Itraconazole and Clarithromycin as Ketoconazole Alternatives for Clinical CYP3A Inhibition Studies

Evaluation of drug-drug interaction between Suraxavir Marboxil (GP681) and itraconazole, and assessment of the impact of gene polymorphism

Introduction

Suraxavir Marboxil (GP681) is a prodrug metabolized to GP1707D07, which inhibits influenza viral replication by targeting cap-dependent endonuclease through a single oral dose. This study assesses the in vivo drug-drug interaction (DDI) potential between GP681 (including its major metabolite GP1707D07, a substrate of CYP3A4) and itraconazole in healthy Chinese subjects, along with the safety profiles during co-administration. Additionally, it evaluates the impact of CYP1A2, CYP2C19, and CYP3A4 gene polymorphisms on GP1707D07 metabolism.

Methods

The study enrolled twelve healthy adult subjects to receive the treatments consisting of GP681 monotherapy and GP681-itraconazole co-administration in a fixed-sequence. Single nucleotide polymorphisms (SNPs) in CYP gene loci were also analyzed.

Results

Co-administration of itraconazole increased the GP1707D07 AUC0- ∞ by about 2.5 folds and Cmax by about 1.4 folds compared with GP681 administered alone. Differences in system exposure were more pronounced during the terminal elimination phase than the early stage of GP1707D07 metabolism. No significant increase in adverse events was observed during co-administration. Using random forest algorithm, we estimated effects of cytochrome P450 enzymes followed the order of CYP 3A4 > CYP 1A2 > CYP 2C19. We also hypothesized CYP 3A4 rs4646437 A>G, CYP 3A4 rs2246709 G>A, and CYP 2C19 rs12768009 A>G to be mutations that enhanced enzyme activity, while CYP1A2 rs762551 C>A weakened it.

Discussion

The pharmacokinetic changes of GP1707D07 during itraconazole co-administration are insufficient to warrant clinical action. Random forest algorithm enhances the understanding of pharmacogenetic variants involved in GP1707D07 metabolism and may serve as a potent tool for assessing gene polymorphism data in small clinical samples.

Clinical Trial Registration

clinicaltrials.gov, identifier NCT05789342.

Trends in drug-drug interactions for new drug clinical trials in China over the past 10 years (2013-2022)

The number of drug-drug interaction (DDI) clinical trials in China has increased rapidly in recent years. The aim of this study was to summarize and analyze DDI clinical trials in China over the past 10 years. We conducted a cross-sectional study of DDI clinical trials registered in the Chinese Center for Drug Evaluation (CDE) from September 6, 2013 to December 31, 2022. All related registration information disclosed on the CDE website were summarized and analyzed. Although the number of DDI clinical trials conducted before 2017 was relatively low, it increased markedly after 2017. The average duration of DDI clinical trials was 85.83 ± 100.99 days from 2013 to 2019 and 107.16 ± 98.57 days from 2020 to 2022. The duration of rifampicin use was 5-19 days, and the investigational drug was administered after 5-14 days of rifampicin use. Itraconazole was administered for 4-17 days, and the investigational drug was administered after 3-10 days of itraconazole use. Clinical trials of drug-drug interactions have recently increased due to the development of new drugs and the updated policies regulating drug registration and marketing. Although the designs of clinical trials comply with the new guidelines, the duration of the administration of interacting drugs still varies widely. Optimizing protocol designs can shorten the implementation period of clinical trials and reduce the costs of drug marketing.

Docetaxel, cyclophosphamide, and epirubicin: application of PBPK modeling to gain new insights for drug-drug interactions

The new adjuvant chemotherapy of docetaxel, epirubicin, and cyclophosphamide has been recommended for treating breast cancer. It is necessary to investigate the potential drug-drug Interactions (DDIs) since they have a narrow therapeutic window in which slight differences in exposure might result in significant differences in treatment efficacy and tolerability. To guide clinical rational drug use, this study aimed to evaluate the DDI potentials of docetaxel, cyclophosphamide, and epirubicin in cancer patients using physiologically based pharmacokinetic (PBPK) models. The GastroPlus™ was used to develop the PBPK models, which were refined and validated with observed data. The established PBPK models accurately described the pharmacokinetics (PKs) of three drugs in cancer patients, and the predicted-to-observed ratios of all the PK parameters met the acceptance criterion. The PBPK model predicted no significant changes in plasma concentrations of these drugs during co-administration, which was consistent with the observed clinical phenomenon. Besides, the verified PBPK models were then used to predict the effect of other Cytochrome P450 3A4 (CYP3A4) inhibitors/inducers on these drug exposures. In the DDI simulation, strong CYP3A4 modulators changed the exposure of three drugs by 0.71-1.61 fold. Therefore, patients receiving these drugs in combination with strong CYP3A4 inhibitors should be monitored regularly to prevent adverse reactions. Furthermore, co-administration of docetaxel, cyclophosphamide, or epirubicin with strong CYP3A4 inducers should be avoided. In conclusion, the PBPK models can be used to further investigate the DDI potential of each drug and to develop dosage recommendations for concurrent usage by additional perpetrators or victims.

The Potentially Significant Role of CYP3A-Mediated Oxidative Metabolism of Dabigatran Etexilate and Its Intermediate Metabolites in Drug-Drug Interaction Assessments Using Microdose Dabigatran Etexilate

Dabigatran etexilate (DABE), a double ester prodrug of dabigatran, is a probe substrate of intestinal P-glycoprotein (P-gp) commonly used in clinical drug-drug interaction (DDI) studies. When compared with its therapeutic dose at 150 mg, microdose DABE (375 µg) showed approximately 2-fold higher in DDI magnitudes with CYP3A/P-gp inhibitors. In this study, we conducted several in vitro metabolism studies to demonstrate that DABE, at a theoretical gut concentration after microdosing, significantly underwent NADPH-dependent oxidation (~40%-50%) in parallel to carboxylesterase-mediated hydrolysis in human intestinal microsomes. Furthermore, NADPH-dependent metabolism of its intermediate monoester, BIBR0951, was also observed in both human intestinal and liver microsomes, accounting for 100% and 50% of total metabolism, respectively. Metabolite profiling using high resolution mass spectrometry confirmed the presence of several novel oxidative metabolites of DABE and of BIBR0951 in the NADPH-fortified incubations. CYP3A was identified as the major enzyme catalyzing the oxidation of both compounds. The metabolism of DABE and BIBR0951 was well described by Michaelis-Menten kinetics, with Km ranging 1-3 µM, significantly below the expected concentrations following the therapeutic dose of DABE. Overall, the present results suggested that CYP3A played a significant role in the presystemic metabolism of DABE and BIBR0951 following microdose DABE administration, thus attributing partly to the apparent overestimation in the DDI magnitude observed with the CYP3A/P-gp inhibitors. Therefore, DABE at the microdose, unlike the therapeutic dose, would likely be a less predictive tool and should be considered as a clinical dual substrate for P-gp and CYP3A when assessing potential P-gp-mediated impacts by dual CYP3A/P-gp inhibitors. SIGNIFICANT STATEMENT: This is the first study demonstrating a potentially significant role of cytochrome P450-mediated metabolism of the prodrug DABE following a microdose but not a therapeutic dose. This additional pathway, coupled with its susceptibility to P-glycoprotein (P-gp), may make DABE a clinical dual substrate for both P-gp and CYP3A at a microdose. The study also highlights the need for better characterization of the pharmacokinetics and metabolism of a clinical drug-drug interaction probe substrate over the intended study dose range for proper result interpretations.

Repurposing antifungal drugs for cancer therapy

BACKGROUND

Repurposing antifungal drugs in cancer therapy has attracted unprecedented attention in both preclinical and clinical research due to specific advantages, such as safety, high-cost effectiveness and time savings compared with cancer drug discovery. The surprising and encouraging efficacy of antifungal drugs in cancer therapy, mechanistically, is attributed to the overlapping targets or molecular pathways between fungal and cancer pathogenesis. Advancements in omics, informatics and analytical technology have led to the discovery of increasing "off-site" targets from antifungal drugs involved in cancerogenesis, such as smoothened (D477G) inhibition from itraconazole in basal cell carcinoma.

