Critical Impact of Drug-Drug Interactions via Intestinal CYP3A in the Risk Assessment of Weak Perpetrators Using Physiologically Based Pharmacokinetic Models

Quantitative prediction of CYP3A induction-mediated drug-drug interactions in clinical practice

There have been no reports on the quantitative prediction of CYP3A induction-mediated decreases in AUC and Cmax for drug candidates identified as a "victims" of CYP3A induction. Our previous study separately evaluated the fold-induction of hepatic and intestinal CYP3A by known inducers using clinical induction data and revealed that we were able to quantitatively predict the AUC ratio (AUCR) of a few CYP3A substrates in the presence and absence of CYP3A inducers. In the present study, we investigate the predictability of AUCR and also Cmax ratio (CmaxR) in additional 54 clinical studies. The fraction metabolized by CYP3A (fm), the intestinal bioavailability (Fg), and the hepatic intrinsic clearance (CLint) of substrates were determined by the in vitro experiments as well as clinical data used for calculating AUCR and CmaxR. The result showed that 65-69% and 65-67% of predictions were within 2-fold of observed AUCR and CmaxR, respectively. A simulation using multiple parameter combinations suggested that the variability of fm and Fg within a certain range might have a minimal impact on the calculation output. These findings suggest that clinical AUCR and CmaxR of CYP3A substrates can be quantitatively predicted from the preclinical stage.

An Integrative Approach to Elucidate Mechanisms Underlying the Pharmacokinetic Goldenseal-Midazolam Interaction: Application of In Vitro Assays and Physiologically Based Pharmacokinetic Models to Understand Clinical Observations

The natural product goldenseal is a clinical inhibitor of CYP3A activity, as evidenced by a 40%-60% increase in midazolam area under the plasma concentration versus time curve (AUC) after coadministration with goldenseal. The predominant goldenseal alkaloids berberine and (-)-β-hydrastine were previously identified as time-dependent CYP3A inhibitors using human liver microsomes. Whether these alkaloids contribute to the clinical interaction, as well as the primary anatomic site (hepatic vs. intestinal) and mode of CYP3A inhibition (reversible vs. time-dependent), remain uncharacterized. The objective of this study was to mechanistically assess the pharmacokinetic goldenseal-midazolam interaction using an integrated in vitro-in vivo-in silico approach. Using human intestinal microsomes, (-)-β-hydrastine was a more potent time-dependent inhibitor of midazolam 1'-hydroxylation than berberine (KI and kinact: 8.48 μM and 0.041 minutes-1, respectively, vs. >250 μM and ∼0.06 minutes-1, respectively). Both the AUC and Cmax of midazolam increased by 40%-60% after acute (single 3-g dose) and chronic (1 g thrice daily × 6 days) goldenseal administration to healthy adults. These increases, coupled with a modest or no increase (≤23%) in half-life, suggested that goldenseal primarily inhibited intestinal CYP3A. A physiologically based pharmacokinetic interaction model incorporating berberine and (-)-β-hydrastine successfully predicted the goldenseal-midazolam interaction to within 20% of that observed after both chronic and acute goldenseal administration. Simulations implicated (-)-β-hydrastine as the major alkaloid precipitating the interaction, primarily via time-dependent inhibition of intestinal CYP3A, after chronic and acute goldenseal exposure. Results highlight the potential interplay between time-dependent and reversible inhibition of intestinal CYP3A as the mechanism underlying natural product-drug interactions, even after acute exposure to the precipitant. SIGNIFICANCE STATEMENT: Natural products can alter the pharmacokinetics of an object drug, potentially resulting in increased off-target effects or decreased efficacy of the drug. The objective of this work was to evaluate fundamental mechanisms underlying the clinically observed goldenseal-midazolam interaction. Results support the use of an integrated approach involving established in vitro assays, clinical evaluation, and physiologically based pharmacokinetic modeling to elucidate the complex interplay between multiple phytoconstituents and various pharmacokinetic processes driving a drug interaction.

