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A drug delivery system based on silybin-conjugated chitosan (CS-SB) polymeric micelles was developed to improve the oral absorption of doxorubicin (DOX). SB was grafted to CS via succinic acid, and CS-SB was identified by 1 H NMR and FT-IR. The DOX-loaded micelles were prepared by self-assembly, and the characteristics of micelles, including a small particle size of 167.8 ± 2.3 nm, a high drug loading capacity of 8.59%, and a low critical micelle concentration of 1.3 × 10 -5 g/mL, were demonstrated. The micelles showed oral bioavailability of up to 193% versus DOX·HCl. The cytotoxicity test showed the biosafety of CS-SB and the potential of reductive DOX-induced cardiotoxicity. The inhibition of P-gp efflux and CYP3A4 enzyme in CS-SB micelles was confirmed by cellular uptake and enzyme activity inhibition tests. The endocytosis process of micelles was revealed by an endocytosis inhibition test. The findings exhibited the potential of CS-SB micelles in drug delivery.

Background and Objectives: A pharmacokinetic model has been developed to quantify the drug-drug interactions of tacrolimus with concentration-dependent inhibition of cytochrome P450 (CYP) 3A4 from voriconazole and clarithromycin based on the CYP3A5 and CYP2C19 genotypes., Methods: This retrospective study recruited unrelated bone marrow transplant recipients receiving oral tacrolimus concomitantly with voriconazole and clarithromycin. The published population pharmacokinetic model that implemented genotypes of CYP3A5 (tacrolimus) and CYP2C19 (voriconazole) was integrated. The tested CYP3A4 inhibition models (Sigmoid efficacy maximum [E max ], E max , log-linear, and linear) were a function of competitive inhibition of voriconazole and mechanism-based inhibition of clarithromycin in a virtual enzyme compartment., Results: The total tacrolimus trough concentrations were 119 points, with a median of 4.3 (range: 2.0-9.9) ng/mL (n = 3). The final model comprised the Sigmoid E max model for voriconazole and clarithromycin, which depicted time-course alterations in tacrolimus concentration and clearance when given voriconazole and clarithromycin., Conclusions: These findings could facilitate the model-informed precision dosing of tacrolimus after unrelated bone marrow transplant., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Early detection of drug-drug interactions (DDIs) can facilitate timely drug development decisions, prevent unnecessary restrictions on patient enrollment, resulting in clinical study populations that are not representative of the indicated study population, and allow for appropriate dose adjustments to ensure safety in clinical trials. All of these factors contribute to a streamlined drug approval process and enhanced patient safety. Here we describe a new approach for early prediction of the magnitude of change in exposure for cytochrome P450 (P450) CYP3A4-related DDIs of small-molecule anticancer drugs based on the model-based extrapolation of human-CYP3A4-transgenic mice pharmacokinetics to humans. Victim drugs brigatinib and lorlatinib were evaluated with the new approach in combination with the perpetrator drugs itraconazole and rifampicin. Predictions of the magnitude of change in exposure deviated at most 0.99- to 1.31-fold from clinical trial results for inhibition with itraconazole, whereas exposure predictions for the induction with rifampicin were less accurate, with deviations of 0.22- to 0.48-fold. Results for the early prediction of DDIs and their clinical impact appear promising for CYP3A4 inhibition, but validation with more victim and perpetrator drugs is essential to evaluate the performance of the new method. SIGNIFICANCE STATEMENT: The described method offers an alternative for the early detection and assessment of potential clinical impact of CYP3A4-related drug-drug interactions. The model was able to adequately describe the inhibition of CYP3A4 metabolism and the subsequent magnitude of change in exposure. However, it was unable to accurately predict the magnitude of change in exposure of victim drugs in combination with an inducer., (Copyright © 2024 by The Author(s).)

Background: Cariprazine is metabolised mainly by CYP3A4 and to a lesser extent by CYP2D6., Aim: This study aimed to evaluate the effects of erythromycin, a moderate cytochrome P450 (CYP)3A4 inhibitor, on the pharmacokinetics of cariprazine in male patients with schizophrenia, and to assess the influence of CYP2D6 phenotypes on cariprazine metabolism., Methods: Forty-two patients received oral doses of 1.5 mg cariprazine alone for 28 days (to reach steady state), followed by a co-administration of cariprazine 1.5 mg daily with erythromycin 500 mg twice daily (BID) and Enterol 250 mg BID for 21 days, followed by a 14-day post-treatment period. Blood samples were collected at predefined time points and analysed for cariprazine, its two active metabolites: desmethyl cariprazine (DCAR) and didesmethyl cariprazine (DDCAR), and erythromycin using validated high performance liquid chromatography-tandem mass spectrometry methods. CYP2D6 phenotypes were determined by genotyping. The pharmacokinetic parameters were calculated using non-compartmental analysis., Results: Erythromycin increased the area under the curve (AUC τ ) and peak concentration (C max ) of Total cariprazine (cariprazine + DCAR + DDCAR) by about 40-50% but did not affect the time to peak concentration (T max ). The CYP2D6 phenotypes had no substantial effect on the pharmacokinetics of cariprazine and its metabolites, either alone or in combination with erythromycin. Cariprazine was well tolerated and safe., Conclusion: The findings suggest that co-administration of cariprazine with moderate CYP3A4 inhibitors may require dose adjustment or monitoring; however, pharmacogenetic testing for CYP2D6 is not necessary for optimising cariprazine therapy., Trial Registration: Trial registration number (EudraCT Number): 2018-003721-28. Date of registration: 21-SEP-2018., (© 2024. The Author(s).)

Purpose: A physiologically based pharmacokinetic (PBPK) model for fedratinib was updated and revalidated to bridge a gap between the observed drug-drug interaction (DDI) of a single sub-efficacious dose in healthy participants and the potential DDI in patients with cancer at steady state. The study aimed to establish an appropriate dose for fedratinib in patients coadministered with dual CYP3A4 and CYP2C19 inhibitors, providing quantitative evidence to inform dosing guidance., Methods: The original minimal PBPK model was developed using Simcyp ® Simulator v17. The model was updated by substituting a single distribution rate (Q sac ) with 2 separate rates (CL in /CL out ) and transitioning to v20. Model parameter updates were further informed with 3 clinical studies, and 3 more studies served as independent validation data. The validated model was applied to simulate potential DDIs between fedratinib and a known dual inhibitor of CYP3A4 and CYP2C19 (fluconazole)., Results: Coadministration of fedratinib with fluconazole in patients was predicted to increase fedratinib exposure by < 2-fold in all simulated scenarios. For patients with cancer receiving the approved dose of fedratinib 400 mg once daily along with fluconazole 200 mg daily, the model predicted an approximate 50% increase in fedratinib exposure at steady state., Conclusions: The updated PBPK model improved description of the observed pharmacokinetics and predicted a low risk of clinically significant DDIs between fedratinib and fluconazole. The quantitative evidence serves as a primary foundation for providing dose guidance in clinical practice for the coadministration of fedratinib with dual CYP3A4 and CYP2C19 inhibitors., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Physiologically based pharmacokinetic (PBPK) models of entrectinib and its equipotent metabolite, M5, were established in healthy adult subjects and extrapolated to pediatric patients to predict increases in steady-state systemic exposure on co-administration of strong and moderate CYP3A4 inhibitors (itraconazole at 5 mg/kg, erythromycin at 7.5-12.5 mg/kg and fluconazole at 3-12 mg/kg, respectively). Adult model establishment involved the optimization of fraction metabolized by CYP3A4 (0.92 for entrectinib and 0.98 for M5) using data from an itraconazole DDI study. This model captured well the exposure changes of entrectinib and M5 seen in adults co-administered with the strong CYP3A4 inducer rifampicin. In pediatrics, reasonable prediction of entrectinib and M5 pharmacokinetics in ≧2 year olds was achieved when using the default models for physiological development and enzyme ontogenies. However, a two to threefold misprediction of entrectinib and M5 exposures was seen in <2 year olds which may be due to missing mechanistic understanding of gut physiology and/or protein binding in very young children. Model predictions for ≧2 year olds showed that entrectinib AUC(0-t) was increased by approximately sevenfold and five to threefold by strong and high-moderate and low-moderate CYP3A4 inhibitors, respectively. Based on these victim DDI predictions, dose adjustments for entrectinib when given concomitantly with strong and moderate CYP3A4 inhibitors in pediatric subjects were recommended. These simulations informed the approved entrectinib label without the need for additional clinical pharmacology studies., (© 2024 The Author(s). Clinical Pharmacology & Therapeutics © 2024 American Society for Clinical Pharmacology and Therapeutics.)