AIM OF REVIEW

This review illustrates several antifungal drugs repurposed for cancer therapy and reveals the underlying mechanism based on their original target and "off-site" target. Furthermore, the challenges and perspectives for the future development and clinical applications of antifungal drugs for cancer therapy are also discussed, providing a refresh understanding of drug repurposing.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review may provide a basic understanding of repurposed antifungal drugs for clinical cancer management, thereby helping antifungal drugs broaden new indications and promote clinical translation.

Clinical assessment of gepotidacin (GSK2140944) as a victim and perpetrator of drug-drug interactions via CYP3A metabolism and transporters

Gepotidacin is a novel triazaacenaphthylene antibiotic in phase III development. Based on nonclinical in vitro characterization of gepotidacin metabolism, two phase I studies were conducted in healthy participants to investigate clinical drug-drug interactions (DDIs). We assessed gepotidacin as a DDI victim with a potent cytochrome P450 (CYP) 3A4/P-glycoprotein (P-gp) inhibitor (itraconazole), potent CYP3A4 inducer (rifampicin), and nonspecific organic cation transporter (OCT)/multidrug and toxic extrusion transporter (MATE) renal transport inhibitor (cimetidine) via single doses of gepotidacin before and after co-administration with multiple doses of the modulator drugs. Gepotidacin DDI perpetrator potential for P-gp inhibition (digoxin) and CYP3A4 inhibition (midazolam) was evaluated via single doses of the two-drug cocktail without and with gepotidacin. The DDI magnitudes were interpreted based on area under the concentration-time curve (AUC). A weak DDI (AUC increase 48%-50%) was observed for gepotidacin co-administered with itraconazole. A clinically significant decrease in gepotidacin plasma AUC (52%) was observed with rifampicin coadministration, indicating a moderate DDI. There was no DDI for gepotidacin with cimetidine; a unique biomarker approach showed increased serum creatinine (24%), decreased renal clearance of creatinine (21%), and N1-methylnicotinamide (39%), which confirmed extensive MATE inhibition and partial OCT2 inhibition. Gepotidacin was not a P-gp DDI perpetrator, although the maximum plasma concentration of digoxin increased (53%) and is potentially clinically relevant given its narrow therapeutic index. Gepotidacin demonstrated weak CYP3A4 inhibition with midazolam (<2-fold AUC increase). There were no new safety-risk profile findings. These results will inform the safe and efficacious clinical use of gepotidacin when co-administered with other drugs.

Prediction of pyrotinib exposure based on physiologically-based pharmacokinetic model and endogenous biomarker

Pyrotinib, a novel irreversible epidermal growth factor receptor dual tyrosine kinase inhibitor, is mainly (about 90%) eliminated through cytochrome P450 (CYP) 3A mediated metabolism in vivo. Meanwhile, genotype is a key factor affecting pyrotinib clearance and 4β-hydroxycholesterol is an endogenous biomarker of CYP3A activity that can indirectly reflect the possible pyrotinib exposure. Thus, it is necessary to evaluate the clinical drug-drug interactions (DDI) between CYP3A perpetrators and pyrotinib, understand potential exposure in specific populations including liver impairment and geriatric populations, and explore the possible relationships among pyrotinib exposure, genotypes and endogenous biomarker. Physiologically-based pharmacokinetic (PBPK) model can be used to replace prospective DDI studies and evaluate external and internal factors that may influence system exposure. Herein, a basic PBPK model was firstly developed to evaluate the potential risk of pyrotinib coadministration with strong inhibitor and guide the clinical trial design. Subsequently, the mechanistic PBPK model was established and used to quantitatively estimate the potential DDI risk for other CYP3A modulators, understand the potential exposure of specific populations, including liver impairment and geriatric populations. Meanwhile, the possible relationships among pyrotinib exposure, genotypes and endogenous biomarker were explored. With the help of PBPK model, the DDI clinical trial of pyrotinib coadministration with strong inhibitor has been successfully completed, some DDI clinical trials may be waived based on the predicted results and clinical trials in specific populations can be reasonably designed. Moreover, the mutant genotypes of CYP3A4*18A and CYP3A5*3 were likely to have a limited influence on pyrotinib clearance, and the genotype-independent linear correlation coefficient between endogenous biomarker and system exposure was larger than 0.6. Therefore, based on the reliable predicted results and the linear correlations between pyrotinib exposure and endogenous biomarker, dosage adjustment of pyrotinib can be designed for clinical practice.

Prediction of Drug-Drug Interaction Potential of Tegoprazan Using Physiologically Based Pharmacokinetic Modeling and Simulation

This study aimed to develop a physiologically based pharmacokinetic (PBPK) model of tegoprazan and to predict the drug-drug interaction (DDI) potential between tegoprazan and cytochrome P450 (CYP) 3A4 perpetrators. The PBPK model of tegoprazan was developed using SimCYP Simulator^® and verified by comparing the model-predicted pharmacokinetics (PKs) of tegoprazan with the observed data from phase 1 clinical studies, including DDI studies. DDIs between tegoprazan and three CYP3A4 perpetrators were predicted by simulating the difference in tegoprazan exposure with and without perpetrators, after multiple dosing for a clinically used dose range. The final PBPK model adequately predicted the biphasic distribution profiles of tegoprazan and DDI between tegoprazan and clarithromycin. All ratios of the predicted-to-observed PK parameters were between 0.5 and 2.0. In DDI simulation, systemic exposure to tegoprazan was expected to increase about threefold when co-administered with the maximum recommended dose of clarithromycin or ketoconazole. Meanwhile, tegoprazan exposure was expected to decrease to ~30% when rifampicin was co-administered. Based on the simulation by the PBPK model, it is suggested that the DDI potential be considered when tegoprazan is used with CYP3A4 perpetrator, as the acid suppression effect of tegoprazan is known to be associated with systemic exposure.

How Science Is Driving Regulatory Guidances

This chapter provides regulatory perspectives on how to translate in vitro drug metabolism findings into in vivo drug-drug interaction (DDI) predictions and how this affects the decision of conducting in vivo DDI evaluation. The chapter delineates rationale and analyses that have supported the recommendations in the U.S. Food and Drug Administration (FDA) DDI guidances in terms of in vitro-in vivo extrapolation of cytochrome P450 (CYP) inhibition-mediated DDI potential for investigational new drugs and their metabolites as substrates or inhibitors. The chapter also describes the framework and considerations to assess UDP-glucuronosyltransferase (UGT) inhibition-mediated DDI potential for drugs as substrates or inhibitors. The limitations of decision criteria and further improvements needed are also discussed. Case examples are provided throughout the chapter to illustrate how decision criteria have been utilized to evaluate in vivo DDI potential from in vitro data.

Prediction of the drug-drug interaction potential of the α1-acid glycoprotein bound, CYP3A4/CYP2C9 metabolized oncology drug, erdafitinib

Erdafitinib is a potent oral pan‐fibroblast growth factor receptor inhibitor being developed as oncology drug for patients with alterations in the fibroblast growth factor receptor pathway. Erdafitinib binds preferentially to α1‐acid glycoprotein (AGP) and is primarily metabolized by cytochrome P450 (CYP) 2C9 and 3A4. This article describes a physiologically based pharmacokinetic (PBPK) model for erdafitinib to assess the drug–drug interaction (DDI) potential of CYP3A4 and CYP2C9 inhibitors and CYP3A4/CYP2C9 inducers on erdafitinib pharmacokinetics (PK) in patients with cancer exhibiting higher AGP levels and in populations with different CYP2C9 genotypes. Erdafitinib's DDI potential as a perpetrator for transporter inhibition and for time‐dependent inhibition and/or induction of CYP3A was also evaluated. The PBPK model incorporated input parameters from various in vitro and clinical PK studies, and the model was verified using a clinical DDI study with itraconazole and fluconazole. Erdafitinib clearance in the PBPK model consisted of multiple pathways (CYP2C9/3A4, renal, intestinal; additional hepatic clearance), making the compound less susceptible to DDIs. In poor‐metabolizing CYP2C9 populations carrying the CYP2C9*3/*3 genotype, simulations shown clinically relevant increase in erdafitinib plasma concentrations. Simulated luminal and enterocyte concentration showed potential risk of P‐glycoprotein inhibition with erdafitinib in the first 5 h after dosing, and simulations showed this interaction can be avoided by staggering erdafitinib and digoxin dosing. Other than a simulated ~ 60% exposure reduction with strong CYP3A/2C inducers such as rifampicin, other DDI liabilities were minimal and considered not clinically relevant.