Pharmacokinetic and Pharmacodynamic Drug-Drug Interactions: Research Methods and Applications

Because of the high research and development cost of new drugs, the long development process of new drugs, and the high failure rate at later stages, combining past drugs has gradually become a more economical and attractive alternative. However, the ensuing problem of drug-drug interactions (DDIs) urgently need to be solved, and combination has attracted a lot of attention from pharmaceutical researchers. At present, DDI is often evaluated and investigated from two perspectives: pharmacodynamics and pharmacokinetics. However, in some special cases, DDI cannot be accurately evaluated from a single perspective. Therefore, this review describes and compares the current DDI evaluation methods based on two aspects: pharmacokinetic interaction and pharmacodynamic interaction. The methods summarized in this paper mainly include probe drug cocktail methods, liver microsome and hepatocyte models, static models, physiologically based pharmacokinetic models, machine learning models, in vivo comparative efficacy studies, and in vitro static and dynamic tests. This review aims to serve as a useful guide for interested researchers to promote more scientific accuracy and clinical practical use of DDI studies.

Application of Physiologically Based Pharmacokinetic Modeling to Predict Drug-Drug Interactions between Elexacaftor/Tezacaftor/Ivacaftor and Tacrolimus in Lung Transplant Recipients

Elexacaftor/tezacaftor/ivacaftor (ETI) treatment has potential benefits in lung transplant recipients, including improvements in extrapulmonary manifestations, such as gastrointestinal and sinus disease; however, ivacaftor is an inhibitor of cytochrome P450 3A (CYP3A) and may, therefore, pose a risk for elevated systemic exposure to tacrolimus. The aim of this investigation is to determine the impact of ETI on tacrolimus exposure and devise an appropriate dosing regimen to manage the risk of this drug-drug interaction (DDI). The CYP3A-mediated DDI of ivacaftor-tacrolimus was evaluated using a physiologically based pharmacokinetic (PBPK) modeling approach, incorporating CYP3A4 inhibition parameters of ivacaftor and in vitro enzyme kinetic parameters of tacrolimus. To further support the findings in PBPK modeling, we present a case series of lung transplant patients who received both ETI and tacrolimus. We predicted a 2.36-fold increase in tacrolimus exposure when co-administered with ivacaftor, which would require a 50% dose reduction of tacrolimus upon initiation of ETI treatment to avoid the risk of elevated systemic exposure. Clinical cases (N = 13) indicate a median 32% (IQR: -14.30, 63.80) increase in the dose-normalized tacrolimus trough level (trough concentration/weight-normalized daily dose) after starting ETI. These results indicate that the concomitant administration of tacrolimus and ETI may lead to a clinically significant DDI, requiring the dose adjustment of tacrolimus.

Prediction for optimal dosage of pazopanib under various clinical situations using physiologically based pharmacokinetic modeling

This study aimed to apply a physiologically based pharmacokinetic (PBPK) model to predict optimal dosing regimens of pazopanib (PAZ) for safe and effective administration when co-administered with CYP3A4 inhibitors, acid-reducing agents, food, and administered in patients with hepatic impairment. Here, we have successfully developed the population PBPK model and the predicted PK variables by this model matched well with the clinically observed data. Most ratios of prediction to observation were between 0.5 and 2.0. Suitable dosage modifications of PAZ have been identified using the PBPK simulations in various situations, i.e., 200 mg once daily (OD) or 100 mg twice daily (BID) when co-administered with the two CYP3A4 inhibitors, 200 mg BID when simultaneously administered with food or 800 mg OD when avoiding food uptake simultaneously. Additionally, the PBPK model also suggested that dosing does not need to be adjusted when co-administered with esomeprazole and administration in patients with wild hepatic impairment. Furthermore, the PBPK model also suggested that PAZ is not recommended to be administered in patients with severe hepatic impairment. In summary, the present PBPK model can determine the optimal dosing adjustment recommendations in multiple clinical uses, which cannot be achieved by only focusing on AUC linear change of PK.