Olverembatinib (HQP1351) is a BCR-ABL1 tyrosine kinase inhibitor with promising clinical activity. It is approved in China for the treatment of patients with chronic myeloid leukemia harboring drug-resistant mutations, such as T315I. In vitro studies suggested that metabolism of olverembatinib is primarily mediated by cytochrome P450 (CYP3A4). The effects of CYP3A4 inhibition and induction on the pharmacokinetics of olverembatinib were evaluated in an open-label, 2-part, fixed-sequence study in healthy volunteers. In Part 1 of this study, 16 participants received a single oral dose of olverembatinib (20 mg) and the oral CYP3A4 inhibitor itraconazole (200 mg). In Part 2, 16 participants received a single oral dose of olverembatinib (40 mg) and the oral CYP3A4 inducer rifampin (600 mg). To measure pharmacokinetic parameters, serial blood samples were collected after administration of olverembatinib alone and combined with itraconazole or rifampin. Coadministration of olverembatinib with itraconazole increased the peak plasma concentration of olverembatinib, its area under the time-concentration curve (AUC) 0-last , and AUC 0-inf by 75.63%, 147.06%, and 158.66%, respectively. Coadministration with rifampin decreased these same variables by 61.27%, 74.21%, and 75.19%, respectively. These results confirm that olverembatinib is primarily metabolized by CYP3A4 in humans, suggesting that caution should be exercised with concurrent use of olverembatinib and strong CYP3A4 inhibitors or inducers., (© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The purpose of this overview was to perform an exploratory analysis of in-house drug-drug interaction (DDI) studies conducted with investigational drugs and oral midazolam to assess the value of measuring 1-OH-midazolam (1-OHM) in such studies. The perpetrator effect of the investigational drugs on cytochrome P450 3A (CYP3A) was assessed by analyzing both midazolam and 1-OHM in plasma and evaluating their pharmacokinetic parameters. Given the almost exclusive metabolism of the parent drug by CYP3A to the main metabolite 1-OHM, an increase in midazolam and a decrease in 1-OHM exposure in the case of CYP3A inhibition caused by a perpetrator drug would be expected. The opposite would be anticipated in the case of CYP3A induction. For this analysis, the perpetrator potential of eight different investigational drugs was incorporated. Among the 10 studies included, the identified CYP3A inhibitors (n = 4) and inducers (n = 1) were classified based on the data generated with midazolam per se, with 1-OHM levels not contributing to the interpretation of the data as they did not corroborate the findings of the parent compound. Therefore, it was concluded that continued analysis of 1-OHM in plasma may be questionable as it does not add value to the interpretation of the results when performing CYP3A DDI studies with an investigational drug as a perpetrator., (© 2024, The American College of Clinical Pharmacology.)

Aims: Early clinical studies have indicated that the pharmacokinetics of Atuliflapon (AZD5718) are time and dose dependent. The reason(s) for these findings is(are) not fully understood, but pre-clinical profiling suggests that time-dependent CYP3A4 inhibition cannot be excluded. In clinical practice, Atuliflapon will be co-administered with CYP3A4 substrates; thus, it is important to determine the impact of Atuliflapon on the pharmacokinetics (PK) of CYP3A4 substrates. The aim of this study was to evaluate the effect of Atuliflapon on the pharmacokinetics of a sensitive CYP3A4 substrate, midazolam, and to explore if the time-/dose-dependent effect seen after repeated dosing could be an effect of change in CYP3A4 activity., Methods: Open-label, fixed-sequence study in healthy volunteers to assess the PK of midazolam alone and in combination with Atuliflapon. Fourteen healthy male subjects received single oral dose of midazolam 2 mg on days 1 and 7 and single oral doses of Atuliflapon (125 mg) from days 2 to 7. A physiologically based pharmacokinetic (PBPK) model was developed to assess this drug-drug interaction., Results: Mean midazolam values of maximum plasma concentration (C max ) and area under the curve (AUC) to infinity were increased by 39% and 56%, respectively, when co-administered with Atuliflapon vs. midazolam alone. The PBPK model predicted a 27% and 44% increase in AUC and a 23% and 35% increase in C max of midazolam following its co-administrations with two predicted therapeutically relevant doses of Atuliflapon., Conclusions: Atuliflapon is a weak inhibitor of CYP3A4; this was confirmed by the validated PBPK model. This weak inhibition is predicted to have a minor PK effect on CYP3A4 metabolized drugs., (© 2024 AstraZeneca. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

4 β -Hydroxycholesterol (4 β -HC) in plasma has been used as a biomarker to assess CYP3A drug-drug interaction (DDI) potential during drug development. However, due to the long half-life and narrow dynamic range of 4 β -HC, its use has been limited to the identification of CYP3A inducers, but not CYP3A inhibitors. The formation of 1 β -hydroxydeoxycholic acid (1 β -OH DCA) from deoxycholic acid (DCA) is mediated by CYP3A, thus 1 β -OH DCA can potentially serve as an alternative to 4 β -HC for assessment of CYP3A DDI potential. To study this feasibility, we developed a sensitive liquid chromatography-tandem mass spectrometry method for the simultaneous quantitation of 1 β -OH DCA and its glycine and taurine conjugates in human plasma with the lower limit of quantitation of 50 pg/ml, which enabled the quantitation of basal levels and further reduction. The method was applied to a DDI study to assess how 1 β -OH DCA and its glycine and taurine conjugates would respond to CYP3A induction or inhibition. Rifampin induction resulted in an increase of 1 β -OH DCA and its conjugates in plasma, with 6.8-, 7.8-, 8.3-, and 10.3-fold increases of area under the curve from the time of dosing to the last measurable concentration (AUC LST ), area under the curve from the time of dosing to 24 hours (AUC 24h ), C max , and mean concentrations for total 1 β -OH DCA (total of all three forms), respectively. Importantly, inhibition with itraconazole resulted in notable reduction of these biomarkers, with 84%, 85%, 82%, and 81% reductions of AUC LST , AUC 24h , C max , and mean concentrations for total 1 β -OH DCA, respectively. These preliminary data demonstrate for the first time that total 1 β -OH DCA in plasma has the potential to serve as a biomarker for CYP3A DDI assessment in early clinical development and may provide key advantages over 4 β -HC. SIGNIFICANCE STATEMENT: The authors have reported the use of total 1 β -hydroxydeoxycholic acid (1 β -OH DCA) (sum of 1 β -OH DCA and its glycine and taurine conjugates) plasma exposure as a biomarker for CYP3A activity. Itraconazole inhibition led to an 81%-85% decrease of total 1 β -OH DCA plasma exposures, whereas rifampin induction led to a 6.8- to 10.3-fold increase of total 1 β -OH DCA plasma exposures. Using 1 β -OH DCA exposures in plasma also provides the benefit of allowing pharmacokinetic and biomarker assessment using the same matrix., (Copyright © 2024 by The American Society for Pharmacology and Experimental Therapeutics.)

GST-HG171 is a potent, broad-spectrum, orally bioavailable small-molecule 3C-like (3CL) protease inhibitor that was recently approved for treating mild to moderate coronavirus disease 2019 patients in China. Since cytochrome P450 (CYP) enzymes, primarily CYP3A, are the main metabolic enzymes of GST-HG171, hepatic impairment may affect its pharmacokinetic (PK) profile. Aiming to guide clinical dosing for patients with hepatic impairment, this study, using a non-randomized, open-label, single-dose design, assessed the impact of hepatic impairment on the PK, safety, and tolerability of GST-HG171. Patients with mild and moderate hepatic impairment along with healthy subjects were enrolled ( n = 8 each), receiving a single oral dose of 150 mg GST-HG171, with concurrent administration of 100 mg ritonavir to sustain CYP3A inhibition before and after GST-HG171 administration (-12, 0, 12, and 24 hours). Compared to subjects with normal hepatic function, the geometric least-squares mean ratios (90% confidence intervals) for GST-HG171's maximum plasma concentration ( C max ), area under the concentration-time curve up to the last quantifiable time (AUC 0- t ), and area under the plasma concentration-time curve from time 0 extrapolated to infinity (AUC 0-∞ ) in subjects with mild hepatic impairment were 1.14 (0.99, 1.31), 1.07 (0.88, 1.30), and 1.07 (0.88, 1.29), respectively. For moderate hepatic impairment, the ratios were 0.87 (0.70, 1.07), 0.82 (0.61, 1.10), and 0.82 (0.61, 1.10), respectively. Hepatic impairment did not significantly alter GST-HG171's peak time ( T max ) and elimination half-life ( T 1/2 ). GST-HG171 exhibited good safety and tolerability in the study. Taken together, mild to moderate hepatic impairment minimally impacted GST-HG171 exposure, suggesting no need to adjust GST-HG171 dosage for patients with mild to moderate hepatic impairment in the clinic.Clinical TrialsRegistered at ClinicalTrials.gov (NCT06106113)., Competing Interests: The authors declare no conflict of interest.

Background: In clinical practice, the vast array of potential drug combinations necessitates swift and accurate assessments of pharmacokinetic drug-drug interactions (DDIs), along with recommendations for adjustments. Current methodologies for clinical DDI evaluations primarily rely on basic extrapolations from clinical trial data. However, these methods are limited in accuracy owing to their lack of a comprehensive consideration of various critical factors, including the inhibitory potency, dosage, and type of the inhibitor, as well as the metabolic fraction and intestinal availability of the substrate., Objective: This study aims to propose an efficient and accurate clinical pharmacokinetic-mediated DDI assessment tool, which comprehensively considers the effects of inhibitory potency and dosage of inhibitors, intestinal availability and fraction metabolized of substrates on DDI outcomes., Methods: This study focuses on DDIs caused by cytochrome P450 3A4 enzyme inhibition, utilizing extensive clinical trial data to establish a methodology to calculate the metabolic fraction and intestinal availability for substrates, as well as the concentration and inhibitory potency for inhibitors ( K i or k inact / K I ). These parameters were then used to predict the outcomes of DDIs involving 33 substrates and 20 inhibitors. We also defined the risk index for substrates and the potency index for inhibitors to establish a clinical DDI risk scale. The training set for parameter calculation consisted of 73 clinical trials. The validation set comprised 89 clinical DDI trials involving 53 drugs. which was used to evaluate the reliability of in vivo values of K i and k inact / K I , the accuracy of DDI predictions, and the false-negative rate of risk scale., Results: First, the reliability of the in vivo K i and k inact / K I values calculated in this study was assessed using a basic static model. Compared with values obtained from other methods, this study values showed a lower geometric mean fold error and root mean square error. Additionally, incorporating these values into the physiologically based pharmacokinetic-DDI model facilitated a good fitting of the C-t curves when the substrate's metabolic enzymes are inhibited. Second, area under the curve ratio predictions of studied drugs were within a 1.5 × margin of error in 81% of cases compared with clinical observations in the validation set. Last, the clinical DDI risk scale developed in this study predicted the actual risks in the validation set with only a 5.6% incidence of serious false negatives., Conclusions: This study offers a rapid and accurate approach for assessing the risk of pharmacokinetic-mediated DDIs in clinical practice, providing a foundation for rational combination drug use and dosage adjustments., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

