Physiologically Based Pharmacokinetic Model of Itraconazole and Two of Its Metabolites to Improve the Predictions and the Mechanistic Understanding of CYP3A4 Drug-Drug Interactions

Utility of physiologically based pharmacokinetic modeling in predicting and characterizing clinical drug interactions

Physiologically based pharmacokinetic (PBPK) modeling is a mechanistic dynamic modeling approach that can be used to predict or retrospectively describe changes in drug exposure due to drug-drug interactions (DDIs). With advancements in commercially available PBPK software, PBPK DDI modeling has become a mainstream approach from early drug discovery through to late-stage drug development and is often used to support regulatory packages for new drug applications. This Minireview will briefly describe the approaches to predicting DDI using PBPK and static modeling approaches, the basic model structures and features inherent to PBPK DDI models, and key examples where PBPK DDI models have been used to describe complex DDI mechanisms. Future directions aimed at using PBPK models to characterize transporter-mediated DDI, predict DDI in special populations, and assess the DDI potential of protein therapeutics will be discussed. A summary of the 209 PBPK DDI examples published to date in 2023 will be provided. Overall, current data and trends suggest a continued role for PBPK models in the characterization and prediction of DDI for therapeutic molecules. SIGNIFICANCE STATEMENT: Physiologically based pharmacokinetic (PBPK) models have been a key tool in the characterization of various pharmacokinetic phenomena, including drug-drug interactions. This Minireview will highlight recent advancements and publications around physiologically based pharmacokinetic drug-drug interaction modeling, an important area of drug discovery and development research in light of the increasing prevalence of polypharmacology in clinical settings.

Effects of Itraconazole on Pharmacokinetics of Mitragynine and 7-Hydroxymitragynine in Healthy Volunteers

CYP3A4-mediated metabolic conversion of mitragynine to 7-hydroxymitragynine (7OH) has been demonstrated in human liver microsomes, and in rodents. Pharmacokinetics (PK) of mitragynine and 7OH in humans is still limited. We aimed to examine the pharmacokinetics of mitragynine and the formation of 7OH in healthy volunteers. To elucidate involvement of CYP3A4 in 7OH formation, inhibition by itraconazole was implemented. Two study periods with PK study of mitragynine alone in period 1, followed by period 2 including itraconazole pretreatment was conducted. Freshly prepared kratom tea consisting of 23.6 mg of mitragynine was given to participants in both study periods. Serial blood samplings were performed for 72 hours, and analyzed using a validated LCMS in multiple reaction monitoring mode. The median Cmax for mitragynine of 159.12 ± 8.68 ng/mL was attained in 0.84 h. While median Cmax for 7OH of 12.81 ± 3.39 ng/mL was observed at 1.77 h. In period 1, Cmax and AUC 0-inf of 7OH accounted for 9% and 20 %, respectively, of those parameters for mitragynine. The geometric mean ratio of AUC0-72 for 7OH/mitragynine (metabolic ratio, MR) was 13.25 ± 1.07. Co-administration of itraconazole 200 mg per day orally for 4 days (period 2) decreased 7OH exposure by 56% for Cmax and 43% for AUC0-72 after a single oral dose of kratom tea. While the Cmax of mitragynine increased by 1.5 folds without a significant change in Tmax. The geometric mean metabolic ratio was 3.30 ± 1.23 (period 2), indicating the attenuation for the formation of 7OH by the pretreatment with itraconazole. This suggested the CYP3A4-mediated formation of 7OH from mitragynine in healthy volunteers. This study provides the first evidence of metabolic conversion of mitragynine to 7OH in humans.

A New Version of the Tissue Composition-Based Model for Improving the Mechanism-Based Prediction of Volume of Distribution at Steady-State for Neutral Drugs

