P450 3A Research Articles

EP08.02-109 A Drug-Drug Interaction Study of Mobocertinib and Midazolam in Patients With Advanced Non-Small Cell Lung Cancer

Mobocertinib is an oral tyrosine kinase inhibitor designed to selectively target epidermal growth factor receptor (EGFR) exon 20 insertion (EGFR ex20ins) mutations in non-small cell lung cancer (NSCLC). In vitro studies indicated the potential for time-dependent inhibition and/or induction of cytochrome P450 (CYP) 3A after mobocertinib administration. Thus, a phase 1 drug-drug interaction study (NCT04051827) was conducted to assess the effect of repeat-dose administration of mobocertinib on the pharmacokinetics (PK) of midazolam, a sensitive CYP3A substrate.

Development of an in vitro insulin resistance dissociated model of hepatic steatosis by co-culture system.

The evidence shows that there is an associated relationship between hepatosteatosis and insulin resistance. While some existing genetic induction animal and patient models challenge this relationship, indicating that hepatosteatosis is dissociated from insulin resistance. However, the molecular mechanisms of this dissociation remain poorly understood due to a lack of available, reliable, and simplistic setup models. Currently, we used primary rat hepatocytes (rHPCs), co-cultured with rat hepatic stellate cells (HSC-T6) or human foreskin fibroblast cells (HFF-1) in stimulation with high insulin and glucose, to develop a model of steatosis charactered as dissociated lipid accumulation from insulin resistance. Oil-Red staining significantly showed intracellular lipid accumulated in the developed model. Gene expression of sterol regulatory element-binding protein 1c (SREBP1c) and elongase of very-long-chain fatty acids 6 (ELOVL6), key genes responsible for lipogenesis, were detected and obviously increased in this model. Inversely, the insulin resistance related genes expression included phosphoenolpyruvate carboxykinase 1 (PCK1), pyruvate dehydrogenase lipoamide kinase isozyme 4 (PDK4), and glucose-6-phosphatase (G6pase) were decreased, suggesting a dissociation relationship between steatosis and insulin resistance in the developed model. As well, the drug metabolism of this developed model was investigated and showed up-regulation of cytochrome P450 3A (CYP3A) and down-regulation of cytochrome P450 2E1 (CYP2E1) and cytochrome P450 1A2 (CYP1A2). Taken together, those results demonstrate that the in vitro model of dissociated steatosis from insulin resistance was successfully created by our co-cultured cells in high insulin and glucose medium, which will be a potential model for investigating the mechanism of insulin resistance dissociated steatosis, and discovering a novel drug for its treatment.

Atorvastatin induced liver injury: A Case Series

Atorvastatin is the most widely used statin for the prevention and treatment of cardiovascular disease. It belongs to the class of drugs called HMG-CoA reductase inhibitors. One of the most significant side effects of statins is liver injury. Liver injury as evidenced by elevation in liver enzymes occurs in some patients treated with atorvastatin 10mg to 80mg. Therefore, Liver function tests (LFTs) need to be assessed before initiating atorvastatin therapy and to be repeated thereafter. Here we discuss three cases of liver enzyme elevations within 24hrs of atorvastatin treatment. Liver enzymes were completely returned to baseline after discontinuing the therapy. The risk factors of atorvastatin induced liver injury are increased age, chronic diseases, and coadministration of drugs metabolised by Cytochrome P450 3A (CYP3A) enzyme.

Therapeutic Drug Monitoring of Ivacaftor, Lumacaftor, Tezacaftor, and Elexacaftor in Cystic Fibrosis: Where Are We Now?

Drugs modulating the cystic fibrosis transmembrane conductance regulator (CFTR) protein, namely ivacaftor, lumacaftor, tezacaftor, and elexacaftor, are currently revolutionizing the management of patients with cystic fibrosis (CF), particularly those with at least one F508del variant (up to 85% of patients). These “caftor” drugs are mainly metabolized by cytochromes P450 3A, whose enzymatic activity is influenced by environmental factors, and are sensitive to inhibition and induction. Hence, CFTR modulators are characterized by an important interindividual pharmacokinetic variability and are also prone to drug–drug interactions. However, these CFTR modulators are given at standardized dosages, while they meet all criteria for a formal therapeutic drug monitoring (TDM) program that should be considered in cases of clinical toxicity, less-than-expected clinical response, drug or food interactions, distinct patient subgroups (i.e., pediatrics), and for monitoring short-term adherence. While the information on CFTR drug exposure–clinical response relationships is still limited, we review the current evidence of the potential interest in the TDM of caftor drugs in real-life settings.

Impact of Inflammation on Midazolam Metabolism in Severe COVID-19 Patients.