A physiologically-based pharmacokinetic (PBPK) model for tipifarnib, which included mechanistic absorption, was built and verified by integrating in vitro data and several clinical data in healthy subjects and cancer patients. The final PBPK model was able to recover the clinically observed single and multiple-dose plasma concentrations of tipifarnib in healthy subjects and cancer patients under several dosing conditions, such as co-administration with a strong CYP3A4 inhibitor and inducer, an acid-reducing agent (proton pump inhibitor and H2 receptor antagonist), and with a high-fat meal. In addition, the model was able to accurately predict the effect of mild or moderate hepatic impairment on tipifarnib exposure. The appropriately verified model was applied to prospectively simulate the liability of tipifarnib as a victim of CYP3A4 enzyme-based drug-drug interactions (DDIs) with a moderate inhibitor and inducer as well as tipifarnib as a perpetrator of DDIs with sensitive substrates of CYP3A4, CYP2B6, CYP2D6, CYP2C9, and CYP2C19 in healthy subjects and cancer patients. The effect of a high-fat meal, acid-reducing agent, and formulation change at the therapeutic dose was simulated. Finally, the model was used to predict the effect of mild, moderate, or severe hepatic, and renal impairment on tipifarnib PK. This multipronged approach of combining the available clinical data with PBPK modeling-guided dosing recommendations for tipifarnib under several conditions. This example showcases the totality of the data approach to gain a more thorough understanding of clinical pharmacology and biopharmaceutic properties of oncology drugs in development., (© 2024 The Author(s). CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

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., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Cytochrome P450 (CYP) 3A4 is an enzyme involved in the metabolism of many drugs that are currently on the market and is therefore a key player in drug-drug interactions (DDIs). ACT-1004-1239 is a potent and selective, first-in-class ACKR3/CXRC7 antagonist being developed as a treatment for demyelinating diseases including multiple sclerosis. Based on the human absorption, distribution, metabolism, and excretion (ADME) study results, ACT-1004-1239 is predominantly metabolized by CYP3A4. This study investigated the effect of the strong CYP3A4 inhibitor, itraconazole, on the pharmacokinetics of single-dose ACT-1004-1239 in healthy male subjects. In the open-label, fixed-sequence DDI study, a total of 16 subjects were treated. Each subject received a single dose of 10 mg ACT-1004-1239 (Treatment A) in the first period followed by concomitant administration of multiple doses of 200 mg itraconazole and a single dose of 10 mg ACT-1004-1239 in the second period. We report a median of difference in t max (90% confidence interval, CI) of 0.5 h (0.0, 1.0) comparing both treatments. The geometric mean ratio (GMR) (90% CI) of C max and AUC 0-∞ was 2.16 (1.89, 2.47) and 2.77 (2.55, 3.00), respectively. The GMR (90% CI) of t 1/2 was 1.46 (1.26, 1.70). Both treatments were well-tolerated with an identical incidence in subjects reporting treatment-emergent adverse events (TEAE). The most frequently reported TEAEs were headache and nausea. In conclusion, ACT-1004-1239 is classified as a moderately sensitive CYP3A4 substrate (i.e., increase of AUC ≥2- to <5-fold), and this should be considered in further clinical studies if CYP3A4 inhibitors are concomitantly administered., (© 2024 Idorsia Pharmaceuticals Ltd. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Dasatinib, a second-generation tyrosine kinase inhibitor, is approved for treating chronic myeloid and acute lymphoblastic leukemia. As a sensitive cytochrome P450 (CYP) 3A4 substrate and weak base with strong pH-sensitive solubility, dasatinib is susceptible to enzyme-mediated drug-drug interactions (DDIs) with CYP3A4 perpetrators and pH-dependent DDIs with acid-reducing agents. This work aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) model of dasatinib to describe and predict enzyme-mediated and pH-dependent DDIs, to evaluate the impact of strong and moderate CYP3A4 inhibitors and inducers on dasatinib exposure and to support optimized dasatinib dosing. Overall, 63 plasma profiles from perorally administered dasatinib in healthy volunteers and cancer patients were used for model development. The model accurately described and predicted plasma profiles with geometric mean fold errors (GMFEs) for area under the concentration-time curve from the first to the last timepoint of measurement (AUC last ) and maximum plasma concentration (C max ) of 1.27 and 1.29, respectively. Regarding the DDI studies used for model development, all (8/8) predicted AUC last and C max ratios were within twofold of observed ratios. Application of the PBPK model for dose adaptations within various DDIs revealed dasatinib dose reductions of 50%-80% for strong and 0%-70% for moderate CYP3A4 inhibitors and a 2.3-3.1-fold increase of the daily dasatinib dose for CYP3A4 inducers to match the exposure of dasatinib administered alone. The developed model can be further employed to personalize dasatinib therapy, thereby help coping with clinical challenges resulting from DDIs and patient-related factors, such as elevated gastric pH., (© 2024 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Maribavir, an orally available antiviral agent, has been approved in multiple countries for the treatment of patients with refractory post-transplant cytomegalovirus (CMV) infection and/or disease. Maribavir is primarily metabolized by CYP3A4; coadministration with CYP3A4 inducers and inhibitors may significantly alter maribavir exposure, thereby affecting its efficacy and safety. The effect of CYP3A4 inducers and inhibitors on maribavir exposure was evaluated based on a drug-drug interaction (DDI) study and physiologically-based pharmacokinetic (PBPK) modeling. The effect of rifampin (a strong inducer of CYP3A4 and moderate inducer of CYP1A2), administered at a 600 mg dose once daily, on maribavir pharmacokinetics was assessed in a clinical phase 1 DDI study in healthy participants. A full PBPK model for maribavir was developed and verified using in vitro and clinical pharmacokinetic data from phase 1 studies. The verified PBPK model was then used to simulate maribavir DDI interactions with various CYP3A4 inducers and inhibitors. The DDI study results showed that coadministration with rifampin decreased the maribavir maximum plasma concentration (C max ), area under the plasma concentration-time curve (AUC), and trough concentration (C trough ) by 39%, 60%, and 82%, respectively. Based on the results from the clinical DDI study, the coadministration of maribavir with rifampin is not recommended. The PBPK model did not predict a clinically significant effect of CYP3A4 inhibitors on maribavir exposure; however, it predicted that strong or moderate CYP3A4 inducers, including carbamazepine, efavirenz, phenobarbital, and phenytoin, may reduce maribavir exposure to a clinically significant extent, and may prompt the consideration of a maribavir dosing increase, in accordance with local approved labels and/or regulations., (© 2023 American College of Clinical Pharmacology.)

Avacopan, a complement 5a receptor (C5aR) antagonist approved for treating severe active antineutrophil cytoplasmic autoantibody (ANCA)-associated vasculitis, was evaluated in 2 clinical drug-drug interaction studies. The studies assessed the impact of avacopan on the pharmacokinetics (PK) of CYP3A4 substrates midazolam and simvastatin and CYP2C9 substrate celecoxib, and the influence of CYP3A4 inhibitor itraconazole and inducer rifampin on the PKs of avacopan. The results indicated that twice-daily oral administration of 30 mg of avacopan increased the area under the curve (AUC) of midazolam by 1.81-fold and celecoxib by 1.15-fold when administered without food, and twice-daily oral administration of 30 or 60 mg of avacopan increased the AUC of simvastatin by approximately 2.6-3.5-fold and the AUC of the active metabolite β-hydroxy-simvastatin acid by approximately 1.4-1.7-fold when co-administered with food. Furthermore, the AUC of avacopan increased by approximately 2.19-fold when co-administered with itraconazole and decreased by approximately 13.5-fold when co-administered with rifampin. These findings provide critical insights into the potential drug-drug interactions involving avacopan, which could have significant implications for patient care and treatment planning. (NCT06207682)., (© 2024, The American College of Clinical Pharmacology.)

This open-label, two-part, phase Ib drug-drug interaction study investigated whether the pharmacokinetic (PK) and safety profiles of lurbinectedin (LRB), a marine-derived drug, are affected by co-administration of itraconazole (ITZ), a strong CYP3A4 inhibitor, in adult patients with advanced solid tumors. In Part A, three patients were sequentially assigned to Sequence 1 (LRB 0.8 mg/m 2 , 1-h intravenous [IV] + ITZ 200 mg/day oral in Cycle 1 [C1] and LRB alone 3.2 mg/m 2 , 1 h, IV in Cycle 2 [C2]). In Part B, 11 patients were randomized (1:1) to receive either Sequence 1 (LRB at 0.9 mg/m 2 + ITZ in C1 and LRB alone in C2) or Sequence 2 (LRB alone in C1 and LRB + ITZ in C2). Eleven patients were evaluable for PK analysis: three in Part A and eight in Part B (four per sequence). The systemic total exposure of LRB increased with ITZ co-administration: 15% for C max , area under the curve (AUC) 2.4-fold for AUC 0-t and 2.7-fold for AUC 0-∞ . Co-administration with ITZ produced statistically significant modifications in the unbound plasma LRB PK parameters. The LRB safety profile was consistent with the toxicities described in previous studies. Co-administration with multiple doses of ITZ significantly altered LRB systemic exposure. Hence, to avoid LRB overexposure when co-administered with strong CYP3A4 inhibitors, an LRB dose reduction proportional to CL reduction should be applied.