In-vitro models are available in the literature for predicting the volume of distribution at steady-state (Vdss) of drugs. The mechanistic model refers to the tissue composition-based model (TCM), which includes important factors that govern Vdss such as drug physiochemistry and physiological data. The recognized TCM published by Rodgers and Rowland (TCM-RR) and a subsequent adjustment made by Simulations Plus Inc. (TCM-SP) have been shown to be generally less accurate with neutral compared to ionized drugs. Therefore, improving these models for neutral drugs becomes necessary. The objective of this study was to propose a new TCM for improving the prediction of Vdss for neutral drugs. The new TCM included two modifications of the published models (i) accentuate the effect of the blood-to-plasma ratio (BPR) that should cover permeated molecules across the biomembranes, which is lacking in these models for neutral compounds, and (ii) use a different approach to estimate the binding in tissues. The new TCM was validated with a large dataset of 202 commercial and proprietary compounds including preclinical and clinical data. All scenario datasets were predicted more accurately with the TCM-New, whereas all statistical parameters indicate that the TCM-New showed significant improvements in terms of accuracy over the TCM-RR and TCM-SP. Predictions of Vdss were frequently more accurate for the TCM-new with 83% within twofold error versus only 50% for the TCM-RR. And more than 95% of the predictions were within threefold error and patient interindividual differences can be predicted with the TCM-New, greatly exceeding the accuracy of the published models. Overall, the new TCM incorporating BPR significantly improved the Vdss predictions in animals and humans for neutral drugs, and, hence, has the potential to better support the drug discovery and facilitate the first-in-human predictions.

Effects of the CYP3A inhibitors, voriconazole, itraconazole, and fluconazole on the pharmacokinetics of osimertinib in rats

Background

Osimertinib, as third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), is the first-line treatment approved to treat advanced T790M mutation-positive tumors. Triazole antifungals are therapeutic drugs for cancer patients to reduce the risk of opportunistic fungal infections. Our objective was to investigate whether three triazole antifungals (voriconazole, itraconazole, and fluconazole) could change the pharmacokinetics of osimertinib in rats.

Methods

The adult male Sprague-Dawley rats were randomly divided into four groups (n = 6): control (0.3% CMC-Na), and voriconazole (20 mg/kg), itraconazole (20 mg/kg), or fluconazole (20 mg/kg) combined with osimertinib (10 mg/kg) group. Tail vein blood samples were collected into heparin tubes at various time points within 0-48 h after osimertinib administration. Osimrtinib's plasma concentration was detected using HPLC-MS/MS system equipped with a Waters XBridge C18 column, with the mobile phase consisting of acetonitrile and 0.2% formic acid water at a flow rate of 0.5 mL/min.

Results

Co-administration with voriconazole or fluconazole increased the Cmax of osimertinib by 58.04% and 53.45%, respectively; the AUC0-t increased by 62.56% and 100.98%, respectively. However, when co-administered with itraconazole, the Cmax and AUC0-t of osimertinib only increased by 13.91% and 34.80%, respectively.

Conclusions

Our results revealed that the pharmacokinetics of osimertinib were significantly changed by voriconazole and fluconazole in rats, whereas it was slightly affected by itraconazole. This work will contribute to a more comprehensive understanding of the pharmacokinetic properties of osimertinib when co-administered with triazole antifungals.

Advances in anti-invasive fungal drug delivery systems

Currently, the first-line drugs for invasive fungal infections (IFI), such as amphotericin B, fluconazole and itraconazole, have drawbacks including poor water solubility, low bioavailability, and severe side effects. Using drug delivery systems is a promising strategy to improve the efficacy and safety of traditional antifungal therapy. Synthetic and biomimetic carriers have greatly facilitated the development of targeted delivery systems for antifungal drugs. Synthetic carrier drug delivery systems, such as liposomes, nanoparticles, polymer micelles, and microspheres, can improve the physicochemical properties of antifungal drugs, prolong their circulation time, enhance targeting capabilities, and reduce toxic side effects. Cell membrane biomimetic drug delivery systems, such as macrophage or red blood cell membrane-coated drug delivery systems, retain the membrane structure of somatic cells and confer various biological functions and specific targeting abilities to the loaded antifungal drugs, exhibiting better biocompatibility and lower toxicity. This article reviews the development of antifungal drug delivery systems and their application in the treatment of IFI, and also discusses the prospects of novel biomimetic carriers in antifungal drug delivery.