Pharmacokinetics of Apixaban and Tacrolimus or Cyclosporine in Kidney and Lung Transplant Recipients

Apixaban is frequently used off‐label in transplant recipients. However, a potential drug interaction exists with the calcineurin inhibitors. We conducted an open‐label drug–drug interaction study to determine the pharmacokinetics of apixaban in lung and kidney transplant recipients who were taking a calcineurin inhibitor. A single dose of apixaban 10 mg was administered orally to kidney and lung transplant recipients maintained on either tacrolimus or cyclosporine, and pharmacokinetic parameters were compared to a reference cohort of 12 healthy subjects who used the same apixaban dose and pharmacokinetic blood sampling. Fourteen participants were enrolled (n = 6 kidney, n = 8 lung), with 10 maintained on tacrolimus and four on cyclosporine. Data from 13 participants was usable. Participants were taking triple therapy immunosuppression and had a mean (SD) of 12 (3) medications. Participants receiving tacrolimus and cyclosporine had area under the plasma concentration–time curve from time zero to infinity (AUC_0‐inf) geometric least square means (90% confidence interval [CI]) of 4312 (95% CI 3682, 5049) and 5388 (95% CI 3277, 8858), respectively. Compared to healthy subjects, the associated geometric mean ratios (GMRs) for apixaban maximum plasma concentration (C_max), AUC from time zero to the last quantifiable concentration (AUC_0‐tlast) and AUC_0‐inf were 197% (95% CI 153, 295), 244% (95% CI 184, 323), and 224% (95% CI 170, 295) for transplant recipients on tacrolimus. The GMR (90% CI) C_max, AUC_0‐tlast, and AUC_0‐inf of apixaban for patients on cyclosporine were 256% (95% CI 184, 358), 287% (95% CI 198, 415), and 280% (95% CI 195, 401). Kidney and lung transplant recipients receiving tacrolimus had higher apixaban exposure. A similar trend was noted for patients receiving cyclosporine, but additional patients are needed to confirm this interaction. Future studies are needed before apixaban can be safely recommended in this population, and the impact of dose staggering should be investigated. This study highlights the importance of pharmacokinetic studies in actual patient populations.

Clinical Pharmacokinetics and Pharmacodynamics of Esaxerenone, a Novel Mineralocorticoid Receptor Antagonist: A Review

Esaxerenone is a selective, nonsteroidal, high-affinity mineralocorticoid receptor antagonist recently approved in Japan for the treatment of hypertension. It has high oral biovailability, a large volume of distribution, and is primarly metabolized in liver and excreted in bile. Esaxerenone is an efficient antihypertensive, whether given alone or as add-on therapy. The antihypertensive effect is accompanied by renoprotective action, which is being further investigated in current clinical trials. Due to its relatively long half-life and high affinity for the mineralocorticoid receptor, esaxerenone is administered once daily and in low absolute doses. The safety of esaxerenone is considerable, since hyperkalemia is not frequent and, when it does appear, not sustained. Endocrine adverse events, which frequently occur with steroidal mineralocorticoid receptor antagonists, are extremely rare with esaxerenone. Although the risk of clinically significant drug-drug interactions is not high, esaxerenone treatment should start with low doses, with subsequent titration to achieve the optimal clinical effect, all while monitoring serum potassium and paying attention to concomitant therapy with drugs that may induce or inhibit esaxerenone metabolism. This review article offers comprehensive information about the pharmacodynamics and pharmacokinetics of esaxerenone in humans, which should help clinicians to more precisely tailor esaxerenone dosing regimens to their patients.

Predictive In Vitro-In Vivo Extrapolation for Time Dependent Inhibition of CYP1A2, CYP2C8, CYP2C9, CYP2C19 and CYP2D6 Using Pooled Human Hepatocytes, Human Liver Microsomes, and a Simple Mechanistic Static Model