Oxycodone is one of the most commonly used opioids to treat moderate to severe pain. It is metabolized mainly by CYP3A4 and CYP2D6, while only a small fraction of the dose is excreted unchanged into the urine. Oxymorphone, the metabolite primarily formed by CYP2D6, has a 40- to 60-fold higher mu-opioid receptor affinity than the parent compound. While CYP2D6-mediated gene-drug-interactions (GDIs) and drug-drug interactions (DDIs) are well-studied, they only account for a portion of the variability in oxycodone and oxymorphone exposure. The combined impact of CYP2D6-mediated GDIs and DDIs, CYP3A4-mediated DDIs, and UGT2B7 GDIs is not fully understood yet and hard to study in head-to-head clinical trials given the relatively large number of scenarios. Instead, we propose the use of a physiologically-based pharmacokinetic model that integrates available information on oxycodone's metabolism to characterize and predict the impact of DDIs and GDIs on the exposure of oxycodone and its major, pharmacologically-active metabolite oxymorphone. To this end, we first developed and verified a PBPK model for oxycodone and its metabolites using published clinical data. The verified model was then applied to determine the dose-exposure relationship of oxycodone and oxymorphone stratified by CYP2D6 and UGT2B7 phenotypes respectively, and administered perpetrators of CYP-based drug interactions. Our simulations demonstrate that the combination of CYP2D6 UM and a UGT2B7Y (268) mutation may lead to a 2.3-fold increase in oxymorphone exposure compared to individuals who are phenotyped as CYP2D6 NM / UGT2B7 NM. The extent of oxymorphone exposure increases up to 3.2-fold in individuals concurrently taking CYP3A4 inhibitors, such as ketoconazole. Inhibition of the CYP3A4 pathway results in a relative increase in the partial metabolic clearance of oxycodone to oxymorphone. Oxymorphone is impacted to a higher extent by GDIs and DDIs than oxycodone. We predict oxymorphone exposure to be highest in CYP2D6 UMs/UGT2B7 PMs in the presence of ketoconazole (strong CYP3A4 index inhibitor) and lowest in CYP2D6 PMs/UGT2B7 NMs in the presence of rifampicin (strong CYP3A4 index inducer) covering a 55-fold exposure range., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023. Published by Elsevier B.V.)

Mosunetuzumab is a CD3/CD20 bispecific antibody. As an on-target effect, transient elevation of interleukin-6 (IL-6) occurs in early treatment cycles. A physiologically-based pharmacokinetic (PBPK) model was developed to assess potential drug interaction caused by IL-6 enzyme suppression on cytochrome P450 3A (CYP3A) during mosunetuzumab treatment. The model's performance in predicting IL-6 CYP3A suppression and subsequent drug-drug interactions (DDIs) was verified using existing clinical data of DDIs caused by chronic and transient IL-6 elevation. Sensitivity analyses were performed for a complete DDI risk assessment. The IL-6 concentration- and time-dependent CYP3A suppression during mosunetuzumab treatment was simulated using PBPK model with incorporation of in vitro IL-6 inhibition data. At clinically approved doses/regimens, the DDI at maximum CYP3A suppression was predicted to be a midazolam maximum drug concentration in plasma (C max ) and area under the plasma drug concentration-time curve (AUC) ratio of 1.17 and 1.37, respectively. At the 95th percentile of IL-6 concentration level or when gut CYP3A suppression was considered, the predicted DDI risk for mosunetuzumab remained low (<2-fold). The PBPK-based DDI predictions informed the mosunetuzumab product label to monitor, in early cycles, the concentrations and toxicities for sensitive CYP3A substrates with narrow therapeutic windows., (© 2023 Genentech. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model to predict changes in the pharmacokinetics (PK) and pharmacodynamics (PD, PDE4 inhibition) of roflumilast (ROF) and ROF N-oxide when co-administered with eight CYP3A4/1A2 perpetrators. The population PBPK model of ROF and ROF N-oxide has been successfully developed and validated based on the four clinical PK studies and five clinical drug-drug interactions (DDIs) studies. In PK simulations, every ratio of prediction to observation for PK parameters fell within the range 0.7 to 1.5. In DDI simulations, except for tow peak concentration ratios (C max ) of ROF with rifampicin (prediction: 0.63 vs. observation: 0.19) and with cimetidine (prediction: 1.07 vs. observation: 1.85), the remaining predicted ratios closely matched the observed ratios. Additionally, the PBPK model suggested that co-administration with the three perpetrators (cimetidine, enoxacin, and fluconazole) may use with caution, with CYP3A4 strong inhibitor (ketoconazole and itraconazole) or with dual CYP3A41A2 inhibitor (fluvoxamine) may reduce to half-dosage or use with caution, while co-administration with CYP3A4 strong or moderate inducer (rifampicin, efavirenz) should avoid. Overall, the present PBPK model can provide recommendations for adjusting dosing regimens in the presence of DDIs., (© 2023. The Author(s).)

The antiarrhythmic agent quinidine is a potent inhibitor of cytochrome P450 (CYP) 2D6 and P-glycoprotein (P-gp) and is therefore recommended for use in clinical drug-drug interaction (DDI) studies. However, as quinidine is also a substrate of CYP3A4 and P-gp, it is susceptible to DDIs involving these proteins. Physiologically-based pharmacokinetic (PBPK) modeling can help to mechanistically assess the absorption, distribution, metabolism, and excretion processes of a drug and has proven its usefulness in predicting even complex interaction scenarios. The objectives of the presented work were to develop a PBPK model of quinidine and to integrate the model into a comprehensive drug-drug(-gene) interaction (DD(G)I) network with a diverse set of CYP3A4 and P-gp perpetrators as well as CYP2D6 and P-gp victims. The quinidine parent-metabolite model including 3-hydroxyquinidine was developed using pharmacokinetic profiles from clinical studies after intravenous and oral administration covering a broad dosing range (0.1-600 mg). The model covers efflux transport via P-gp and metabolic transformation to either 3-hydroxyquinidine or unspecified metabolites via CYP3A4. The 3-hydroxyquinidine model includes further metabolism by CYP3A4 as well as an unspecific hepatic clearance. Model performance was assessed graphically and quantitatively with greater than 90% of predicted pharmacokinetic parameters within two-fold of corresponding observed values. The model was successfully used to simulate various DD(G)I scenarios with greater than 90% of predicted DD(G)I pharmacokinetic parameter ratios within two-fold prediction success limits. The presented network will be provided to the research community and can be extended to include further perpetrators, victims, and targets, to support investigations of DD(G)Is., (© 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Itraconazole is a potent inhibitor of cytochrome P450 3A4 (CYP3A4), associated with numerous drug-drug interactions (DDI). PUR1900, a dry powder formulation of itraconazole for oral inhalation, results in high lung and low systemic exposure. This project used physiologically based pharmacokinetic (PBPK) modeling to assess the DDI potential of inhaled PUR1900, using midazolam as a "victim drug." The basic and mechanistic static models evaluated the DDI potential of PUR1900, assuming 5 mg of midazolam coadministration at steady-state itraconazole exposure. Subsequently, Simcyp® PBPK simulation software and pharmacokinetic data from a Phase 1 clinical trial with PUR1900 (NCT03479411) were used to optimize an existing itraconazole PBPK model. The model was applied to investigate the potential for CYP3A4 DDI when 5 mg of midazolam is co-administered with inhaled PUR1900 at a steady state in a virtual healthy population at PUR1900 doses up to 40 mg per day. The basic static and mechanistic static models suggested a strong likelihood for DDI with inhaled PUR1900. The PBPK model was consistent with PUR1900 Phase 1 trial data. The geometric mean C max and AUC ratios of midazolam at a maximum dose of 40 mg PUR1900 were 1.14 and 1.26, respectively, indicating a minimal likelihood of DDI with inhaled PUR1900. The low systemic exposure of itraconazole when administered as PUR1900 results in minimal to no CYP3A4 inhibition, reducing the concern of drug-drug interactions. As the risk of CYP3A4 DDI is predicted to be significantly lower when itraconazole is administered via oral inhalation as PUR1900, it is likely that PUR1900 can be safely used for the treatment of pulmonary fungal infections in patients taking pharmaceuticals currently contraindicated with oral itraconazole., (© 2023. The Author(s).)

Encorafenib, a potent BRAF kinase inhibitor gets significantly metabolised by CYP3A4 (83%) and CYP2C19 (16%) and is a substrate for P-glycoprotein (P-gp). Due to significant metabolism by CYP3A4, encorafenib exposure can increase in hepatic and renal impairment and may lead to altered magnitude of drug-drug interactions (DDI). Hence, it is necessary to assess the exposures & DDI's in impaired population.Physiologically based pharmacokinetic modelling (PBPK) was utilised to determine the exposures of encorafenib in hepatic and renal impairment along with altered DDI's. Prospective DDI's were predicted with USFDA recommended clinical CYP3A4, CYP2C19, P-gp inhibitors and CYP3A4 inducers.PBPK models for encorafenib, perpetrators simulated PK parameters within 2-folds error. Encorafenib exposures significantly increased in hepatic as compared to renal impairment because of reduced CYP3A4 levels.Hepatic impairment caused changes in inhibition and induction DDI's, when compared to healthy population. Renal impairment did not cause significant changes in DDIs except for itraconazole. P-gp, CYP2C19 inhibitors did not result in altered DDI's. The DDI's were found to have insignificant correlation with relative exposure increase of perpetrators in case of impairment. Overall, this work signifies use of PBPK modelling for DDI's evaluations in hepatic and renal impairment populations.