Differential effects of ketoconazole, fluconazole, and itraconazole on the pharmacokinetics of pyrotinib in vitro and in vivo

It has been reported that drug-drug interactions (DDIs) can affect the pharmacokinetics and pharmacodynamics of various oral drugs. To better understand the effects of azole antifungal drugs (ketoconazole, fluconazole, and itraconazole) on pyrotinib’s pharmacokinetics, DDIs between pyrotinib and three azoles were studied with Sprague-Dawley (SD) rat liver microsomes in vitro. Additionally, in vivo pyrotinib metabolic experiment was also performed. Twenty-four male SD rats were randomly divided into four groups: the ketoconazole (40 mg/kg), fluconazole (40 mg/kg), itraconazole (40 mg/kg), and the control group. UPLC-MS/MS was used for the determination of Pyrotinib’s plasma concentration in rats. In vitro experiments showed that IC₅₀ values of ketoconazole, fluconazole and itraconazole were 0.06, 11.55, and 0.27 μM, respectively, indicating that these drugs might reduce the clearance rate of pyrotinib at different degrees. In rat studies, coadministration of pyrotinib with ketoconazole or fluconazole could dramatically increase the C_max and AUC_(0-t) values and decrease the clearance rate of pyrotinib, especially for ketoconazole. However, coadministration with itraconazole had no impact on the pharmacokinetic characters of pyrotinib. These data indicated that ketoconazole and fluconazole could significantly decrease the metabolism of pyrotinib both in vitro and in vivo. More attentions should be paid when pyrotinib is combined with azole antifungal drugs in clinic although further investigation is still required in future.

Does the choice of applied physiologically‐based pharmacokinetics platform matter? A case study on simvastatin disposition and drug–drug interaction

Physiologically‐based pharmacokinetic (PBPK) models have an important role in drug discovery/development and decision making in regulatory submissions. This is facilitated by predefined PBPK platforms with user‐friendly graphical interface, such as Simcyp and PK‐Sim. However, evaluations of platform differences and the potential implications for disposition‐related applications are still lacking. The aim of this study was to assess how PBPK model development, input parameters, and model output are affected by the selection of PBPK platform. This is exemplified via the establishment of simvastatin PBPK models (workflow, final models, and output) in PK‐Sim and Simcyp as representatives of established whole‐body PBPK platforms. The major finding was that the choice of PBPK platform influenced the model development strategy and the final model input parameters, however, the predictive performance of the simvastatin models was still comparable between the platforms. The main differences between the structure and implementation of Simcyp and PK‐Sim were found in the absorption and distribution models. Both platforms predicted equally well the observed simvastatin (lactone and acid) pharmacokinetics (20–80 mg), BCRP and OATP1B1 drug–gene interactions (DGIs), and drug–drug interactions (DDIs) when co‐administered with CYP3A4 and OATP1B1 inhibitors/inducers. This study illustrates that in‐depth knowledge of established PBPK platforms is needed to enable an assessment of the consequences of PBPK platform selection. Specifically, this work provides insights on software differences and potential implications when bridging PBPK knowledge between Simcyp and PK‐Sim users. Finally, it provides a simvastatin model implemented in both platforms for risk assessment of metabolism‐ and transporter‐mediated DGIs and DDIs.

Influence of Gender, Body Mass Index, and Age on the Pharmacokinetics of Itraconazole in Healthy Subjects: Non-Compartmental Versus Compartmental Analysis

Itraconazole is a triazole antifungal agent with highly variable pharmacokinetics, with not yet fully identified factors as the source of this variability. Our study aimed to examine the influence of body mass index, gender, and age on the first dose pharmacokinetics of itraconazole in healthy subjects, using pharmacokinetic modeling, non-compartmental versus compartmental ones. A total of 114 itraconazole and hydroxy-itraconazole sets of plasma concentrations of healthy subjects of both genders, determined using a validated liquid chromatographic method with mass spectrometric detection (LC-MS), were obtained for pharmacokinetic analyses performed by the computer program Kinetica 5®. Genetic polymorphism in CYP3A4, CYP3A5, CYP1A1, CYP2C9, and CYP2C19 was analyzed using PCR-based methods. Multiple linear regression analysis indicated that gender had a significant effect on AUC as the most important pharmacokinetics endpoint, whereas body mass index and age did not show such an influence. Therefore, further analysis considered gender and indicated that both geometric mean values of itraconazole and hydroxy-itraconazole plasma concentrations in men were prominently higher than those in women. A significant reduction of the geometric mean values of Cmax and AUC and increment of Vd in females compared with males were obtained. Analyzed genotypes and gender differences in drug pharmacokinetics could not be related. Non-compartmental and one-compartmental models complemented each other, whereas the application of the two-compartmental model showed a significant correlation with the analysis of one compartment. They indicated a significant influence of gender on itraconazole pharmacokinetics after administration of the single oral dose of the drug, given under fed conditions. Women were less exposed to itraconazole and hydroxy-itraconazole than men due to poorer absorption of itraconazole, its more intense pre-systemic metabolism, and higher distribution of both drug and its metabolite.