Pediatric Drug-Drug Interaction Evaluation: Drug, Patient Population, and Methodological Considerations

Hospitalized pediatric patients and those with complex or chronic conditions treated on an outpatient basis are commonly prescribed multiple drugs, resulting in increased risk for drug-drug interactions (DDIs). Although dedicated DDI evaluations are routinely performed in healthy adult volunteers during drug development, they are rarely performed in pediatric patients because of ethical, logistical, and methodological challenges. In the absence of pediatric DDI evaluations, adult DDI data are often extrapolated to pediatric patients. However, the magnitude of a DDI in pediatric patients may differ from adults because of age-dependent physiological changes that can impact drug disposition or response and because of other factors related to the drug (eg, dose, formulation) and the patient population (eg, disease state, obesity). Therefore, the DDI magnitude needs to be assessed in children separately from adults, although a lack of clinical DDI data in pediatric populations makes this evaluation challenging. As a result, pediatric DDI assessment relies on the predictive performance of the pharmacometric approaches used, such as population and physiologically based pharmacokinetic modeling. Therefore, careful consideration needs to be given to adequately account for the age-dependent physiological changes in these models to build high confidence for such untested DDI scenarios. This review article summarizes the key considerations related to the drug, patient population, and methodology, and how they can impact DDI evaluation in the pediatric population.

Assessment of Clinical Drug-Drug Interactions of Elagolix, a Gonadotropin-Releasing Hormone Receptor Antagonist

Elagolix is an oral gonadotropin-releasing hormone receptor antagonist indicated for the management of endometriosis-associated pain and in combination with estradiol/norethindrone acetate indicated for the management of heavy menstrual bleeding associated with uterine leiomyomas (fibroids) in premenopausal women. Elagolix coadministered with estradiol/norethindrone acetate is in late-stage development for the management of heavy menstrual bleeding associated with uterine fibroids. Based on the in vitro profile of elagolix metabolism and disposition, 9 drug-drug interaction (DDI) studies evaluating the victim and perpetrator characteristics of elagolix were conducted in 144 healthy volunteers. As a victim of cytochrome P450 (CYPs) and transporter-mediated DDIs, elagolix area under the curve (AUC) increased by ∼2-fold following coadministration with ketoconazole and by ∼5- and ∼2-fold with single and multiple doses of rifampin, respectively. As a perpetrator, elagolix decreased midazolam AUC (90% confidence interval) by 54% (50%-59%) and increased digoxin AUC by 32% (23%-41%). Elagolix decreased rosuvastatin AUC by 40% (29%-50%). No clinically significant changes in exposure on coadministration with sertraline or fluconazole occurred. A elagolix 150-mg once-daily regimen should be limited to 6 months with strong CYP3A inhibitors and rifampin because of the potential increase in bone mineral density loss, as described in the drug label. A 200-mg twice-daily regimen is recommended for no more than 1 month with strong CYP3A inhibitors and not recommended with rifampin. Elagolix is contraindicated with strong organic anion transporter polypeptide B1 inhibitors (eg, cyclosporine and gemfibrozil). Consider increasing the doses of midazolam and rosuvastatin when coadministered with elagolix, and individualize therapy based on patient response. Clinical monitoring is recommended for P-glycoprotein substrates with a narrow therapeutic window (eg, digoxin). Dose adjustments are not required for sertraline, fluconazole, bupropion (or any CYP2B6 substrate), or elagolix when coadministered.

Evaluation of iberdomide and cytochrome p450 drug-drug interaction potential in vitro and in a phase 1 study in healthy subjects

PURPOSE

Iberdomide is a cereblon E3 ligase modulator capable of redirecting the protein degradation machinery of the cell towards the elimination of target proteins potentially driving therapeutic effects. In vitro studies demonstrated that iberdomide predominantly undergoes oxidative metabolism mediated by cytochrome P450 (CYP) 3A4/5 but had no notable inhibition or induction of CYP enzymes. Consequently, the potential of iberdomide as a victim of drug-drug interactions (DDI) was evaluated in a clinical study with healthy subjects.

METHODS

A total of 33 males and 5 females with 19 subjects per part were enrolled. Part 1 evaluated the pharmacokinetics (PK) of iberdomide alone (0.6 mg) and when administered with the CYP3A and P-gp inhibitor itraconazole (200 mg twice daily on day 1 and 200 once daily on days 2 through 9). Part 2 evaluated the PK of iberdomide alone (0.6 mg) and with CYP3A4 inducer rifampin (600 mg QD days 1 through 13). Plasma concentrations of iberdomide and the active metabolite M12 were determined by validated liquid chromatography-tandem mass spectrometry assay.

RESULTS

Coadministration of iberdomide with itraconazole increased iberdomide peak plasma concentration (C_max) 17% and area under the concentration curve (AUC) approximately 2.4-fold relative to administration of iberdomide alone. The C_max and AUC of iberdomide were reduced by approximately 70% and 82%, respectively, when iberdomide was administered with rifampin compared with iberdomide administered alone. Exploratory assessment of metabolite M12 concentrations demonstrated that CYP3A is responsible for M12 formation.

CONCLUSIONS

Caution should be taken when coadministering iberdomide with strong CYP3A inhibitors. Coadministration of iberdomide with strong CYP3A inducers is not advised.

CLINICAL TRIAL REGISTRATION

Clinical trial identification number is NCT02820935 and was registered in July 2016.

Physiologically based pharmacokinetic modeling to assess metabolic drug-drug interaction risks and inform the drug label for fedratinib

Purpose

Fedratinib (INREBIC^®), a Janus kinase 2 inhibitor, is approved in the United States to treat patients with myelofibrosis. Fedratinib is not only a substrate of cytochrome P450 (CYP) enzymes, but also exhibits complex auto-inhibition, time-dependent inhibition, or mixed inhibition/induction of CYP enzymes including CYP3A. Therefore, a mechanistic modeling approach was used to characterize pharmacokinetic (PK) properties and assess drug–drug interaction (DDI) potentials for fedratinib under clinical scenarios.

Methods

The physiologically based pharmacokinetic (PBPK) model of fedratinib was constructed in Simcyp^® (V17R1) by integrating available in vitro and in vivo information and was further parameterized and validated by using clinical PK data.

Results

The validated PBPK model was applied to predict DDIs between fedratinib and CYP modulators or substrates. The model simulations indicated that the fedratinib-as-victim DDI extent in terms of geometric mean area under curve (AUC) at steady state is about twofold or 1.2-fold when strong or moderate CYP3A4 inhibitors, respectively, are co-administered with repeated doses of fedratinib. In addition, the PBPK model successfully captured the perpetrator DDI effect of fedratinib on a sensitive CY3A4 substrate midazolam and predicted minor effects of fedratinib on CYP2C8/9 substrates.

Conclusions

The PBPK-DDI model of fedratinib facilitated drug development by identifying DDI potential, optimizing clinical study designs, supporting waivers for clinical studies, and informing drug label claims. Fedratinib dose should be reduced to 200 mg QD when a strong CYP3A4 inhibitor is co-administered and then re-escalated to 400 mg in a stepwise manner as tolerated after the strong CYP3A4 inhibitor is discontinued.