Inactivation of Cytochrome P450 (CYP450) enzymes can lead to significant increases in exposure of co-medicants. The majority of reported in vitro to in vivo extrapolation (IVIVE) data have historically focused on CYP3A4 leaving the assessment of other CYP isoforms insubstantial. To this end, the utility of human hepatocytes (HHEP) and microsome (HLM) to predict clinically relevant DDIs was investigated with a focus on CYP1A2, CYP2C8, CYP2C9, CYP2C19 and CYP2D6. Evaluation of IVIVE for CYP2B6 was limited to only weak inhibition. A search of the University of Washington Drug-Drug Interaction Database was conducted to identify a clinically relevant weak, moderate and strong inhibitor for selective substrates of CYP1A2, CYP2C8, CYP2C9, CYP2C19 and CYP2D6, resulting in 18 inhibitors for in vitro characterization against 119 clinical interaction studies. Pooled human hepatocytes and HLM were pre-incubated with increasing concentrations of inhibitors for designated timepoints. Time dependent inhibition (TDI) was detected in HLM for four moderate/strong inhibitors suggesting that some optimization of incubation conditions (i.e. lower protein concentrations) is needed to capture weak inhibition. Clinical risk assessment was conducted by incorporating the in vitro derived kinetic parameters k_inact and K_I into static equations recommended by regulatory authorities. Significant overprediction was observed when applying the basic models recommended by regulatory agencies. Mechanistic static models (MSM), which consider the fraction of metabolism through the impacted enzyme, using the unbound hepatic inlet concentration lead to the best overall prediction accuracy with 92% and 85% of data from HHEPs and HLM, respectively, within 2-fold of the observed value. Significance Statement Collectively, the data demonstrate that coupling time-dependent inactivation parameters derived from pooled human hepatocytes and HLM with a mechanistic static model provides an easy and quantitatively accurate means to determine clinical DDI risk from in vitro data. Weak and moderate inhibitors did not show TDI under standard incubation conditions using HLM and optimization of incubation conditions is warranted. Recommendations are made with respect to input parameters for IVIVE of TDI with non-CYP3A enzymes using available data from HLM and HHEPs.

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.

Reversible Mechanisms of Enzyme Inhibition and Resulting Clinical Significance

Inhibition of a drug-metabolizing enzyme by the reversible interaction of a drug with the enzyme, thus decreasing the metabolism of another drug, is a major cause of clinically significant drug-drug interactions. This chapter defines the four reversible mechanisms of inhibition exhibited by drugs: competitive, noncompetitive, uncompetitive, and mixed competitive/noncompetitive. An in vitro procedure to determine the potential of a drug to be a reversible inhibitor is also provided. Finally, a number of examples of clinically significant drug-drug interactions resulting from reversible inhibition are described.

Drug-Drug Interaction Risk Assessment of Esaxerenone as a Perpetrator by In Vitro Studies and Static and Physiologically Based Pharmacokinetic Models

Esaxerenone (CS-3150) is a novel, oral, nonsteroidal, selective mineralocorticoid receptor blocker approved for the treatment of hypertension in Japan. Here, the drug-drug interaction (DDI) potential of esaxerenone was evaluated in vitro, and its impact in clinical practice was estimated. Esaxerenone exhibited time-dependent inhibition and induction of CYP3A. When the clinical impacts of esaxerenone on the inhibition and induction of CYP3A were estimated separately by using a mechanistic static model, the predicted area under the curve ratios (AUCRs) of midazolam, a typical CYP3A substrate, were 1.80 and 0.31, respectively, suggesting that the DDI potential of esaxerenone cannot be neglected. Because it was suggested that DDIs mainly occur in the intestine, predictions using concentration-time profiles in each segment of the gastrointestinal tract were performed with GastroPlus, a physiologically based pharmacokinetic (PBPK) modeling software. The predicted AUCR of midazolam was approximately 1.2, which is close to that in a clinical study, despite the difficulty of predicting DDIs for compounds with both inhibition and induction effects. When only inhibition or induction was incorporated into a model, the AUCR of midazolam changed depending on the dosing period and dose level of esaxerenone and the timing of midazolam administration. However, the AUCR calculated by incorporating both effects remained almost constant. This study shows the ability of PBPK models to simulate weak DDIs via intestinal CYP3A and that esaxerenone has low DDI potential as a perpetrator because of the offset of inhibition and induction. SIGNIFICANCE STATEMENT: Weak CYP3A inhibition and/or induction sometimes cause DDIs in the intestine but not the liver. Because strong inhibitors maximally inhibit intestinal CYP3A, the predictability of weak DDIs in the intestine should be evaluated further. Here, we simulate the DDIs of esaxerenone as a perpetrator by using physiologically based pharmacokinetic modeling focusing on the intestine and offset of inhibition and induction.