative structure-activity relationship models for the three major xenobiotic metabolizing cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4. The use of these models early in drug discovery will enable project teams to strategize or pivot when necessary, thereby accelerating drug discovery research.

Functional assessment of the effects of CYP3A4 variants on acalabrutinib metabolism in vitro

AIM

We aimed (i) to study the effects of genetic polymorphism of cytochrome P450 3A4 (CYP3A4) and drug interactions on acalabrutinib (ACA) metabolism and (ii) to investigate the mechanisms underlying the effects of CYP3A4 variants on the differential kinetic profiles of ACA and ibrutinib.

METHOD

Recombinant human CYP3A4 and variants were expressed using a Bac-to-Bac baculovirus expression system. The cell microsome was prepared and subjected to kinetic study. The analyte concentrations were determined by UPLC-MS/MS. A molecular docking assay was employed to investigate the mechanisms leading to differences in kinetic profiles.

RESULTS

The kinetic parameters of ACA, catalyzed by CYP3A4 and 28 of its variants, were determined, including V_max, K_m, and K_si. CYP3A4.6-8, 12, 13, 17, 18, 20, and 30 lost their catalytic function. No significant differences were found for CYP3A4.4, 5, 10, 15, 31, and 34 compared with CYP3A4.1 with respect to intrinsic clearance (V_max/K_m, Clint). However, the Clint values of CYP3A4.9, 14, 16, 19, 23, 24, 28, 32 were obviously decreased, ranging from 0.02 to 0.05 μL/min/pmol. On the contrary, the catalytic activities of CYP3A4.2, 3, 11, 29, and 33 were increased dramatically. The Clint value of CYP3A4.11 was 5.95 times as high as that of CYP3A4.1. Subsequently, CYP3A4.1, 3, 11, 23, and 28 were chosen to study the kinetic changes in combination with ketoconazole. Interestingly, we found the inhibitory potency of ketoconazole varied in different variants. In addition, the kinetic parameters of ibrutinib and ACA were accordingly compared in different CYP3A4 variants. Significant differences in relative clearance were observed among variants, which would probably influence the distance between the redox site and the heme iron atom.

CONCLUSION

Genetic polymorphism of CYP3A4 extensively changes its ACA-metabolizing enzymatic activity. In combination with a CYP inhibitor, its inhibitory potency also varied among different variants. Even the same variants exhibited different capabilities catalyzing ACA. Its enzymatic capabilities are probably determined by the distance between the substrate and the heme iron atom, which could be impacted by mutation.

Proposal of a Safe and Effective Study Design for CYP3A-Mediated Drug-Drug Interactions

Numerous drug-drug interaction (DDI) trials have to be conducted in healthy volunteers based on current regulatory guidelines. Because the worst-case scenario of strong cytochrome P450 (CYP) inhibitors has to be tested, the results and their validity have to be balanced with the risk to volunteer safety. The use of ketoconazole in clinical DDI studies has been discouraged by regulatory agencies due to an alleged risk of liver injury. In order to reduce the risk to healthy volunteers, we carried out a study with single-day exposure to each of 6 perpetrator azole fungistatic drugs. They were evaluated regarding their CYP3A inhibition using microdosed midazolam and a limited sampling strategy. Ratios of areas under the concentration-time curves ranged from 1.93 with isavuconazole to 8.42 with ketoconazole. The highest number of adverse events occurred with voriconazole, followed by ketoconazole; 2 dropouts occurred due to adverse events following itraconazole administration. Literature data on adverse events of azole fungistatic drugs in DDI trials are rare and inconclusive. Only in recent years with the newer drugs are they more precise and reliable. It can be concluded that the duration of preexposure of perpetrator drugs can be reduced to 1 hour before administration of the victim drug. This still can be sufficient to achieve the scientific objectives of the trial with the lowest possible risk.