Electronic supplementary material

The online version of this article (10.1007/s00280-020-04131-y) contains supplementary material, which is available to authorized users.

An Adaptive Physiologically Based Pharmacokinetic-Driven Design to Investigate the Effect of Itraconazole and Rifampicin on the Pharmacokinetics of Molibresib (GSK525762) in Healthy Female Volunteers

Molibresib (GSK525762), an orally bioavailable small molecule with 2 major equipotent active metabolites, is being developed for the treatment of cancers. Molibresib is a substrate of cytochrome P450 (CYP) 3A4 and P‐glycoprotein (P‐gp). To enable administering safe doses of molibresib to healthy volunteers, this 2‐part randomized, open‐label, crossover drug‐drug interaction trial was conducted as an adaptive design study using physiologically based pharmacokinetic (PBPK) modeling and simulation to predict the lowest doses of molibresib that could be safely administered alone (10 mg) or with itraconazole and rifampicin (strong inhibitors and inducers of CYP3A and P‐gp, respectively). PBPK simulation guided the molibresib dose (5 mg) to be administered along with itraconazole in part 1. Itraconazole increased total exposure (AUC) of molibresib by 4.15‐fold with a 66% increase in C_max, whereas the total AUC and C_max for the 2 major active metabolites of molibresib decreased by about 70% and 87%, respectively. A second PBPK simulation was conducted with part 1 data to also include the active metabolites to update the recommendation for the molibresib dose (20 mg) with rifampicin. With rifampicin, the AUC and C_max of molibresib decreased by approximately 91% and 80%, respectively, whereas the AUC of the 2 active metabolites decreased to a lesser extent (8%), with a 2‐fold increase in C_max. The results of this study confirmed the in vitro data that molibresib is a substrate for CYP3A4. The adaptive design, including Simcyp simulations, allowed evaluation of 2 drug interactions of an oncology drug in a single trial, thus minimizing time and exposures administered to healthy subjects.

Antifungal therapeutic drug monitoring: focus on drugs without a clear recommendation

BACKGROUND

The goal of therapeutic drug monitoring (TDM) is to determine the appropriate exposure of difficult-to-manage medications to optimize the clinical outcomes in patients in various clinical situations. Concerning antifungal treatment, and knowing that this procedure is expensive and time-consuming, TDM is particularly recommended for certain systemic antifungals: i.e., agents with a well-defined exposure-response relationship and unpredictable pharmacokinetic profile or narrow therapeutic index. Little evidence supports the routine use of TDM for polyenes (amphotericin B), echinocandins, fluconazole or new azoles such as isavuconazole, despite the fact that a better understanding of antifungal exposure may lead to a better response.

AIMS

The aim of this work is to review published pharmacokinetic/pharmacodynamic data on systemically administered antifungals, focusing on those for which monitoring is not routinely recommended by experts.

SOURCES

A MEDLINE search of the literature in English was performed introducing the following search terms: amphotericin B, fluconazole, itraconazole, voriconazole, posaconazole, triazoles, caspofungin, micafungin, anidulafungin, echinocandins, pharmacokinetics, pharmacodynamics, and therapeutic drug monitoring. Review articles and guidelines were also screened.

CONTENT

This review collects different pharmacokinetic/pharmacodynamic aspects of systemic antifungals and summarizes recent threshold values for clinical outcomes and adverse events. Although for polyenes, echinocandins, fluconazole and isavuconazole extensive clinical validation is still required for a clear threshold and a routine monitoring recommendation, particular points such as liposome structure or complex pathophysiological conditions affecting final exposure are discussed. For the rest, their better-defined exposure-response/toxicity relationships allow access to useful threshold values and to justify routine monitoring. Additionally, clinical data are needed to better define thresholds that can minimize the development of antifungal resistance.

IMPLICATIONS

General TDM for all systemic antifungals is not recommended; however, this approach may help to establish an adequate antifungal exposure for a favourable response, prevention of toxicity or development of resistance in special clinical circumstances.

An Open-Label Study to Assess the Effect of Itraconazole and Rifampin on Parsaclisib Pharmacokinetics When Administered Orally in Healthy Participants

Parsaclisib, a selective, potent phosphatidylinositol 3‐kinase delta inhibitor being developed for the treatment of cancer and autoimmune diseases, is primarily metabolized by cytochrome P450 (CYP) 3A4. This study assessed the pharmacokinetics (PK) and safety of parsaclisib alone or combined with itraconazole (potent CYP3A inhibitor) or rifampin (potent CYP3A4 inducer) in healthy participants. In this open‐label, fixed‐sequence study, cohort 1 received oral parsaclisib 10 mg once daily on days 1 and 8 and oral itraconazole 200 mg once daily on days 4‐11; cohort 2 received oral parsaclisib 20 mg once daily on days 1 and 11 and oral rifampin 600 mg once daily on days 4‐12. Parsaclisib plasma concentration was tested and PK parameters calculated by noncompartmental analysis. Geometric mean ratios (GMRs) and 2‐sided 90% confidence intervals (CIs) were estimated by 2‐factor analysis of variance. Thirty‐six healthy participants were enrolled (18 per cohort). Parsaclisib maximum plasma drug concentration (C_max) and area under the concentration‐time curve extrapolated to infinity (AUC_0‐∞) were increased by 21% and 107% with concomitant itraconazole versus parsaclisib alone (GMR, 1.21; 90%CI, 1.14‐1.29; and 2.07; 90%CI, 1.97‐2.17, respectively). Parsaclisib C_max and AUC were reduced by 43% and 77%, respectively, with concomitant rifampin versus parsaclisib alone (GMR, 0.57; 90%CI, 0.53‐0.60; and 0.23; 90%CI, 0.21‐0.24, respectively). Headache was the most common adverse event, reported by 13.9% of participants (all in cohort 2). Single‐dose parsaclisib alone or combined with itraconazole or rifampin appeared safe and well tolerated in healthy participants. Parsaclisib dose adjustment may be necessary with concomitant administration of strong CYP3A4 inhibitors or inducers.

Drug Interactions for Low-Dose Inhaled Nemiralisib: A Case Study Integrating Modeling, In Vitro, and Clinical Investigations

In vitro data for low-dose inhaled phosphoinositide 3-kinase delta inhibitor nemiralisib revealed that it was a substrate and a potent metabolism-dependent inhibitor of cytochrome P450 (P450) 3A4 and a P-glycoprotein (P-gp) substrate. An integrated in silico, in vitro, and clinical approach including a clinical drug interaction study as well as a bespoke physiologically based pharmacokinetic (PBPK) model was used to assess the drug-drug interaction (DDI) risk. Inhaled nemiralisib (100 µg, single dose) was coadministered with itraconazole, a potent P4503A4/P-gp inhibitor, following 200 mg daily administrations for 10 days in 20 male healthy subjects. Systemic exposure to nemiralisib (AUC0-inf) increased by 2.01-fold versus nemiralisib alone. To extrapolate the clinical data to other P4503A4 inhibitors, an inhaled PBPK model was developed using Simcyp software. Retrospective simulation of the victim risk showed good agreement between simulated and observed data (AUC0-inf ratio 2.3 vs. 2.01, respectively). Prospective DDI simulations predicted a weak but manageable drug interaction when nemiralisib was coadministered with other P4503A4 inhibitors, such as the macrolides clarithromycin and erythromycin (simulated AUC0-inf ratio of 1.7), both common comedications in the intended patient populations. PBPK and static mechanistic models were also used to predict a negligible perpetrator DDI effect for nemiralisib on other P4503A4 substrates, including midazolam (a sensitive probe substrate of P4503A4) and theophylline (a narrow therapeutic index drug and another common comedication). In summary, an integrated in silico, in vitro, and clinical approach including an inhalation PBPK model has successfully discharged any potential patient DDI risks in future nemiralisib clinical trials. SIGNIFICANCE STATEMENT: This paper describes the integration of in silico, in vitro, and clinical data to successfully discharge potential drug-drug interaction risks for a low-dose inhaled drug. This work featured assessment of victim and perpetrator risks of drug transporters and cytochrome P450 enzymes, utilizing empirical and mechanistic approaches combined with clinical data (drug interaction and human absorption, metabolism, and pharmacokinetics) and physiologically based pharmacokinetic modeling approaches to facilitate bespoke risk assessment in target patient populations.