Encorafenib, a potent BRAF kinase inhibitor undergoes significant metabolism by CYP3A4 (83%) and CYP2C19 (16%) and also a substrate of P-glycoprotein (P-gp). Because of this, encorafenib possesses potential for enzyme-transporter related interactions. Clinically, its drug-drug interactions (DDIs) with CYP3A4 inhibitors (posaconazole, diltiazem) were reported and hence there is a necessity to study DDIs with multiple enzyme inhibitors, inducers, and P-gp inhibitors.USFDA recommended clinical CYP3A4, CYP2C19, P-gp inhibitors, CYP3A4 inducers were selected and prospective DDIs were simulated using physiologically based pharmacokinetic modelling (PBPK). Impact of dose (50 mg vs. 300 mg) and staggering of administrations (0-10 h) on the DDIs were predicted.PBPK models for encorafenib, perpetrators simulated PK parameters within twofold prediction error. Clinically reported DDIs with posaconazole and diltiazem were successfully predicted.CYP2C19 inhibitors did not result in significant DDI whereas strong CYP3A4 inhibitors resulted in DDI ratio up to 4.5. Combining CYP3A4, CYP2C19 inhibitors yielded DDI equivalent CYP3A4 alone. Strong CYP3A4 inducers yielded DDI ratio up to 0.3 and no impact of P-gp inhibitors on DDIs was observed. The DDIs were not impacted by dose and staggering of administration. Overall, this work indicated significance of PBPK modelling for evaluating clinical DDIs with enzymes, transporters and interplay.

Vonoprazan is metabolized extensively through CYP3A and is an in vitro time-dependent inhibitor of CYP3A. A tiered approach was applied to understand the CYP3A victim and perpetrator drug-drug interaction (DDI) potential for vonoprazan. Mechanistic static modeling suggested vonoprazan is a potential clinically relevant CYP3A inhibitor. Thus, a clinical study was conducted to evaluate the impact of vonoprazan on the exposure of oral midazolam, an index substrate for CYP3A. A physiologically-based pharmacokinetic (PBPK) model for vonoprazan was also developed using in vitro data, drug- and system-specific parameters, and clinical data and observations from a [ 14 C] human absorption, distribution, metabolism, and excretion study. The PBPK model was refined and verified using data from a clinical DDI study with the strong CYP3A inhibitor, clarithromycin, to confirm the fraction metabolized by CYP3A, and the oral midazolam clinical DDI data assessing vonoprazan as a time-dependent inhibitor of CYP3A. The verified PBPK model was applied to simulate the anticipated changes in vonoprazan exposure due to moderate and strong CYP3A inducers (efavirenz and rifampin, respectively). The clinical midazolam DDI study indicated weak inhibition of CYP3A, with a less than twofold increase in midazolam exposure. PBPK simulations projected a 50% to 80% reduction in vonoprazan exposure when administered concomitantly with moderate or strong CYP3A inducers. Based on these results, the vonoprazan label was revised and states that lower doses of sensitive CYP3A substrates with a narrow therapeutic index should be used when administered concomitantly with vonoprazan, and co-administration with moderate and strong CYP3A inducers should be avoided., (© 2023 Phathom Pharmaceuticals and The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Purpose: This study aimed to investigate the drug-drug interactions of ponatinib with strong, moderate, or weak CYP3A4 inhibitors/inducers by developing physiologically based pharmacokinetic (PBPK) models., Methods: Simcyp ® Ver 20.1 (Certara Inc., Sheffield, UK) was used to construct a PBPK model for ponatinib and to predict its interaction with strong, moderate, or weak CYP3A4 inhibitors/inducers. The constructed model was validated by comparing predicted values with actual observed values. Inhibitors or inducers that increased or decreased the area under the plasma concentration curve of ponatinib by more than two-fold when used in combination were considered significant., Results: The PBPK model of ponatinib accurately represented its oral pharmacokinetics. It also reasonably predicted its pharmacokinetics when combined with ketoconazole and rifampicin. No weak to strong CYP3A4 inhibitor combinations significantly increased the AUC of ponatinib. However, the strong CYP3A4 inducers rifampicin (oral, 600 mg QD) and phenytoin (oral, 100 mg TID) decreased AUC by 60-70% and 50%, respectively., Conclusions: The PBPK model predicted a significant drug interaction when ponatinib was combined with a strong CYP3A4 inducer. Conversely, the combination with weak-to-strong CYP3A4 inhibitors did not suggest a drug interaction with ponatinib., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: To develop a mathematical model combined between physiologically based pharmacokinetic and BTK occupancy (PBPK-BO) to simultaneously predict pharmacokinetic (PK) and pharmacodynamic (PD) changes of acalabrutinib (ACA) and active metabolite ACP-5862 in healthy humans as well as PD in patients. Next, to use the PBPK-BO to determine the optimal dosing regimens in patients alone, with different CYP3A4 variants, when co-administration with four CYP3A4 modulators and in patients with hepatic impairment, respectively., Methods: The PBPK-BO model was built using physicochemical and biochemical properties of ACA and ACP-5862 and then verified by observed PK and PD data from healthy humans and patients. Finally, the model was applied to determine optimal dosing regimens in various clinical situations., Results: The simulations demonstrated that 100 mg ACA twice daily (BID) was the optimal dosing regimen in patients alone. Additionally, dosage regimens might be reduced to 50 mg BID in patients with five CYP3A4 variants. Moreover, the dosing regimen should be modified to 100 mg (even to 50 mg) once daily (QD) when co-administration with erythromycin or clarithromycin, and be increased to 200 mg BID with rifampicin, and but be avoided co-administration with itraconazole. Furthermore, dosage regimen simulations showed that optimal dosing might be decreased to 50 mg BID in patients with mild and moderate hepatic impairment, and be avoided taking ACA in severely hepatically impaired patients., Conclusion: This PBPK-BO model can predict PK and PD in healthy humans and patients and also predict the optimal dosing regimens in various clinical situations., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We characterized the impact of chronic kidney disease (CKD) on the cytochrome P450 (CYP) 3A4-mediated metabolism of saxagliptin to its metabolite, 5-hydroxysaxagliptin, using a physiologically based pharmacokinetic (PBPK) model. A PBPK model of saxagliptin and its CYP3A4 metabolite, 5-hydroxysaxagliptin, was constructed and validated for oral doses ranging from 5 to 100 mg. The observed ratios of area under the plasma concentration-time curve (AUC) and maximum plasma concentration (C max ) between healthy subjects and subjects with CKD were compared with those predicted using PBPK model simulations. Simulations were performed with virtual CKD populations having decreased CYP3A4 activity (ie, 64%-75% of the healthy subjects' CYP3A4 abundance) and preserved CYP3A4 activity (ie, 100% of the healthy subjects' CYP3A4 abundance). We found that simulations using decreased CYP3A4 activity generally overpredicted the ratios of saxagliptin AUC and C max in CKD compared with those using preserved CYP3A4 activity. Similarly, simulations using decreased CYP3A4 activity underpredicted the ratio of 5-hydroxysaxagliptin AUC in moderate and severe CKD compared with simulations using preserved CYP3A4 activity. These findings suggest that decreased CYP3A4 activity in CKD underpredicts saxagliptin clearance compared with that observed clinically. Preserving CYP3A4 activity in CKD more closely estimates saxagliptin clearance and 5-hydroxysaxagliptin exposure changes observed in vivo. Our findings suggest that there is no clinically meaningful impact of CKD on the metabolism of saxagliptin by CYP3A4. Since saxagliptin is not a highly sensitive substrate and validated probe for CYP3A4, this work represents a case study of a CYP3A4 substrate-metabolite pair and is not a generalization for all CYP3A4 substrates., (© 2022 The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals LLC on behalf of American College of Clinical Pharmacology.)

Youkenafil is a novel selective phosphodiesterase type 5 inhibitor to treat erectile dysfunction. In order to study the drug-drug interactions of youkenafil, in vitro experiments were conducted with human liver microsomes and recombinant isoenzymes to identify the effect of cytochrome P450 (CYP) enzymes on the metabolism of youkenafil. Then two clinical studies were performed to investigate the effects of itraconazole and rifampicin (potent CYP3A4/5 inhibitor and inducer, respectively) on the pharmacokinetics of youkenafil and its main metabolite, N-desethyl youkenafil (M1). Each study enrolled thirty healthy male subjects. In study 1, subjects were given a single dose of youkenafil (50 mg on Days 1 and 13) and multiple doses of itraconazole (200 mg once daily from Days 6 to 14). In study 2, subjects were given a single dose of youkenafil (100 mg on Days 1 and 20) and multiple doses of rifampicin (600 mg once daily from Days 6 to 20). The results showed that youkenafil was mainly metabolized through CYP3A4/5 in vitro. Itraconazole increased youkenafil AUC and C max by about 12- and 6-fold, respectively, and increased M1 AUC and C max by 5- and 1.3-fold, respectively. Conversely, rifampicin reduced youkenafil AUC and C max both by about 98%. It did not change the AUC of M1 significantly, but increased the C max by 30%. All treatments were well tolerated by subjects in both studies. Therefore, co-administration of youkenafil with potent inhibitors or inducers of CYP3A4/5 should be avoided or carefully monitored., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Purpose: Venetoclax (VEN), an anti-tumor drug that is a substrate of cytochrome P450 3A enzyme (CYP3A4), is used to treat leukemia. Voriconazole (VCZ) is an antifungal medication that inhibits CYP3A4. The goal of this study is to predict the effect of VCZ on VEN exposure., Method: Two physiological based pharmacokinetics (PBPK) models were developed for VCZ and VEN using the bottom-up and top-down method. VCZ model was also developed to describe the effect of CYP2C19 polymorphism on its pharmacokinetics (PK). The reversible inhibition constant (K i ) of VCZ for CYP3A4 was calibrated using drug-drug interaction (DDI) data of midazolam and VCZ. The clinical verified VCZ and VEN model were used to predict the DDI of VCZ and VEN at clinical dosing scenario., Result: VCZ model predicted VCZ exposure in the subjects of different CYP2C19 genotype and DDI related fold changes of sensitive CYP3A substrate with acceptable prediction error. VEN model can capture PK of VEN with acceptable prediction error. The DDI PBPK model predicted that VCZ increased the exposure of VEN by 4.5-9.6 fold. The increase in VEN exposure by VCZ was influenced by subject's CYP2C19 genotype. According to the therapeutic window, VEN dose should be reduced to 100 mg when co-administered with VCZ., Conclusion: The PBPK model developed here could support individual dose adjustment of VEN and DDI risk assessment. Predictions using the robust PBPK model confirmed that the 100 mg dose adjustment is still applicable in the presence of VCZ with high inter-individual viability., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Certain drugs inherently have unfavourable pharmacokinetic properties; for example, they are poorly absorbed or broken down too quickly in the liver. In some cases, the addition of a pharmacokinetic excipient, thus deliberately causing an interaction, may offer a solution. To date, this concept has been most widely applied in HIV treatment where addition of the CYP3A inhibitors ritonavir and cobicistat greatly increases plasma levels of other HIV medications. For the same reason, ritonavir has been added to the new oral antiviral drug against the SARS CoV-2 virus, nirmatrelvir. In addition to a better and/or longer effect, theoretically lower doses can also be used, resulting in cost savings. Deliberately inducing a pharmacokinetic interaction is not without risk: after all, interactions with other CYP3A substrates can also occur. Nevertheless, we believe that with good interaction management, CYP3A inhibitors can be used safely with benefits for patients and society.