Antifungal Drugs TDM: Trends and Update

PURPOSE

The increasing burden of invasive fungal infections results in growing challenges to antifungal (AF) therapeutic drug monitoring (TDM). This review aims to provide an overview of recent advances in AF TDM.

METHODS

We conducted a PubMed search for articles during 2016-2020 using "TDM" or "pharmacokinetics" or "drug-drug-interaction" with "antifungal," consolidated for each AF. Selection was limited to English language articles with human data on drug exposure.

RESULTS

More than 1000 articles matched the search terms. We selected 566 publications. The latest findings tend to confirm previous observations in real-life clinical settings. The pharmacokinetic variability related to special populations is not specific but must be considered. AF benefit-to-risk ratio, drug-drug interaction (DDI) profiles, and minimal inhibitory concentrations for pathogens must be known to manage at-risk situations and patients. Itraconazole has replaced ketoconazole in healthy volunteers DDI studies. Physiologically based pharmacokinetic modeling is widely used to assess metabolic azole DDI. AF prophylactic use was studied more for Aspergillus spp. and Mucorales in oncohematology and solid organ transplantation than for Candida (already studied). Emergence of central nervous system infection and severe infections in immunocompetent individuals both merit special attention. TDM is more challenging for azoles than amphotericin B and echinocandins. Fewer TDM requirements exist for fluconazole and isavuconazole (ISZ); however, ISZ is frequently used in clinical situations in which TDM is recommended. Voriconazole remains the most challenging of the AF, with toxicity limiting high-dose treatments. Moreover, alternative treatments (posaconazole tablets, ISZ) are now available.

CONCLUSIONS

TDM seems to be crucial for curative and/or long-term maintenance treatment in highly variable patients. TDM poses fewer cost issues than the drugs themselves or subsequent treatment issues. The integration of clinical pharmacology into multidisciplinary management is now increasingly seen as a part of patient care.

Reviewing Data Integrated for PBPK Model Development to Predict Metabolic Drug-Drug Interactions: Shifting Perspectives and Emerging Trends

Physiologically-based pharmacokinetics (PBPK) modeling is a robust tool that supports drug development and the pharmaceutical industry and regulatory authorities. Implementation of predictive systems in the clinics is more than ever a reality, resulting in a surge of interest for PBPK models by clinicians. We aimed to establish a repository of available PBPK models developed to date to predict drug-drug interactions (DDIs) in the different therapeutic areas by integrating intrinsic and extrinsic factors such as genetic polymorphisms of the cytochromes or environmental clues. This work includes peer-reviewed publications and models developed in the literature from October 2017 to January 2021. Information about the software, type of model, size, and population model was extracted for each article. In general, modeling was mainly done for DDI prediction via Simcyp^® software and Full PBPK. Overall, the necessary physiological and physio-pathological parameters, such as weight, BMI, liver or kidney function, relative to the drug absorption, distribution, metabolism, and elimination and to the population studied for model construction was publicly available. Of the 46 articles, 32 sensibly predicted DDI potentials, but only 23% integrated the genetic aspect to the developed models. Marked differences in concentration time profiles and maximum plasma concentration could be explained by the significant precision of the input parameters such as Tissue: plasma partition coefficients, protein abundance, or Ki values. In conclusion, the models show a good correlation between the predicted and observed plasma concentration values. These correlations are all the more pronounced as the model is rich in data representative of the population and the molecule in question. PBPK for DDI prediction is a promising approach in clinical, and harmonization of clearance prediction may be helped by a consensus on selecting the best data to use for PBPK model development.