Predicting Clinical Effects of CYP3A4 Modulators on Abemaciclib and Active Metabolites Exposure Using Physiologically Based Pharmacokinetic Modeling

Abemaciclib, a selective inhibitor of cyclin‐dependent kinases 4 and 6, is metabolized mainly by cytochrome P450 (CYP)3A4. Clinical studies were performed to assess the impact of strong inhibitor (clarithromycin) and inducer (rifampin) on the exposure of abemaciclib and active metabolites. A physiologically based pharmacokinetic (PBPK) model incorporating the metabolites was developed to predict the effect of other strong and moderate CYP3A4 inhibitors and inducers. Clarithromycin increased the area under the plasma concentration‐time curve (AUC) of abemaciclib and potency‐adjusted unbound active species 3.4‐fold and 2.5‐fold, respectively. Rifampin decreased corresponding exposures 95% and 77%, respectively. These changes influenced the fraction metabolized via CYP3A4 in the model. An absolute bioavailability study informed the hepatic and gastric availability. In vitro data and a human radiolabel study determined the fraction and rate of formation of the active metabolites as well as absorption‐related parameters. The predicted AUC ratios of potency‐adjusted unbound active species with rifampin and clarithromycin were within 0.7‐ and 1.25‐fold of those observed. The PBPK model predicted 3.78‐ and 7.15‐fold increases in the AUC of the potency‐adjusted unbound active species with strong CYP3A4 inhibitors itraconazole and ketoconazole, respectively; and 1.62‐ and 2.37‐fold increases with the concomitant use of moderate CYP3A4 inhibitors verapamil and diltiazem, respectively. The model predicted modafinil, bosentan, and efavirenz would decrease the AUC of the potency‐adjusted unbound active species by 29%, 42%, and 52%, respectively. The current PBPK model, which considers changes in unbound potency‐adjusted active species, can be used to inform dosing recommendations when abemaciclib is coadministered with CYP3A4 perpetrators.

Estimation of an Appropriate Dose of Trazodone for Pediatric Insomnia and the Potential for a Trazodone-Atomoxetine Interaction

There is a paucity of clinical trials for the treatment of pediatric insomnia. This study was designed to predict the doses of trazodone to guide dosing in a clinical trial for pediatric insomnia using physiologically-based pharmacokinetic (PBPK) modeling. Data on the pharmacokinetics of trazodone in children are currently lacking. The interaction potential between trazodone and atomoxetine was also predicted. Doses predicted in the following age groups, with exposures corresponding to adult dosages of 30, 75, and 150 mg once a day (q.d.), respectively, were: (i) 2- to 6-year-old group, doses of 0.35, 0.8, and 1.6 mg/kg q.d.; (ii) >6- to 12-year-old group, doses of 0.4, 1.0, and 1.9 mg/kg q.d.; (iii) >12- to 17-year-old group, doses of 0.4, 1.1, and 2.1 mg/kg q.d. An interaction between trazodone and atomoxetine was predicted to be unlikely. Clinical trials based on the aforementioned predicted dosing are currently in progress, and pharmacokinetic data obtained will enable further refinement of the PBPK models.

An increase in side-group hydrophobicity largely improves the potency of ritonavir-like inhibitors of CYP3A4

Identification of structural determinants required for potent inhibition of drug-metabolizing cytochrome P450 3A4 (CYP3A4) could help develop safer drugs and more effective pharmacoenhancers. We utilize a rational inhibitor design to decipher structure-activity relationships in analogues of ritonavir, a highly potent CYP3A4 inhibitor marketed as pharmacoenhancer. Analysis of compounds with the R₁ side-group as phenyl or naphthalene and R₂ as indole or naphthalene in different stereo configuration showed that (i) analogues with the R₂-naphthalene tend to bind tighter and inhibit CYP3A4 more potently than the R₂-phenyl/indole containing counterparts; (ii) stereochemistry becomes a more important contributing factor, as the bulky side-groups limit the ability to optimize protein-ligand interactions; (iii) the relationship between the R₁/R₂ configuration and preferential binding to CYP3A4 is complex and depends on the side-group functionality/interplay and backbone spacing; and (iv) three inhibitors, 5a-b and 7d, were superior to ritonavir (IC₅₀ of 0.055-0.085 μM vs. 0.130 μM, respectively).

Recommendations for the Design of Clinical Drug-Drug Interaction Studies With Itraconazole Using a Mechanistic Physiologically-Based Pharmacokinetic Model

Regulatory agencies currently recommend itraconazole (ITZ) as a strong cytochrome P450 3A (CYP3A) inhibitor for clinical drug–drug interaction (DDI) studies. This work by an International Consortium for Innovation and Quality in Pharmaceutical Development working group (WG) is to develop and verify a mechanistic ITZ physiologically‐based pharmacokinetic model and provide recommendations for optimal DDI study design based on model simulations. To support model development and verification, in vitro and clinical PK data for ITZ and its metabolites were collected from WG member companies. The model predictions of ITZ DDIs with seven different CYP3A substrates were within the guest criteria for 92% of area under the concentration‐time curve ratios and 95% of maximum plasma concentration ratios, thus verifying the model for DDI predictions. The verified model was used to simulate various clinical DDI study scenarios considering formulation, duration of dosing, dose regimen, and food status to recommend the optimal design for maximal inhibitory effect by ITZ.

Uptake and metabolism of clarithromycin and sulfadiazine in lettuce

Antibiotics are introduced into agricultural fields by the application of manure or biosolids, or via irrigation using reclaimed wastewater. Antibiotics can enter the terrestrial food chains through plant uptake, which forms an alternative pathway for human exposure to antibiotics. However, previous studies mainly focused on detecting residues of the parent antibiotics, while ignoring the identification of antibiotics transformation products in plants. Here, we evaluated the uptake and metabolism of clarithromycin (CLA) and sulfadiazine (SDZ) in lettuce under controlled hydroponic conditions. The antibiotics and their metabolites were identified by ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QToF-MS/MS) and ultra-performance liquid chromatograph Micromass triple quadrupole mass spectrometry (UPLC-QqQ-MS/MS). The structure of CLA, SDZ and N-acetylated SDZ were confirmed with synthesized standards, verifying the reliability of the identification method. Eight metabolites of CLA and two metabolites of SDZ were detected in both the leaves and roots of lettuce. The metabolites of CLA included phases I and II transformation products, while only phase II metabolites of SDZ were observed in lettuce. The proportion of CLA metabolites was estimated to be greater than 70%, indicating that most of the CLA was metabolized in plant tissues. The proportion of SDZ metabolites was lower than 12% in the leaves and 10% in the roots. Some metabolites might have the ability to increase or acquire antibacterial activity. Therefore, in addition to the parent compounds, metabolites of antibiotics in edible vegetables are also worthy of study for risk assessment and to determine the consequences of long-term exposure.

Pharmacokinetic/pharmacodynamic drug-drug interactions of avatrombopag when coadministered with dual or selective CYP2C9 and CYP3A interacting drugs

AIMS

Avatrombopag, a thrombopoietin receptor agonist, is a substrate of cytochrome P450 (CYP) 2C9 and CYP3A. We assessed three drug-drug interactions of avatrombopag as a victim with dual or selective CYP2C9/3A inhibitors and inducers.