Structural Perspectives of the CYP3A Family and Their Small Molecule Modulators in Drug Metabolism

Cytochrome P450 enzymes function to catalyze a wide range of reactions, many of which are critically important for drug response. Members of the human cytochrome P450 3A (CYP3A) family are particularly important in drug clearance, and they collectively metabolize more than half of all currently prescribed medications. The ability of these enzymes to bind a large and structurally diverse set of compounds increases the chances of their modulating or facilitating drug metabolism in unfavorable ways. Emerging evidence suggests that individual enzymes in the CYP3A family play discrete and important roles in catalysis and disease progression. Here we review the similarities and differences among CYP3A enzymes with regard to substrate recognition, metabolism, modulation by small molecules, and biological consequence, highlighting some of those with clinical significance. We also present structural perspectives to further characterize the basis of these comparisons.

Effect of glimepiride on the pharmacokinetics of teneligliptin in healthy Korean subjects

WHAT IS KNOWN AND OBJECTIVE

Teneligliptin is a DPP-4 inhibitor used for the treatment of type 2 diabetes mellitus, commonly prescribed in combination with glimepiride. Teneligliptin is metabolized by CYP3A4, and glimepiride might be partly metabolized by CYP3A4. The aim of the study was to investigate the possible effect of glimepiride on the pharmacokinetics of teneligliptin in healthy subjects.

METHODS

A repeated dose, open-label, fixed-sequence study was conducted in 26 healthy subjects. All participants were administered 20 mg teneligliptin daily for 6 days. On day 7, 4 mg glimepiride was administered together with 20 mg teneligliptin. Plasma teneligliptin concentrations were measured at a steady state, and its pharmacokinetic characteristics were compared without and with glimepiride.

RESULTS AND DISCUSSION

No statistically significant difference was found in the effect of glimepiride on teneligliptin pharmacokinetics. The steady-state C_max,ss values of teneligliptin without and with glimepiride were 207.01 ng/mL and 202.15 ng/mL, respectively. Its AUC_τ values at steady-state without and with glimepiride were 1527.8 ng · h/mL and 1578.6 ng · h/mL, respectively. The point estimation of geometric mean ratios (GMR) and the 90% confidence interval for both C_max,ss and AUC_τ were within the equivalence range of 0.8-1.25. The results of the present study revealed that glimepiride did not cause pharmacokinetic interaction with teneligliptin in humans.

WHAT IS NEW AND CONCLUSION

Glimepiride did not affect the pharmacokinetic characteristics of teneligliptin in healthy subjects.

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.

Prediction of drug-drug interactions using physiologically-based pharmacokinetic models of CYP450 modulators included in Simcyp software

In recent years, physiologically based PharmacoKinetic (PBPK) modeling has received growing interest as a useful tool for the assessment of drug pharmacokinetics. It has been demonstrated to be informative and helpful to quantify the modification in drug exposure due to specific physio-pathological conditions, age, genetic polymorphisms, ethnicity and particularly drug-drug interactions (DDIs). In this paper, the prediction success of DDIs involving various cytochrome P450 isoenzyme (CYP) modulators namely ketoconazole (a competitive inhibitor of CYP3A), itraconazole (a competitive inhibitor of CYP3A), clarithromycin (a mechanism-based inhibitor of CYP3A), quinidine (a competitive inhibitor of CYP2D6), paroxetine (a mechanism-based inhibitor of CYP2D6), ciprofloxacin (a competitive inhibitor of CYP1A2), fluconazole (a competitive inhibitor of CYP2C9/2C19) and rifampicin (an inducer of CYP3A) were assessed using Simcyp^® software. The aim of this report was to establish confidence in each CYP-specific modulator file so they can be used in the future for the prediction of DDIs involving new victim compounds. Our evaluation of these PBPK models suggested that they can be successfully used to evaluate DDIs in untested scenarios. The only noticeable exception concerned a quinidine inhibitor model that requires further improvement. Additionally, other important aspects such as model validation criteria were discussed.