Artemisinin Cocrystals for Bioavailability Enhancement. Part 2: In Vivo Bioavailability and Physiologically Based Pharmacokinetic Modeling

We report the evaluation and prediction of the pharmacokinetic (PK) performance of artemisinin (ART) cocrystal formulations, that is, 1:1 artemisinin/orcinol (ART-ORC) and 2:1 artemisinin/resorcinol (ART²-RES), using in vivo murine animal and physiologically based pharmacokinetic (PBPK) models. The efficacy of the ART cocrystal formulations along with the parent drug ART was tested in mice infected with Plasmodium berghei. When given at the same dose, the ART cocrystal formulation showed a significant reduction in parasitaemia at day 4 after infection compared to ART alone. PK parameters including C_max (maximum plasma concentration), T_max (time to C_max), and AUC (area under the curve) were obtained by determining drug concentrations in the plasma using liquid chromatography-high-resolution mass spectrometry (LC-HRMS), showing enhanced ART levels after dosage with the cocrystal formulations. The dose-response tests revealed that a significantly lower dose of the ART cocrystals in the formulation was required to achieve a similar therapeutic effect as ART alone. A PBPK model was developed using a PBPK mouse simulator to accurately predict the in vivo behavior of the cocrystal formulations by combining in vitro dissolution profiles with the properties of the parent drug ART. The study illustrated that information from classical in vitro and in vivo experimental investigations of the parent drug of ART formulations can be coupled with PBPK modeling to predict the PK parameters of an ART cocrystal formulation in an efficient manner. Therefore, the proposed modeling strategy could be used to establish in vitro and in vivo correlations for different cocrystals intended to improve dissolution properties and to support clinical candidate selection, contributing to the assessment of cocrystal developability and formulation development.

Physiologically-based pharmacokinetic modeling to evaluate in vitro-to-in vivo extrapolation for intestinal P-glycoprotein inhibition

As one of the key components in model‐informed drug discovery and development, physiologically‐based pharmacokinetic (PBPK) modeling linked with in vitro‐to‐in vivo extrapolation (IVIVE) is widely applied to quantitatively predict drug–drug interactions (DDIs) on drug‐metabolizing enzymes and transporters. This study aimed to investigate an IVIVE for intestinal P‐glycoprotein (Pgp, ABCB1)‐mediated DDIs among three Pgp substrates, digoxin, dabigatran etexilate, and quinidine, and two Pgp inhibitors, itraconazole and verapamil, via PBPK modeling. For Pgp substrates, assuming unbound Michaelis‐Menten constant (K_m) to be intrinsic, in vitro‐to‐in vivo scaling factors for maximal Pgp‐mediated efflux rate (J_max) were optimized based on the clinically observed results without co‐administration of Pgp inhibitors. For Pgp inhibitors, PBPK models utilized the reported in vitro values of Pgp inhibition constants (K_i), 1.0 μM for itraconazole and 2.0 μM for verapamil. Overall, the PBPK modeling sufficiently described Pgp‐mediated DDIs between these substrates and inhibitors with the prediction errors of less than or equal to ±25% in most cases, suggesting a reasonable IVIVE for Pgp kinetics in the clinical DDI results. The modeling results also suggest that Pgp kinetic parameters of both the substrates (K_m and J_max) and the inhibitors (K_i) are sensitive to Pgp‐mediated DDIs, thus being key for successful DDI prediction. It would also be critical to incorporate appropriate unbound inhibitor concentrations at the site of action into PBPK models. The present results support a quantitative prediction of Pgp‐mediated DDIs using in vitro parameters, which will significantly increase the value of in vitro studies to design and run clinical DDI studies safely and effectively.

Evidence-Based Guidelines for Drug Interaction Studies: Model-Informed Time Course of Intestinal and Hepatic CYP3A4 Inhibition by Clarithromycin