METHODS

This was a three-part, open-label study. Forty-eight healthy subjects received single 20 mg doses of avatrombopag alone or with one of 3 CYP2C9/3A inhibitors or inducers: fluconazole 400 mg once daily for 16 days, itraconazole 200 mg twice daily on Day 1 and 200 mg once daily on Days 2-16, or rifampicin 600 mg once daily for 16 days. Pharmacokinetics, pharmacodynamics (platelet count) and safety of avatrombopag were evaluated.

RESULTS

Coadministration of a single 20-mg dose of avatrombopag with fluconazole at steady-state resulted in 2.16-fold increase of AUC of avatrombopag, prolonged terminal elimination phase half-life (from 19.7 h to 39.9 h) and led to a clinically significant increase in maximum platelet count (1.66-fold). Itraconazole had a mild increase on both avatrombopag pharmacokinetics and pharmacodynamics compared to fluconazole. Coadministration of rifampicin caused a 0.5-fold decrease in AUC and shortened terminal elimination phase half-life (from 20.3 h to 9.84 h), but has no impact on maximum platelet count. Coadministration with interacting drugs was found to be generally safe and well-tolerated.

CONCLUSIONS

The results from coadministration of fluconazole or itraconazole suggest that CYP2C9 plays a more predominant role in metabolic clearance of avatrombopag than CYP3A. To achieve comparable platelet count increases when avatrombopag is coadministered with CYP3A and CYP2C9 inhibitors, an adjustment in the dose or duration of treatment is recommended, while coadministration with strong inducers is not currently recommended.

Functional characterization of a unique cytochrome P450 in Toxoplasma gondii

The basic metabolic cytochrome P450 (CYP) proteins are essential for the biotransformation of sterols and xenobiotics. By contrast, the Toxoplasma gondii genome contains only one CYP gene, and the role of this enzyme in the physiology and biochemistry of apicomplexan parasites is unknown. Because it is a potential resistance gene, identifying the functionality of P450 in T. gondii is particularly important. Knocking out Tg-P450 had no significant effect on T. gondii survival, but mice infected with parasites overexpressing Tg-P450 exhibited significantly enhanced pathogenicity. Enzyme activity analyses demonstrated that this protein has mammalian CYP2B and CYP3A enzymatic activity. In addition, T. gondii lacking the P450 gene exhibited reduced resistance to quinine, mefloquine and clarithromycin compared with parasites overexpressing Tg-P450. These results suggest that P450 functions in T. gondii metabolism and detoxification is involved in vitally important processes in parasitic organisms, making this enzyme a potential drug target.

Pharmacokinetic Drug Interactions of Apatinib With Rifampin and Itraconazole

Apatinib is a small-molecule tyrosine kinase inhibitor that has been approved for the treatment of patients with advanced-stage gastric cancer or gastroesophageal junction cancer who have progressed or recurred after at least 2 kinds of systemic chemotherapy. In vitro data indicate that cytochrome P450 (CYP) 3A4 is the primary CYP isoenzyme involved in the metabolism of apatinib. Pharmacokinetic drug-drug interactions of apatinib and (1) a CYP3A4 inducer (rifampin) or (2) a CYP3A inhibitor (itraconazole) were clinically evaluated in healthy volunteers. Compared with the single administration of apatinib, its coadministration with rifampin resulted in a 5.6-fold plasma clearance (CL/F) and 83% decrease in plasma AUC_0-t of apatinib. By contrast, coadministration with itraconazole reduced the CL/F of apatinib by 40% and increased its AUC_0-t by 75%. In summary, a strong CYP3A4 inducer (rifampin) had a strong effect (>5-fold) on the clinical pharmacokinetics of apatinib, whereas a strong CYP3A inhibitor (itraconazole 100 mg once a day) had a weak effect (1.25- to 2-fold). Whether these effects are of clinical significance needs further research and information about the exposure-safety and exposure-efficacy relationship of apatinib.

Development of a Physiologically Based Pharmacokinetic Model for Itraconazole Pharmacokinetics and Drug-Drug Interaction Prediction

BACKGROUND AND OBJECTIVES

Physiologically based pharmacokinetic (PBPK) modeling for itraconazole has been challenging due to highly variable in vitro d ata used for 'bottom-up' model building. Under-prediction of pharmacokinetics and drug-drug interactions (DDIs) following multiple doses of itraconazole has limited the use of PBPK model simulation to aid an itraconazole clinical DDI study design. The aim of this work is to develop an itraconazole PBPK model predominantly using a 'top-down' approach to enable a more accurate pharmacokinetic and DDI prediction.

METHODS

An itraconazole PBPK model describing itraconazole and hydroxyl-itraconazole (OH-ITZ) was constructed in Simcyp(®). The key parameters that govern the pharmacokinetic profile, including non-linear clearance (i.e., maximum rate of reaction [V max] and the Michaelis-Menten constant [K m]) and volume of distribution for both itraconazole and OH-ITZ, were redefined by leveraging existing in vivo data. Model verification was performed by comparing the simulated itraconazole and OH-ITZ pharmacokinetic profiles with the observed clinical data. Finally, the model was used to simulate clinical DDIs between itraconazole and midazolam.

RESULTS

The developed PBPK model well-described the pharmacokinetics of itraconazole and OH-ITZ, and particularly captured their accumulation after repeated doses of itraconazole. This was verified with the observed data from 29 clinical studies where itraconazole solution or capsule was given as a single or multiple dose. The predicted DDI between itraconazole and midazolam was within 1.25-fold of the observed data for seven of ten studies and within 1.5-fold for nine of ten studies.

CONCLUSION

The improvement of the itraconazole PBPK model increased our confidence in using PBPK model simulations to optimize clinical itraconazole DDI study design.

Evaluation of Cytochrome P450 3A4-Mediated Drug-Drug Interaction Potential for Cobimetinib Using Physiologically Based Pharmacokinetic Modeling and Simulation

BACKGROUND AND OBJECTIVES

Cobimetinib is eliminated mainly through cytochrome P450 (CYP) 3A4-mediated hepatic metabolism in humans. A clinical drug-drug interaction (DDI) study with the potent CYP3A4 inhibitor itraconazole resulted in an approximately sevenfold increase in cobimetinib exposure. The DDI risk for cobimetinib with other CYP3A4 inhibitors and inducers needs to be assessed in order to provide dosing instructions.

METHODS

A physiologically based pharmacokinetic (PBPK) model was developed for cobimetinib using in vitro data. It was then optimized and verified using clinical pharmacokinetic data and itraconazole-cobimetinib DDI data. The contribution of CYP3A4 to the clearance of cobimetinib in humans was confirmed using sensitivity analysis in a retrospective simulation of itraconazole-cobimetinib DDI data. The verified PBPK model was then used to predict the effect of other CYP3A4 inhibitors and inducers on cobimetinib pharmacokinetics.

RESULTS

The PBPK model described cobimetinib pharmacokinetic profiles after both intravenous and oral administration of cobimetinib well and accurately simulated the itraconazole-cobimetinib DDI. Sensitivity analysis suggested that CYP3A4 contributes ~78 % of the total clearance of cobimetinib. The PBPK model predicted no change in cobimetinib exposure (area under the plasma concentration-time curve, AUC) with the weak CYP3A inhibitor fluvoxamine and a three to fourfold increase with the moderate CYP3A inhibitors, erythromycin and diltiazem. Similarly, cobimetinib exposure in the presence of strong (rifampicin) and moderate (efavirenz) CYP3A inducers was predicted to decrease by 83 and 72 %, respectively.

CONCLUSION

This study demonstrates the value of using PBPK simulation to assess the clinical DDI risk inorder to provide dosing instructions with other CYP3A4 perpetrators.

Assessment of effect of CYP3A inhibition, CYP induction, OATP1B inhibition, and high-fat meal on pharmacokinetics of the JAK1 inhibitor upadacitinib

AIMS

Upadacitinib (ABT-494) is a selective Janus kinase 1 inhibitor being developed for treatment of auto-immune inflammatory disorders. This work evaluated effects of high-fat meal, cytochrome P450 (CYP) 3A inhibition, CYP induction, and organic anion transporting polypeptide (OATP) 1B inhibition on upadacitinib pharmacokinetics.