Anlotinib is a small molecule of novel tyrosine kinase inhibitor initially approved to treat non-small cell lung cancer in China. Drug-drug interaction (DDI) is an extrinsic factor important for the appropriate use of anlotinib in clinical practice. In vitro experiments demonstrated that anlotinib is a substrate of cytochrome P450 (CYP) enzymes and moderate inhibitor of several common ones; however, no clinical DDI studies have been performed to investigate inhibitory effects of anlotinib on these CYP enzymes. Thus, its drug label recommends avoiding co-administration with substrates of these enzymes, which have narrow therapeutic windows. In this study, we performed a CYP450 inhibition study, followed by gathering in vitro and clinical pharmacokinetic data to build the first physiologically based pharmacokinetic (PBPK) model of anlotinib. The verified model was subsequently used to predict the DDI mediated by anlotinib. As a result, the marginal plasma exposure changes of typical CYP3A and CYP2C9 substrates were less than the bioequivalence threshold, indicating that anlotinib has a very low potential of causing clinically meaningful DDI through the inhibition of several major CYP enzymes. According to the FDA's latest guideline on DDI, the established model with the simulation results may support the revision of anlotinib labelling without further clinical studies, lifting unnecessary restrictions on anlotinib regimens., (© 2022 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society). Published by John Wiley & Sons Ltd.)

Idasanutlin is a potent inhibitor of the p53-MDM2 interaction that enables reactivation of the p53 pathway, which induces cell cycle arrest and/or apoptosis in tumor cells expressing functional p53. It was investigated for the treatment of solid tumors and several hematologic indications such as relapsed/refractory acute myeloid leukemia, polycythemia vera, or non-Hodgkin lymphoma. For safety reasons, it cannot be given in healthy volunteers for drug-drug interaction (DDI) explorations. This triggered the need for in silico explorations on top of the one available CYP3A clinical DDI study with posaconazole in solid tumor patients. Idasanutlin's clearance is dependent on CYP3A4/2C8 forming its major circulating metabolite M4, with contributions from UGT1A3 and biliary excretion. Idasanutlin and M4 have low permeability, very low clearance, and extremely low unbound fraction in plasma (<0.001), which makes in vitro data showing inhibition on CYP3A4/2C8 enzymes challenging to translate to clinical relevance. Physiologically-based pharmacokinetic models of idasanutlin and M4 have been established to simulate perpetrator and victim DDI scenarios and to evaluate whether further DDI studies in oncology patients are necessary. Modeling indicated that idasanutlin and M4 would show no or weak clinical inhibition of selective CYP3A4/2C8 substrates. Co-administered strong CYP3A and CYP2C8 inhibitors might lead to weak or moderate idasanutlin exposure increases, and the strong inducer rifampicin might cause moderate exposure reduction. As the simulated idasanutlin systemic exposure changes would be within the range of observed intrinsic variability, the target population can take co-medications that are either CYP2C8/3A4 inhibitors or weak/moderate CYP2C8/3A4 inducers without dose adjustment. SIGNIFICANCE STATEMENT: Clinical trials for idasanutlin are restricted to cancer patients, which imposes practical, scientific, and ethical challenges on drug-drug interaction investigations. Furthermore, idasanutlin and its major circulating metabolite have very challenging profiles of absorption, distribution, metabolism and excretion including high protein binding, low permeability and a combination of different elimination pathways each with extremely low clearance. Nonetheless, physiologically-based pharmacokinetic models could be established and applied for drug-drug interaction risk assessment and were especially useful to provide guidance on concomitant medications in patients., (Copyright © 2022 by The American Society for Pharmacology and Experimental Therapeutics.)

Patients with coronavirus disease 2019 (COVID-19) may experience a cytokine storm with elevated interleukin-6 (IL-6) levels in response to severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). IL-6 suppresses hepatic enzymes, including CYP3A; however, the effect on drug exposure and drug-drug interaction magnitudes of the cytokine storm and resulting elevated IL-6 levels have not been characterized in patients with COVID-19. We used physiologically-based pharmacokinetic (PBPK) modeling to simulate the effect of inflammation on the pharmacokinetics of CYP3A metabolized drugs. A PBPK model was developed for lopinavir boosted with ritonavir (LPV/r), using clinically observed data from people living with HIV (PLWH). The inhibition of CYPs by IL-6 was implemented by a semimechanistic suppression model and verified against clinical data from patients with COVID-19, treated with LPV/r. Subsequently, the verified model was used to simulate the effect of various clinically observed IL-6 levels on the exposure of LPV/r and midazolam, a CYP3A model drug. Clinically observed LPV/r concentrations in PLWH and patients with COVID-19 were predicted within the 95% confidence interval of the simulation results, demonstrating its predictive capability. Simulations indicated a twofold higher LPV exposure in patients with COVID-19 compared with PLWH, whereas ritonavir exposure was predicted to be comparable. Varying IL-6 levels under COVID-19 had only a marginal effect on LPV/r pharmacokinetics according to our model. Simulations showed that a cytokine storm increased the exposure of the CYP3A paradigm substrate midazolam by 40%. Our simulations suggest that CYP3A metabolism is altered in patients with COVID-19 having increased cytokine release. Caution is required when prescribing narrow therapeutic index drugs particularly in the presence of strong CYP3A inhibitors., (© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.)

Purpose: Fuzuloparib (AiRuiYi TM , formerly fluzoparib, SHR3162) is a new orally active poly adenosine diphosphate ribose polymerase (PARP) inhibitor. It has multiple pharmacological activities in breast, ovarian, and prostatic cancer. Fuzuloparib is mainly metabolized through the enzyme CYP3A4 may slow fuzuloparib metabolism and increase its concentrations in blood. We evaluated the pharmacokinetics and tolerability of fuzuloparib by fluconazole, which is a broad antifungal agent and a moderate inhibitor of CYP3A4., Methods: In this study, the effects of CYP3A4 inhibition on the pharmacokinetics of fuzuloparib were assessed in a total of 20 healthy Chinese male subjects in an open-label, two-period, single-sequence, crossover study., Results: Pharmacokinetic parameters, including the maximal plasma concentration (C max ) , the plasma concentration-time curve from time 0 to last measurable area under concentration (AUC 0-t ), and from time 0 to infinity (AUC 0-∞ ), were increased by 32.4%, 104.5%, and 109.6%, with corresponding 90% confidence intervals of (23-43%), (93-116%), and (98-122%), respectively, when fluconazole was combined with fuzuloparib compared to fuzuloparib alone. There was also a slight increase in the incidence of treatment emergent adverse events, including hyperlipidemia and elevated aspartate transaminase., Conclusion: The fuzuloparib is 150 mg b.i.d in clinics use. Our results suggest that fuzuloparib could well be tolerated when administered as a single 20 mg oral dose alone or co-administered with 400 mg fluconazole in healthy male subjects. It is recommended to avoid using moderate CYP3A4 inhibitors together with fuzuloparib or instead of 50 mg when necessary., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background and Objective: Increased glycine availability at the synaptic cleft may enhance N-methyl-D-aspartate receptor signalling and provide a promising therapeutic strategy for cognitive impairment associated with schizophrenia. These studies aimed to assess the pharmacokinetics of BI 425809, a potent glycine-transporter-1 inhibitor, when co-administered with a strong cytochrome P450 3A4 (CYP3A4) inhibitor (itraconazole) and inducer (rifampicin)., Methods: In vitro studies using recombinant CYPs, human liver microsomes, and human hepatocytes were conducted to determine the CYP isoforms responsible for BI 425809 metabolism. In addition, two open-label, fixed-treatment period, phase I studies in healthy male volunteers are described. Period 1: participants received oral BI 425809 25 mg (single dose) on day 1; period 2: participants received multiple doses, across 10 days, of oral itraconazole or rifampicin combined with a single dose of oral BI 425809 25 mg on day 4/7 of the itraconazole/rifampicin treatment, respectively. Pharmacokinetic and safety endpoints were assessed in the absence/presence of itraconazole/rifampicin and included area under the concentration-time curve (AUC) over the time interval 0-167 h (AUC 0‒167 ; itraconazole), 0-168 h (AUC 0‒168 ; rifampicin), or 0-infinity (AUC 0-∞ ; rifampicin and itraconazole), maximum measured concentration (C max ) of BI 425809, and adverse events., Results: In vitro results suggested that CYP3A4 accounted for ≥ 90% of the metabolism of BI 425809. BI 425809 exposure (adjusted geometric mean ratio [%]) was higher in the presence of itraconazole (AUC 0‒167 : 265.3; AUC 0-∞ : 597.0; C max : 116.1) and lower in the presence of rifampicin (AUC 0‒168 : 10.3; AUC 0-∞ : 9.8; C max : 37.4) compared with BI 425809 alone. Investigational treatments were well tolerated., Conclusions: Systemic exposure of BI 425809 was altered in the presence of strong CYP3A4 modulators, corroborating in vitro results that CYP3A4 mediates a major metabolic pathway for BI 425809., Trial Registration Number: NCT02342717 (registered on 15 January 2015) and NCT03082183 (registered on 10 March 2017)., (© 2021. The Author(s).)