Drug-drug interaction (DDI) studies are mandated in drug development; however, protocols for evaluating the impact of cytochrome P450 (CYP) inhibition on new molecular entities are currently inconsistent. This study utilised validated physiologically based pharmacokinetic (PBPK) software to define the optimal dose, frequency, and duration of clarithromycin to achieve optimal characterisation of CYP3A4 inhibition in a study population. The Simcyp® Simulator (Version 19.0) was used to simulate clarithromycin-mediated CYP3A4 inhibition in healthy virtual cohorts. Between trial variability in magnitude and time course of CYP3A4 activity was assessed following clarithromycin dosing strategies obtained from the University of Washington Drug Interaction Database. Heterogeneity in CYP3A4 inhibition was evaluated across sex, race, and age. Literature review identified 500 mg twice daily for 5 days as the most common clarithromycin dosing protocol for CYP3A4 inhibition studies. On simulation, clarithromycin 500 mg twice daily resulted in the largest steady-state inhibition of hepatic (percent mean inhibition [95%CI] = 80 [77-83]) and small intestine (94 [94-95]) CYP3A4 activity (as compared to 500 mg once daily, 400 mg once/twice daily, or 250 mg once/twice daily). Additionally, 500 mg twice daily was associated with the shortest time for 90% of individuals to reach 90% of their minimum hepatic (4 days) and small intestine (1 days) CYP3A4 activity. The study presented herein supports that clarithromycin dosing protocol of 500 mg twice daily for 5 days is sufficient to achieve maximal hepatic and small intestine CYP3A4 inhibition. These findings were consistent between sex, race, and age differences.

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.

A New Intestinal Model for Analysis of Drug Absorption and Interactions Considering Physiological Translocation of Contents

Precise prediction of drug absorption is key to the success of new drug development and efficacious pharmacotherapy. In this study, we developed a new absorption model, the advanced translocation model (ATOM), by extending our previous model, the translocation model. ATOM reproduces the translocation of a substance in the intestinal lumen using a partial differential equation with variable dispersion and convection terms to describe natural flow and micromixing within the intestine under not only fasted but also fed conditions. In comparison with ATOM, it was suggested that a conventional absorption model, advanced compartmental absorption and transit model, tends to underestimate micromixing in the upper intestine, and it is difficult to adequately describe movements under the fasted and fed conditions. ATOM explains the observed nonlinear absorption of midazolam successfully, with a minimal number of scaling factors. Furthermore, ATOM considers the apical and basolateral membrane permeabilities of enterocytes separately and assumes compartmentation of the lamina propria, including blood vessels, to consider intestinal blood flow appropriately. ATOM estimates changes in the intestinal availability caused by drug interaction associated with inhibition of CYP3A and P-glycoprotein in the intestine. Additionally, ATOM can estimate the drug absorption in the fed state considering delayed intestinal drug flow. Therefore, ATOM is a useful tool for the analysis of local pharmacokinetics in the gastrointestinal tract, especially for the estimation of nonlinear drug absorption, which may involve various interactions with intestinal contents or other drugs. SIGNIFICANCE STATEMENT: The newly developed advanced translocation model precisely explains various movements of intestinal contents under fasted and fed conditions, which cannot be adequately described by the current physiological pharmacokinetic models.

A generic framework for the physiologically-based pharmacokinetic platform qualification of PK-Sim and its application to predicting cytochrome P450 3A4-mediated drug-drug interactions

The success of applications of physiologically‐based pharmacokinetic (PBPK) modeling in drug development and drug labeling has triggered regulatory agencies to demand rigorous demonstration of the predictive capability of the specific PBPK platform for a particular intended application purpose. The effort needed to comply with such qualification requirements exceeds the costs for any individual PBPK application. Because changes or updates of a PBPK platform would require (re‐)qualification, a reliable and efficient generic qualification framework is needed. We describe the development and implementation of an agile and sustainable technical framework for automatic PBPK platform (re‐)qualification of PK‐Sim^® embedded in the open source and open science GitHub landscape of Open Systems Pharmacology. The qualification approach enables the efficient assessment of all aspects relevant to the qualification of a particular purpose and provides transparency and traceability for all stakeholders. As a showcase example for the power and versatility of the qualification framework, we present the qualification of PK‐Sim^® for the intended purpose of predicting cytochrome P450 3A4 (CYP3A4)–mediated drug–drug interactions (DDIs). Several perpetrator PBPK models featuring various degrees of CYP3A4 modulation and different types of mechanisms (competitive inhibition, mechanism‐based inactivation, and induction) were coupled with a set of PBPK models of sensitive CYP3A4 victim drugs. Simulations were compared to a comprehensive data set of 135 observations from published clinical DDI studies. The platform's overall predictive performance showed reasonable accuracy and precision (geometric mean fold error of 1.4 for both area under the plasma concentration‐time curve ratios and peak plasma concentration ratios with/without perpetrator) and suggests that PK‐Sim^® can be applied to quantitatively assess CYP3A4‐mediated DDI in clinically untested scenarios.