METHODS

Two Phase 1 evaluations were conducted, each in 12 healthy subjects. In Study 1, using a randomized, two-sequence crossover design, a 3 mg dose of upadacitinib (immediate-release capsules) was administered alone under fasting conditions, after high-fat meal, or on Day 4 of a 6-day regimen of 400 mg once-daily ketoconazole. In Study 2, a 12 mg upadacitinib dose was administered alone, with the first, and with the eighth dose of a 9-day regimen of rifampin 600 mg once daily. Upadacitinib plasma concentrations were characterized.

RESULTS

Administration of upadacitinib immediate-release capsules after a high-fat meal decreased upadacitinib C_max by 23% and had no impact on upadacitinib AUC relative to the fasting conditions. Ketoconazole (strong CYP3A inhibitor) increased upadacitinib C_max and AUC by 70% and 75%, respectively. Multiple doses of rifampin (broad CYP inducer) decreased upadacitinib C_max and AUC by approximately 50% and 60%, respectively. A single dose of rifampin (also an OATP1B inhibitor) had no effect on upadacitinib AUC. Upadacitinib was well tolerated when co-administered with ketoconazole, rifampin, or after a high-fat meal.

CONCLUSIONS

Strong CYP3A inhibition and broad CYP induction result in a weak and moderate effect, respectively, on upadacitinib exposures. OATP1B inhibition and administration of upadacitinib immediate-release formulation with food does not impact upadacitinib exposure.

A physiologically based pharmacokinetic modeling approach to predict drug-drug interactions between domperidone and inhibitors of CYP3A4

Domperidone is a dopamine receptor antagonist and a substrate of CYP3A4, hence there is a potential for CYP3A inhibition-based drug-drug interactions (DDI). A physiologically based pharmacokinetic model was developed to describe DDIs between domperidone and three different inhibitors of CYP3A4. Simcyp V13.1 was used to simulate human domperidone pharmacokinetics and DDIs. Inputs included domperidone chemical and physical properties (LogP, pKa, etc.), in vitro human liver microsomal data and pharmacokinetic parameters from single-dose intravenous clinical studies in healthy participants. The simulated mean maximum domperidone plasma concentration and AUC after single- and multiple-oral doses under diverse conditions were within 1.1-1.4 fold of the observed values. The simulated intestinal availability, hepatic availability and the fraction absorbed were 0.45 ± 0.14, 0.31 ± 0.10 and 0.89 ± 0.11, respectively, and comparable to observed in vivo values. The simulated ratios of AUC and C(max) in the presence of ketoconazole, erythromycin or itraconazole to baseline were consistent with the observed ratios. Simulated ketoconazole, erythromycin, itraconazole and C(max,ss) and AUC(ss) were within 1.5-fold of the observed values.

Ibrutinib Dosing Strategies Based on Interaction Potential of CYP3A4 Perpetrators Using Physiologically Based Pharmacokinetic Modeling

Based on ibrutinib pharmacokinetics and potential sensitivity towards CYP3A4-mediated drug-drug interactions (DDIs), a physiologically based pharmacokinetic approach was developed to mechanistically describe DDI with various CYP3A4 perpetrators in healthy men under fasting conditions. These models were verified using clinical data for ketoconazole (strong CYP3A4 inhibitor) and used to prospectively predict and confirm the inducing effect of rifampin (strong CYP3A4 inducer); DDIs with mild (fluvoxamine, azithromycin) and moderate inhibitors (diltiazem, voriconazole, clarithromycin, itraconazole, erythromycin), and moderate (efavirenz) and strong CYP3A4 inducers (carbamazepine), were also predicted. Ketoconazole increased ibrutinib area under the curve (AUC) by 24-fold, while rifampin decreased ibrutinib AUC by 10-fold; coadministration of ibrutinib with strong inhibitors or inducers should be avoided. The ibrutinib dose should be reduced to 140 mg (quarter of maximal prescribed dose) when coadministered with moderate CYP3A4 inhibitors so that exposures remain within observed ranges at therapeutic doses. Thus, dose recommendations for CYP3A4 perpetrator use during ibrutinib treatment were developed and approved for labeling.

Use of Human Plasma Samples to Identify Circulating Drug Metabolites that Inhibit Cytochrome P450 Enzymes

Drug interactions elicited through inhibition of cytochrome P450 (P450) enzymes are important in pharmacotherapy. Recently, greater attention has been focused on not only parent drugs inhibiting P450 enzymes but also on possible inhibition of these enzymes by circulating metabolites. In this report, an ex vivo method whereby the potential for circulating metabolites to be inhibitors of P450 enzymes is described. To test this method, seven drugs and their known plasma metabolites were added to control human plasma at concentrations previously reported to occur in humans after administration of the parent drug. A volume of plasma for each drug based on the known inhibitory potency and time-averaged concentration of the parent drug was extracted and fractionated by high-pressure liquid chromatography-mass spectrometry, and the fractions were tested for inhibition of six human P450 enzyme activities (CYP1A2, CYP2C8, CYP2C9, CYP2C19, CYP2D6, and CYP3A4). Observation of inhibition in fractions that correspond to the retention times of metabolites indicates that the metabolite has the potential to contribute to P450 inhibition in vivo. Using this approach, norfluoxetine, hydroxyitraconazole, desmethyldiltiazem, desacetyldiltiazem, desethylamiodarone, hydroxybupropion, erythro-dihydrobupropion, and threo-dihydrobupropion were identified as circulating metabolites that inhibit P450 activities at a similar or greater extent as the parent drug. A decision tree is presented outlining how this method can be used to determine when a deeper investigation of the P450 inhibition properties of a drug metabolite is warranted.

No Increased Risk of Ketoconazole Toxicity in Drug-Drug Interaction Studies

In July 2013 the U.S. Food and Drug Administration (FDA) released a safety announcement regarding the use of ketoconazole and its adverse drug reactions. The FDA report advised against the use ketoconazole tablets as a first-line treatment for any fungal infections because of the risk of potentially serious drug-drug interactions and liver and adrenal gland complications. The European Medicines Agency (EMA) also proposed to limit the use of oral ketoconazole in fungal infections because of the same risk of harmful effects and interactions. In addition, the FDA also advised against the use of oral ketoconazole in drug interaction studies, in which it has been extensively used as an index inhibitor of drug metabolism. The aim of this investigation was to evaluate the risks of ketoconazole-induced hepatotoxicity described by the FDA and EMA in published drug interaction studies with ketoconazole and compare these data with the toxicity reported for ketoconazole when used as antifungal treatment. In the drug interaction studies (2355 participants; healthy volunteers and patients; median treatment duration, 6 days), only 40 participants were reported to have increased liver transaminase activity (1.7%), and no deaths were reported or associated with ketoconazole. In studies investigating ketoconazole treatment, patients were treated for 276 days (median), and 5.6% of patients had elevated liver enzyme activity. Because of the short treatment period in drug interaction studies the risk of drug-induced hepatic injury is considered very low. As such, we recommend that ketoconazole remain a safe CYP3A index inhibitor for use in drug interaction studies with healthy volunteers.