The absorption kinetics of ketoconazole plays a major role in explaining the reported variability in the level of interaction with midazolam: Interplay between formulation and inhibition of gut wall and liver metabolism

The impact of different single oral doses of ketoconazole (KTZ) (100, 200 and 400 mg) and of staggering its dosage (400 mg at -12, -2, 0, 2 and 4 h), with respect to the administration of a single 5 mg oral dose of midazolam (MDZ) on the extent of inhibition of the metabolism of the latter, was evaluated in healthy subjects in two separate studies. Escalation of the ketoconazole dosage resulted in 2.3 (1.9), 2.7 (1.7) and 4.2 (2.5) -fold increases in the mean AUC_(0,12h) (and C_max ) values of midazolam. Dose-staggering was associated with 3.9 (2.5), 4.9 (2.9), 5.4 (2.8), 2.0 (1.3) and 1.2 (0.9) -fold increases in the mean AUC_(0,12h) (and C_max ) of midazolam. These findings could be predicted by physiologically based pharmacokinetic (PBPK) modelling using the ADAM (advanced dissolution absorption and metabolism) model within the Simcyp Simulator (Version 12 Release 2) to characterize the absorption kinetics of ketoconazole with respect to disintegration time, supersaturation ratio and precipitation rate. This study also emphasizes a need to account for inter-individual variability in the gut wall and systemic exposure of inhibitors with physicochemical properties similar to ketoconazole, in particular in their rate of oral absorption and when using different pharmaceutical formulations, in designing and evaluating the extent of drug-drug interactions. Copyright © 2016 John Wiley & Sons, Ltd.

Progress in Prediction and Interpretation of Clinically Relevant Metabolic Drug-Drug Interactions: a Minireview Illustrating Recent Developments and Current Opportunities

PURPOSE OF REVIEW

This review gives a perspective on the current "state of the art" in metabolic drug-drug interaction (DDI) prediction. We highlight areas of successful prediction and illustrate progress in areas where limits in scientific knowledge or technologies prevent us from having full confidence.

RECENT FINDINGS

Several examples of success are highlighted. Work done for bitopertin shows how in vitro and clinical data can be integrated to give a model-based understanding of pharmacokinetics and drug interactions. The use of interpolative predictions to derive explicit dosage recommendations for untested DDIs is discussed using the example of ibrutinib, and the use of DDI predictions in lieu of clinical studies in new drug application packages is exemplified with eliglustat and alectinib. Alectinib is also an interesting case where dose adjustment is unnecessary as the activity of a major metabolite compensates sufficiently for changes in parent drug exposure. Examples where "unusual" cytochrome P450 (CYP) and non-CYP enzymes are responsible for metabolic clearance have shown the importance of continuing to develop our repertoire of in vitro regents and techniques. The time-dependent inhibition assay using human hepatocytes suspended in full plasma allowed improved DDI predictions, illustrating the importance of continued in vitro assay development and refinement.

SUMMARY

During the past 10 years, a highly mechanistic understanding has been developed in the area of CYP-mediated metabolic DDIs enabling the prediction of clinical outcome based on preclinical studies. The combination of good quality in vitro data and physiologically based pharmacokinetic modeling may now be used to evaluate DDI risk prospectively and are increasingly accepted in lieu of dedicated clinical studies.

A highly sensitive LC-MS/MS method for determination of ketoconazole in human plasma: Application to a clinical study of the exposure to ketoconazole in patients after topical administration

A simple, rapid and highly sensitive LC-MS/MS method was developed and validated for the determination of ketoconazole in human plasma. Sample preparation was accomplished through a single step liquid-liquid extraction by ethyl acetate. The chromatography separation was carried out on a Hedera CN (150mm×2.1mm, 5μm) column with isocratic elution using acetonitrile and 10mM ammonium acetate containing 0.1% formic acid (45:55, v/v) as the mobile phase. The flow rate was 0.5mL/min. Detection was performed in the positive ion electrospray ionization mode using multiple reaction monitoring of the transitions of 531.2→489.3 and 286.1→217.1 for ketoconazole and letrozole (the internal standard), respectively. The method exhibited good linearity over the concentration range of 0.01-12ng/mL for ketoconazole. The intra- and inter-batch precision and accuracy of ketoconazole were all within the acceptable criteria. The method was successfully applied to a clinical study of the exposure to ketoconazole in Chinese seborrheic dermatitis patients after topical administration of two ketoconazole formulations of foam and lotion, respectively. The study results showed that there was little systemic absorption of ketoconazole in patients for the two formulations, and the ketoconazole foam and lotion are safe therapeutic drugs for seborrheic dermatitis patients.