The prediction of drug-drug interactions (DDIs) plays critical roles for the estimation of DDI risk caused by inhibition of CYP3A4. The aim of this paper is to develop a physiologically based pharmacokinetic (PBPK)-DDI model for prediction of the DDI co-administrated with ketoconazole in humans and evaluate the predictive performance of the model. The pharmacokinetic and biopharmaceutical properties of 35 approved drugs, as victims, were collected for the development of a PBPK model, which were linked to the PBPK model of ketoconazole for the DDI prediction. The PBPK model of victims and ketoconazole were validated by matching actual in vivo pharmacokinetic data. The predicted results of DDI were compared with actual data to evaluate the predictive performance. The percentage of predicted ratio of AUC (AUCR), C max (C max R), and T max (T max R) was 75%, 69%, and 91%, respectively, which were within the twofold threshold (range, 0.5-2.0×) of the observed values. Only 3% of the predicted AUCRs are obviously underestimated. After integration of the reported fraction of metabolism (f m ) into the PBPK-DDI model for limited four cases, the model-predicted AUCRs were improved from the twofold range of the observed AUCRs to the 90% confidence interval. The developed method could reasonably predict drug-drug interaction with a low risk of underestimation. The present accuracy of the prediction was improved compared with that of static mechanistic models. The evaluation of predictive performance increases the confidence using the model to evaluate the risk of DDIs co-administrated with ketoconazole before the in vivo DDI study., (© 2021. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

Purpose: Knowledge on Ruxolitinib exposure in patients with graft versus host disease (GvHD) is scarce. The purpose of this prospective study was to analyze Ruxolitinib concentrations of GvHD patients and to investigate effects of CYP3A4 and CYP2C9 inhibitors and other covariates as well as concentration-dependent effects., Methods: 262 blood samples of 29 patients with acute or chronic GvHD who were administered Ruxolitinib during clinical routine were analyzed. A population pharmacokinetic model obtained from myelofibrosis patients was adapted to our population and was used to identify relevant pharmacokinetic properties and covariates on drug exposure. Relationships between Ruxolitinib exposure and adverse events were assessed., Results: Median of individual mean trough serum concentrations was 39.9 ng/mL at 10 mg twice daily (IQR 27.1 ng/mL, range 5.6-99.8 ng/mL). Applying a population pharmacokinetic model revealed that concentrations in our cohort were significantly higher compared to myelofibrosis patients receiving the same daily dose (p < 0.001). Increased Ruxolitinib exposure was caused by a significant reduction in Ruxolitinib clearance by approximately 50%. Additional comedication with at least one strong CYP3A4 or CYP2C9 inhibitor led to a further reduction by 15% (p < 0.05). No other covariate affected pharmacokinetics significantly. Mean trough concentrations of patients requiring dose reduction related to adverse events were significantly elevated (p < 0.05)., Conclusion: Ruxolitinib exposure is increased in GvHD patients in comparison to myelofibrosis patients due to reduced clearance and comedication with CYP3A4 or CYP2C9 inhibitors. Elevated Ruxolitinib trough concentrations might be a surrogate for toxicity., (© 2021. The Author(s).)

Purpose: To examine the single- and multiple-dose pharmacokinetics (PK), CYP3A inhibition potential of ipatasertib, and effect of food on PK of ipatasertib in patients with refractory solid tumors and a dedicated food effect assessment in healthy subjects., Methods: The Phase I dose-escalation study enrolled patients with solid tumors in a standard 3 + 3 design with a 1 week washout after the first dose, followed by once-daily dosing on a 3-week-on/1-week-off schedule. In the expansion cohort, the effect of ipatasertib on CYP3A substrate (midazolam) was assessed by examining the change in midazolam exposure when dosed in the absence and presence of steady-state ipatasertib at 600 mg. The effect of food on ipatasertib PK was studied with ipatasertib administered in fed or fasted state (6 patients from Phase I patient study and 18 healthy subjects from the dedicated food effect study)., Results: Ipatasertib was generally well tolerated at doses up to 600 mg given daily for 21 days. Ipatasertib showed rapid absorption (t max , 0.5-3 h), was dose-proportional over a range of 200-800 mg, had a median half-life (range) of 45.0 h (27.8-66.9 h), and had approximately two-fold accumulation following once-daily dosing. Midazolam exposure (AUC 0-∞ ) increased by 2.2-fold in the presence of ipatasertib. PK was comparable in subjects administered ipatasertib in a fed or fasted state., Conclusion: Ipatasertib exhibited rapid absorption and was dose-proportional over a broad dose range. Ipatasertib appeared to be a moderate CYP3A inhibitor when administered at 600 mg and could be administered with or without food in clinical studies., Trail Registration: NCT01090960 (registered March 23, 2010); NCT02536391 (registered August 31, 2015)., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Risdiplam (Evrysdi) improves motor neuron function in patients with spinal muscular atrophy (SMA) and has been approved for the treatment of patients ≥2 months old. Risdiplam exhibits time-dependent inhibition of cytochrome P450 (CYP) 3A in vitro. While many pediatric patients receive risdiplam, a drug-drug interaction (DDI) study in pediatric patients with SMA was not feasible. Therefore, a novel physiologically-based pharmacokinetic (PBPK) model-based strategy was proposed to extrapolate DDI risk from healthy adults to children with SMA in an iterative manner. A clinical DDI study was performed in healthy adults at relevant risdiplam exposures observed in children. Risdiplam caused an 1.11-fold increase in the ratio of midazolam area under the curve with and without risdiplam (AUCR)), suggesting an 18-fold lower in vivo CYP3A inactivation constant compared with the in vitro value. A pediatric PBPK model for risdiplam was validated with independent data and combined with a validated midazolam pediatric PBPK model to extrapolate DDI from adults to pediatric patients with SMA. The impact of selected intestinal and hepatic CYP3A ontogenies on the DDI susceptibility in children relative to adults was investigated. The PBPK analysis suggests that primary CYP3A inhibition by risdiplam occurs in the intestine rather than the liver. The PBPK-predicted risdiplam CYP3A inhibition risk in pediatric patients with SMA aged 2 months-18 years was negligible (midazolam AUCR of 1.09-1.18) and included in the US prescribing information of risdiplam. Comprehensive evaluation of the sensitivity of predicted CYP3A DDI on selected intestinal and hepatic CYP3A ontogeny functions, together with PBPK model-based strategy proposed here, aim to guide and facilitate DDI extrapolations in pediatric populations., (© 2021 F Hoffmann-La Roche AG. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Bictegravir is equally metabolized by cytochrome P450 (CYP)3A and uridine diphosphate-glucuronosyltransferase (UGT)1A1. Drug-drug interaction (DDI) studies were only conducted for strong inhibitors and inducers, leading to some uncertainty whether moderate perpetrators or multiple drug associations can be safely coadministered with bictegravir. We used physiologically-based pharmacokinetic (PBPK) modeling to simulate DDI magnitudes of various scenarios to guide the clinical DDI management of bictegravir. Clinically observed DDI data for bictegravir coadministered with voriconazole, darunavir/cobicistat, atazanavir/cobicistat, and rifampicin were predicted within the 95% confidence interval of the PBPK model simulations. The area under the curve (AUC) ratio of the DDI divided by the control scenario was always predicted within 1.25-fold of the clinically observed data, demonstrating the predictive capability of the used modeling approach. After the successful verification, various DDI scenarios with drug pairs and multiple concomitant drugs were simulated to analyze their effect on bictegravir exposure. Generally, our simulation results suggest that bictegravir should not be coadministered with strong CYP3A and UGT1A1 inhibitors and inducers (e.g., atazanavir, nilotinib, and rifampicin), but based on the present modeling results, bictegravir could be administered with moderate dual perpetrators (e.g., efavirenz). Importantly, the inducing effect of rifampicin on bictegravir was predicted to be reversed with the concomitant administration of a strong inhibitor such as ritonavir, resulting in a DDI magnitude within the efficacy and safety margin for bictegravir (0.5-2.4-fold). In conclusion, the PBPK modeling strategy can effectively be used to guide the clinical management of DDIs for novel drugs with limited clinical experience, such as bictegravir., (© 2021 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Background and Objective: Entrectinib is a selective inhibitor of ROS1/TRK/ALK kinases, recently approved for oncology indications. Entrectinib is predominantly cleared by cytochrome P450 (CYP) 3A4, and modulation of CYP3A enzyme activity profoundly alters the pharmacokinetics of both entrectinib and its active metabolite M5. We describe development of a combined physiologically based pharmacokinetic (PBPK) model for entrectinib and M5 to support dosing recommendations when entrectinib is co-administered with CYP3A4 inhibitors or inducers., Methods: A PBPK model was established in Simcyp ® Simulator. The initial model based on in vitro-in vivo extrapolation was refined using sensitivity analysis and non-linear mixed effects modeling to optimize parameter estimates and to improve model fit to data from a clinical drug-drug interaction study with the strong CYP3A4 inhibitor, itraconazole. The model was subsequently qualified against clinical data, and the final qualified model used to simulate the effects of moderate to strong CYP3A4 inhibitors and inducers on entrectinib and M5 pharmacokinetics., Results: The final model showed good predictive performance for entrectinib and M5, meeting commonly used predictive performance acceptance criteria in each case. The model predicted that co-administration of various moderate CYP3A4 inhibitors (verapamil, erythromycin, clarithromycin, fluconazole, and diltiazem) would result in an average increase in entrectinib exposure between 2.2- and 3.1-fold, with corresponding average increases for M5 of approximately 2-fold. Co-administration of moderate CYP3A4 inducers (efavirenz, carbamazepine, phenytoin) was predicted to result in an average decrease in entrectinib exposure between 45 and 79%, with corresponding average decreases for M5 of approximately 50%., Conclusions: The model simulations were used to derive dosing recommendations for co-administering entrectinib with CYP3A4 inhibitors or inducers. PBPK modeling has been used in lieu of clinical studies to enable regulatory decision-making., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Milademetan is a small-molecule inhibitor of murine double minute 2 (MDM2) that is in clinical development for advanced solid tumors and hematological cancers, including liposarcoma and acute myeloid leukemia. Milademetan is a CYP3A and P-glycoprotein substrate and moderate CYP3A inhibitor. The current study aims to understand the drug-drug interaction (DDI) risk of milademetan as a CYP3A substrate during its early clinical development. A clinical DDI study of milademetan (NCT03614455) showed that concomitant administration of single-dose milademetan with the strong CYP3A inhibitor itraconazole or posaconazole increased milademetan mean area under the curve from zero to infinity (AUC inf ) by 2.15-fold (90% confidence interval [CI], 1.98-2.34) and 2.49-fold (90% CI, 2.26-2.74), respectively, supporting that the milademetan dose should be reduced by 50% when concomitantly administered with strong CYP3A inhibitors. A physiologically-based pharmacokinetic (PBPK) model of milademetan was subsequently developed to predict the magnitude of CYP3A-mediated DDI potential of milademetan with moderate CYP3A inhibitors. The PBPK model predicted an increase in milademetan exposure of 1.72-fold (90% CI, 1.69-1.76) with fluconazole, 1.91-fold (90% CI, 1.83-1.99) with erythromycin, and 2.02-fold (90% CI, 1.93-2.11) with verapamil. In addition, it estimated that milademetan's original dose (160 mg once daily) could be resumed from its half-reduced dose 3 days after discontinuation of concomitant strong CYP3A inhibitors. The established PBPK model of milademetan was qualified and considered to be robust enough to support continued development of milademetan., (© 2021 Daiichi Sankyo Inc. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Purpose: Previous studies evaluating ticagrelor drug-drug interactions have not differentiated intestinal versus systemic mechanisms, which we do here., Methods: Using recently published methodologies from our laboratory to differentiate metabolic- from transporter-mediated drug-drug interactions, a critical evaluation of five published ticagrelor drug-drug interactions was carried out to investigate the purported clinical significance of enzymes and transporters in ticagrelor disposition., Results: The suggested CYP3A4 inhibitors, ketoconazole and diltiazem, displayed unchanged mean absorption time (MAT) and time of maximum concentration (T max ) values as was expected, i.e., the interactions were mainly mediated by metabolic enzymes. The potential CYP3A4/P-gp inhibitor cyclosporine also showed an unchanged MAT value. Further analysis assuming there was no P-gp effect suggested that the increased AUC and unchanged t 1/2 for ticagrelor after cyclosporine administration were attributed to the inhibition of intestinal CYP3A4 rather than P-gp. Rifampin, an inducer of CYP3As after multiple dosing, unexpectedly showed decreased MAT and T max values, which cannot be completely explained. In contrast, grapefruit juice, an intestinal CYP3A/P-gp/OATP inhibitor, significantly increased MAT and T max values for ticagrelor, which may be due to activation of P-gp or inhibition of OATPs expressed in intestine., Conclusions: This study provides new insight into the role of transporter pathways in ticagrelor intestinal absorption by examining potential MAT and T max changes mediated by drug-drug interactions., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Icotinib (ICT) is an antitumor drug approved by China National Medical Products Administration and is found to be effective against non-small cell lung cancer. The present study aimed at the interaction of ICT with CYP3A. ICT exhibited time-, concentration-, and NADPH-dependent inhibitory effect on recombinant human CYP3A4/5. About 60% of CYP3A activity was suppressed by ICT at 50 μM after 30 minutes. The observed enzyme inhibition could not be recovered by dialysis. Nifedipine protected CYP3A from the inactivation by ICT. The inhibitory effects of ICT on CYP3A were influenced neither by glutathione/ N -acetyl lysine nor by superoxide dismutase/catalase. Incubation of ICT with human hepatic microsomes produced a ketene reactive intermediate trapped by 4-bromobenzylamine. CYP3A4 dominated the metabolic activation of ICT to the ketene intermediate. Ethyl and vinyl analogs of ICT did not induce inactivation of recombinant human CYP3A4/5, which indicates that acetylenic bioactivation of ICT contributed to the enzyme inactivation. Moreover, the metabolic activation of ICT resulted in heme destruction. In conclusion, this study demonstrated that ICT was a mechanism-based inactivator of recombinant human CYP3A4/5, and heme destruction by the ketene metabolite may be responsible for the observed CYP3A inactivation. SIGNIFICANCE STATEMENT: Cytochrome P450 enzymes play an important role in drug-drug interactions. The present study demonstrated that icotinib, an inhibitor of epidermal growth factor receptor used to treat non-small cell lung cancer, is a mechanism-based inactivator of recombinant human CYP3A4/5. The study provided solid evidence for the involvement of acetylene moiety in the metabolic activation as well as the inactivation of the enzyme. Furthermore, the resulting ketene intermediate was found to destroy heme, which is possibly responsible for the observed enzyme inactivation., (Copyright © 2021 by The American Society for Pharmacology and Experimental Therapeutics.)