Evaluation of Ketoconazole and Its Alternative Clinical CYP3A4/5 Inhibitors as Inhibitors of Drug Transporters: The In Vitro Effects of Ketoconazole, Ritonavir, Clarithromycin, and Itraconazole on 13 Clinically-Relevant Drug Transporters

Ketoconazole is a potent CYP3A4/5 inhibitor and, until recently, recommended by the Food and Drug Administration (FDA) and the European Medicines Agency as a strong CYP3A4/5 inhibitor in clinical drug-drug interaction (DDI) studies. Ketoconazole sporadically causes liver injury or adrenal insufficiency. Because of this, the FDA and European Medicines Agency recommended suspension of ketoconazole use in DDI studies in 2013. The FDA specifically recommended use of clarithromycin or itraconazole as alternative strong CYP3A4/5 inhibitors in clinical DDI studies, but many investigators have also used ritonavir as an alternative. Although the effects of these clinical CYP3A4/5 inhibitors on other CYPs are largely established, reports on the effects on the broad range of drug transporter activities are sparse. In this study, the inhibitory effects of ketoconazole, clarithromycin, ritonavir, and itraconazole (and its CYP3A4-inhibitory metabolites, hydroxy-, keto-, and N-desalkyl itraconazole) toward 13 drug transporters (OATP1B1, OATP1B3, OAT1, OAT3, OCT1, OCT2, MATE1, MATE2-K, P-gp, BCRP, MRP2, MRP3, and BSEP) were systematically assessed in transporter-expressing HEK-293 cell lines or membrane vesicles. In vitro findings were translated into clinical context with the basic static model approaches outlined by the FDA in its 2012 draft guidance on DDIs. The results indicate that, like ketoconazole, the alternative clinical CYP3A4/5 inhibitors ritonavir, clarithromycin, and itraconazole each have unique transporter inhibition profiles. None of the alternatives to ketoconazole provided a clean inhibition profile toward the 13 drug transporters evaluated. The results provide guidance for the selection of clinical CYP3A4/5 inhibitors when transporters are potentially involved in a victim drug's pharmacokinetics.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Evacetrapib: in vitro and clinical disposition, metabolism, excretion, and assessment of drug interaction potential with strong CYP3A and CYP2C8 inhibitors

Evacetrapib is an investigational cholesteryl ester transfer protein inhibitor (CETPi) for reduction of risk of major adverse cardiovascular events in patients with high-risk vascular disease. Understanding evacetrapib disposition, metabolism, and the potential for drug-drug interactions (DDI) may help guide prescribing recommendations. In vitro, evacetrapib metabolism was investigated with a panel of human recombinant cytochromes P450 (CYP). The disposition, metabolism, and excretion of evacetrapib following a single 100-mg oral dose of (14)C-evacetrapib were determined in healthy subjects, and the pharmacokinetics of evacetrapib were evaluated in the presence of strong CYP3A or CYP2C8 inhibitors. In vitro, CYP3A was responsible for about 90% of evacetrapib's CYP-associated clearance, while CYP2C8 accounted for about 10%. In the clinical disposition study, only evacetrapib and two minor metabolites circulated in plasma. Evacetrapib metabolism was extensive. A mean of 93.1% and 2.30% of the dose was excreted in feces and urine, respectively. In clinical DDI studies, the ratios of geometric least squares means for evacetrapib with/without the CYP3A inhibitor ketoconazole were 2.37 for area under the curve (AUC)(0-∞) and 1.94 for C max. There was no significant difference in evacetrapib AUC(0-τ) or C max with/without the CYP2C8 inhibitor gemfibrozil, with ratios of 0.996 and 1.02, respectively. Although in vitro results indicated that both CYP3A and CYP2C8 metabolized evacetrapib, clinical studies confirmed that evacetrapib is primarily metabolized by CYP3A. However, given the modest increase in evacetrapib exposure and robust clinical safety profile to date, there is a low likelihood of clinically relevant DDI with concomitant use of strong CYP3A or CYP2C8 inhibitors.

The enhancement of cardiac toxicity by concomitant administration of Berberine and macrolides

As is well-known, hERG plays an essential role in phase III repolarization of cardiac action potentials. Blocking of hERG channels can lead to LQTS. Inhibition of the metabolism of CYPs activities may elevate plasma levels, to further increase accumulation of drug on cardiac. The elevated serum levels may however elicit unexpected toxicities. Therefore, the inhibition tests of hERG and CYP are central to the preclinical studies because they may lead to severe cardiac toxicity. Berberine is widely used as an antibacterial agent and often combined with macrolides to treat gastropathy. Our objective was to assess cardiac toxicity during the combined use of Berberine with macrolides. (1) Azithromycin reduced hERG currents by accelerated channel inactivation. (2) The combination of Berberine with Azithromycin reduced hERG currents, producing an inhibitive effect stronger than use of a single drug alone, due to the high binding affinity for the onset of inactivation. (3) When cells were perfused concomitantly with Berberine and Clarithromycin, they showed a stronger inhibitive effect on hERG currents by decreasing the time constant for the onset of inactivation. (4) The combined administration of Berberine with Clarithromycin had a powerful inhibitive effect on CYP3A activities than use of a single drug alone. Collectively, these results demonstrated that concomitant use of Berberine with macrolides may require close monitoring because of potential drug toxicities, especially cardiac toxicity.

Best practices for the use of itraconazole as a replacement for ketoconazole in drug-drug interaction studies

Ketoconazole has been widely used as a strong cytochrome P450 (CYP) 3A (CYP3A) inhibitor in drug-drug interaction (DDI) studies. However, the US Food and Drug Administration has recommended limiting the use of ketoconazole to cases in which no alternative therapies exist, and the European Medicines Agency has recommended the suspension of its marketing authorizations because of the potential for serious safety concerns. In this review, the Innovation and Quality in Pharmaceutical Development's Clinical Pharmacology Leadership Group (CPLG) provides a compelling rationale for the use of itraconazole as a replacement for ketoconazole in clinical DDI studies and provides recommendations on the best practices for the use of itraconazole in such studies. Various factors considered in the recommendations include the choice of itraconazole dosage form, administration in the fasted or fed state, the dose and duration of itraconazole administration, the timing of substrate and itraconazole coadministration, and measurement of itraconazole and metabolite plasma concentrations, among others. The CPLG's recommendations are based on careful review of available literature and internal industry experiences.

Organ Impairment-Drug-Drug Interaction Database: A Tool for Evaluating the Impact of Renal or Hepatic Impairment and Pharmacologic Inhibition on the Systemic Exposure of Drugs

The organ impairment and drug–drug interaction (OI-DDI) database is the first rigorously assembled database of pharmacokinetic drug exposure data from publicly available renal and hepatic impairment studies presented together with the maximum change in drug exposure from drug interaction inhibition studies. The database was used to conduct a systematic comparison of the effect of renal/hepatic impairment and pharmacologic inhibition on drug exposure. Additional applications are feasible with the public availability of this database.

Ritonavir is the best alternative to ketoconazole as an index inhibitor of cytochrome P450-3A in drug-drug interaction studies

AIMS

The regulatory prohibition of ketoconazole as a CYP3A index inhibitor in drug-drug interaction (DDI) studies has compelled consideration of alternative inhibitors.

METHODS

The biomedical literature was searched to identify DDI studies in which oral midazolam (MDZ) was the victim, and the inhibitory perpetrator was either ketoconazole, itraconazole, clarithromycin, or ritonavir. The ratios (RAUC ) of total area under the curve (AUC) for MDZ with inhibitor divided by MDZ AUC in the control condition were aggregated across individual studies for each inhibitor.

RESULTS

Mean (± SE) RAUC values were: ketoconazole (15 studies, 131 subjects), 11.5 (±1.2); itraconazole (five studies, 48 subjects), 7.3 (±1.0); clarithromycin (five studies, 73 subjects), 6.5 (±10.9); and ritonavir (13 studies, 159 subjects), 14.5 (±2.0). Differences among inhibitors were significant (F = 5.31, P < 0.005). RAUC values were not significantly related to inhibitor dosage or to duration of inhibitor pre-exposure prior to administration of MDZ.

CONCLUSIONS

Ritonavir produces CYP3A inhibition equivalent to or greater than ketoconazole, and is the best index CYP3A inhibitor alternative to ketoconazole. Cobicistat closely resembles ritonavir in structure and function, and can also be considered. Itraconazole and clarithromycin are not suitable alternatives since they do not produce inhibition comparable with ketoconazole or ritonavir, and have other significant disadvantages as well.