Effects of CYP3A inhibitors ketoconazole, voriconazole, and itraconazole on the pharmacokinetics of sunitinib and its main metabolite in rats

Sunitinib is a small molecule inhibitor of multiple receptor tyrosine kinases such as platelet derived growth factor receptor, vascular endothelial growth factor receptor, kit receptor and other receptors. The US Food and Drug Administration (FDA) has approved sunitinib for the treatment of advanced renal cell carcinoma and gastrointestinal stromal tumors. It has been reported that sunitinib was mainly metabolized by CYP3A but its pharmacokinetic interactions have not been revealed. In this study, we investigated whether CYP3A inhibitors (ketoconazole, voriconazole, and itraconazole) could influence the pharmacokinetics of sunitinib and its equipotent metabolite N-desethyl sunitinib in a drug-drug interaction study in Sprague Dawley (SD) rats. The results showed that ketoconazole and voriconazole significantly increased the exposure of sunitinib, decreased the exposure of N-desethyl sunitinib, and inhibited the metabolism of sunitinib in rats. However, itraconazole showed only a weak effect on pharmacokinetics and metabolism. Coadministration of sunitinib with ketoconazole and voriconazole should be avoided if possible or if not, there should be therapeutic drug monitoring of the levels of sunitinib and N-desethyl sunitinib. Therefore, drug-drug interaction should be considered when sunitinib is administered in conjunction with CYP3A inhibitors, which might lead to toxicity.

A combination of receptor mediated transcytosis and photothermal effect promotes BBB permeability and the treatment of meningitis using itraconazole

Fungal infections of the central nervous system (CNS) may lead to life-threatening meningitis. Itraconazole (ITZ) is an effective antifungal agent that can be used to treat various fungal infections; however, its poor solubility along with poor permeability of the blood-brain barrier (BBB) prevents it from treating meningitis. Receptor mediated transcytosis (RMT) shows modest efficacy in BBB crossing, while affinity and saturability of interactions between ligands and receptors account for the limited efficacy of RMT in crossing the BBB. Mild hyperthermia could temporarily disrupt the BBB to increase its permeability. Therefore, we speculated that the combination of mild hyperthermia with RMT could potentially increase BBB permeability of ITZ leading to improved efficacy in fungal meningitis. Here, we have constructed for the first time, apolipoprotein E (Apo E) mimicked peptide COG1410 modified polydopamine (PDA)-coated bovine serum albumin nanoparticles (ApoE-PDA@ITZ-NPs). Different levels of COG1410-modified NPs were prepared and characterized. ApoE-PDA@ITZ-NPs have a superior photothermal effect under 808 nm light irradiation and exhibited favorable plasma stability and photothermal stability. Moreover, the cellular uptake of nanoparticles increased with an increase in COG1410. H-ApoE-PDA@ITZ-NPs increased cellular uptake and in vitro BBB permeability by 4.2-fold and 4.8-fold, respectively, compared to the ITZ-NPs. Live imaging implied that H-ApoE-PDA@ITZ-NPs could significantly increase the distribution of ITZ in the brain under 808 nm light irradiation. Histopathological analysis of periodic acid-Schiff-stained brain sections of the H-ApoE-PDA@ITZ-NP treated C. albicans meningitis model indicated that H-ApoE-PDA@ITZ-NPs showed superior antifungal activity after 808 nm light irradiation. Hence, we report ApoE-PDA@ITZ-NPs in tandem with 808 nm irradiation as a novel strategy of RMT combination with a photothermal effect in enhancing BBB permeability to facilitate drug accumulation in the brain region and enhance the therapeutic efficacy of ITZ in meningitis.