Many women take drugs during their pregnancy to treat a variety of clinical conditions. To optimize drug efficacy and reduce fetal toxicity, it is important to determine or predict fetal drug exposure throughout pregnancy. Previously, we developed and verified a maternal-fetal physiologically based pharmacokinetic (m-f PBPK) model to predict fetal K p,uu (unbound fetal plasma AUC/unbound maternal plasma AUC) of drugs that passively cross the placenta. Here, we used in vitro transport studies in Transwell, in combination with our m-f PBPK model, to predict fetal K p,uu of drugs that are effluxed by placental P-glycoprotein (P-gp)-namely, dexamethasone, betamethasone, darunavir, and lopinavir. Using Transwell, we determined the efflux ratio of these drugs in hMDR1-MDCK cP-gpKO cells, in which human P-gp was overexpressed and the endogenous P-gp was knocked out. Then, using the proteomics-informed efflux ratio-relative expressive factor approach, we predicted the fetal K p,uu of these drugs at term. Finally, to verify our predictions, we compared them with the observed in vivo fetal K p,uu at term. The latter was estimated using our m-f PBPK model and published fetal [umbilical vein (UV)]/maternal plasma drug concentrations obtained at term (UV/maternal plasma). Fetal K p,uu predictions for dexamethasone (0.63), betamethasone (0.59), darunavir (0.17), and lopinavir (0.08) were successful, as they fell within the 90% confidence interval of the corresponding in vivo fetal K p,uu (0.30-0.66, 0.29-0.71, 0.11-0.22, 0.04-0.19, respectively). This is the first demonstration of successful prediction of fetal K p,uu of P-gp drug substrates from in vitro studies. SIGNIFICANCE STATEMENT: For the first time, using in vitro studies in cells, this study successfully predicted human fetal K p,uu of P-gp substrate drugs. This success confirms that the m-f PBPK model, combined with the ER-REF approach, can successfully predict fetal drug exposure to P-gp substrates. This success provides increased confidence in the use of the ER-REF approach, combined with the m-f PBPK model, to predict fetal K p,uu of drugs (transported by P-gp or other transporters), both at term and at earlier gestational ages., (Copyright © 2021 The Author(s).)

Cytochrome P450 3A (CYP3A) is a frequent target for time-dependent inhibition (TDI) that can give rise to drug-drug interactions (DDI). Yet many drugs that exhibit in vitro TDI for CYP3A do not result in DDI. There were 23 drugs with published clinical DDI evaluated for CYP3A TDI in human liver microsomes (HLM) and hepatocytes (HHEP), and these data were used in static and dynamic models for projecting DDI caused by inactivation of CYP3A in both liver and intestine. TDI parameters measured in HHEP, particularly the maximal rate of enzyme inactivation, were generally lower than those measured in HLM. In static models, the use of estimated average unbound organ exit concentrations offered the most accurate projections of DDI with geometric mean fold errors of 2.0 and 1.7 for HLM and HHEP, respectively. Use of maximum organ entry concentrations yielded marked overestimates of DDI. When evaluated in a binary fashion (i.e., projection of DDI of 1.25-fold or greater), data from HLM offered the greatest sensitivity (100%) and specificity (67%) and yielded no missed DDI when average unbound organ exit concentrations were used. In dynamic physiologically based pharmacokinetic modeling, accurate projections of DDI were obtained with geometric mean fold errors of 1.7 and 1.6 for HLM and HHEP, respectively. Sensitivity and specificity were 100% and 67% when using TDI data generated in HLM and Simcyp modeling. Overall, DDI caused by CYP3A-mediated TDI can be reliably projected using dynamic or static models. For static models, average organ unbound exit concentrations should be used as input values otherwise DDI will be markedly overestimated. SIGNIFICANCE STATEMENT: CYP3A time-dependent inhibitors (TDI) are important in the design and development of new drugs. The prevalence of CYP3A TDI is high among newly synthesized drug candidates, and understanding the potential need for running clinical drug-drug interaction (DDI) studies is essential during drug development. Ability to reliably predict DDI caused by CYP3A TDI has been difficult to achieve. We report a thorough evaluation of CYP3A TDI and demonstrate that DDI can be predicted when using appropriate models and input parameters generated in human liver microsomes or hepatocytes., (Copyright © 2021 by The American Society for Pharmacology and Experimental Therapeutics.)