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

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

Borneol and poly (ethylene glycol) dual modified BSA nanoparticles as an itraconazole vehicle for brain targeting

Itraconazole (ITZ) can be used for the treatment of cryptococcus neoformans meningitis and aspergillus brain abscess. While, the inherent hydrophobicity of ITZ and the existence of blood brain barrier (BBB) limit its applications as a central nervous system drug. In this study, a novel brain targeting drug delivery system based on bovine serum albumin (BSA) was constructed for enhancing ITZ distribution in brain. Firstly, ITZ was loaded into BSA nanoparticles (ITZ-NPs) with 11.6% of drug loading. Subsequently, the nanoparticles were modified with borneol (BO) and polyethylene glycol (PEG) (PEG/BO-ITZ-NPs). The resulting nanoparticles retained their nanosize (186.3 nm), uniform and spherical morphology, and negative surface charge (-21.03 mV). Cell uptake studies showed that compared with ITZ-NPs, PEG/BO-ITZ-NPs had significantly increased uptake in bEnd.3 cells, and the increase in BO concentration was beneficial for the cellular uptake of NPs. Moreover, PEG/BO-ITZ-NPs displayed an approximately 3.5-fold higher area under the curve in rats and about 2-fold higher brain distribution in mice than that of Sporanox®, i.e. ITZ solubilized by hydroxylpropyl-β-cyclodetrin, after i.v. administration. In a word, BO and PEG dual modified BSA nanoparticles may potentially serve as an ITZ vehicle for brain targeting.

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.

The optimization of methadone dosing whilst treating with rifampicin: A pharmacokinetic modeling study

BACKGROUND

The use of oral methadone in opioid substitution treatment (OST) for the management of opioid use disorder is established clinical practice. Confounding treatment is the increased risks of contracting Mycobacterium tuberculosis, the mainstay treatment of which incorporates the potent CYP 2B6 inducer rifampicin.

METHODS

This study applied pharmacokinetic modelling using virtual clinical trials, to pharmacokinetically quantify the extent and impact of rifampicin-mediated drug-drug interactions (DDI) on methadone plasma concentrations. An R-methadone model was developed and validated against 11 retrospective clinical studies prior to use in all subsequent studies. The aims were to investigate: (i) the impact of the DDI on daily methadone doses of 60 mg, 90 mg and 120 mg; (ii) dose escalation during rifampicin and (iii) dose reduction following rifampicin cessation.

RESULTS

A dose increase to 160 mg daily during rifampicin treatment phases was required to maintain peak methadone plasma concentrations within a derived therapeutic window of 80-700 ng/mL. Dose escalation prior to rifampicin initiation was not required and resulted in an increase in subjects with supra-therapeutic concentrations. However, during rifampicin cessation, a dose reduction of 10 mg every 2 days commencing prior to rifampicin cessation, ensured that most patients possessed a peak methadone plasma concentration within an optimal therapeutic window.

IMPLICATIONS

Rifampicin significantly alters methadone plasma concentrations and necessitates dose adjustments. Daily doses of almost double those used perhaps more commonly in clinical practice are required for optimal plasma concentration and careful consideration of dose reduction strategies would be required during the deinduction phase.

Impact of Intracellular Concentrations on Metabolic Drug-Drug Interaction Studies

Accurate prediction of drug-drug interactions (DDI) is a challenging task in drug discovery and development. It requires determination of enzyme inhibition in vitro which is highly system-dependent for many compounds. The aim of this study was to investigate whether the determination of intracellular unbound concentrations in primary human hepatocytes can be used to bridge discrepancies between results obtained using human liver microsomes and hepatocytes. Specifically, we investigated if Kp_uu could reconcile differences in CYP enzyme inhibition values (K_i or IC₅₀). Firstly, our methodology for determination of Kp_uu was optimized for human hepatocytes, using four well-studied reference compounds. Secondly, the methodology was applied to a series of structurally related CYP2C9 inhibitors from a Roche discovery project. Lastly, the Kp_uu values of three commonly used CYP3A4 inhibitors—ketoconazole, itraconazole, and posaconazole—were determined and compared to compound-specific hepatic enrichment factors obtained from physiologically based modeling of clinical DDI studies with these three compounds. Kp_uu obtained in suspended human hepatocytes gave good predictions of system-dependent differences in vitro. The Kp_uu was also in fair agreement with the compound-specific hepatic enrichment factors in DDI models and can therefore be used to improve estimations of enrichment factors in physiologically based pharmacokinetic modeling.