Midazolam is a benzodiazepine frequently used for sedation in patients hospitalized in the intensive care unit (ICU) for coronavirus disease 2019 (COVID‐19). This drug is primarily metabolized by cytochrome P450 3A (CYP3A) isoenzymes. Several studies have suggested that inflammation, frequently observed in these patients, could modulate CYP3A activity. The objective of this work was to study the impact of inflammation on midazolam pharmacokinetics in patients with COVID‐19. Forty‐eight patients hospitalized in the ICU for COVID‐19 and treated with midazolam administered by continuous infusion were included in this study. Midazolam and α‐hydroxymidazolam concentrations were measured and patient data, including the use of CYP3A inhibitors, were collected. Total and unbound concentrations of midazolam and α‐hydroxymidazolam were measured in plasma using a validated liquid‐chromatography coupled with mass spectrometry method. Inflammatory condition was evaluated by C‐reactive protein (CRP) level measurement. Both drug concentrations and CRP measurements were performed on 354 plasma samples. CRP elevation was significantly associated with the α‐hydroxymidazolam/midazolam plasma ratio decrease, whether for the unbound fraction or for the total fraction. Conversely, inflammation was not associated with protein binding modifications. Logically, α‐hydroxymidazolam/midazolam plasma ratio was significantly reduced when patients were treated with CYP3A inhibitors. In this study, we showed that inflammation probably reduces the metabolism of midazolam by CYP3A. These results suggest that molecules with narrow therapeutic margins and metabolized by CYP3A should be administrated with care in case of massive inflammatory situations.

Species Specificity and Selection of Models for Drug Oxidations Mediated by Polymorphic Human Enzymes.

Many drug oxygenations are mainly mediated by polymorphic cytochromes P450 (P450s) and also by flavin-containing monooxygenases (FMOs). More than 50 years of research on P450/FMO-mediated drug oxygenations have clarified their catalytic roles. The natural product coumarin causes hepatotoxicity in rats via the reactive coumarin 3,4-epoxide, a reaction catalyzed by P450 1A2; however, coumarin undergoes rapid 7-hydroxylation by polymorphic P450 2A6 in humans. The primary oxidation product of the teratogen thalidomide in rats is deactivated 5'-hydroxythalidomide plus sulfate and glucuronide conjugates; however, similar 5'-hydroxythalidomide and 5-hydroxythalidomide are formed in rabbits in vivo. Thalidomide causes human P450 3A enzyme induction in liver (and placenta) and is also activated in vitro and in vivo by P450 3A through the primary human metabolite 5-hydroxythalidomide (leading to conjugation with glutathione/nonspecific proteins). Species differences exist in terms of drug metabolism in rodents and humans, and such differences can be very important when determining the contributions of individual enzymes. The approaches used for investigating the roles of human P450 and FMO enzymes in understanding drug oxidations and clinical therapy have not yet reached maturity and still require further development. SIGNIFICANCE STATEMENT: Drug oxidations in animals and humans mediated by P450s and FMOs are important for understanding the pharmacological properties of drugs, such as the species-dependent teratogenicity of the reactive metabolites of thalidomide and the metabolism of food-derived odorous trimethylamine to non-odorous (but proatherogenic) trimethylamine N-oxide. Recognized differences exist in terms of drug metabolism between rodents, non-human primates, and humans, and such differences are important when determining individual liver enzyme contributions with substrates in in vitro and in vivo systems.

A Comprehensive Investigation of Dog Cytochrome P450 3A (CYP3A) Reveals a Functional Role of Newly Identified CYP3A98 in Small Intestine.

Dogs are frequently used in drug metabolism studies, and their important drug-metabolizing enzymes, including cytochromes P450 (P450), have been analyzed. In humans, CYP3A4 is an especially important P450 due to its abundance and major roles in liver and intestine. In the present study, dog CYP3A98 and CYP3A99 were identified and characterized, along with previously identified CYP3A12 and CYP3A26. The dog CYP3A cDNAs contained open reading frames of 503 amino acids and shared high sequence identity (78%-80%) with human CYP3As. Among the dog CYP3A mRNAs, CYP3A98 mRNA was expressed most abundantly in small intestine. In contrast, dog CYP3A12 and CYP3A26 mRNAs were expressed in liver, where CYP3A12 mRNA was the most abundant. The four CYP3A genes had similar gene structures and formed a gene cluster in the dog and human genomes. Metabolic assays of dog CYP3A proteins heterologously expressed in Escherichia coli indicated that the dog CYP3As tested were functional enzymes with respect to typical human CYP3A4 substrates. Dog CYP3A98 efficiently catalyzed oxidations of nifedipine, alprazolam, and midazolam, indicating major roles of CYP3A98 in the small intestine. Dog CYP3A12 and CYP3A26 metabolizing nifedipine and/or midazolam would play roles in these reactions in the liver. In contrast, dog CYP3A99 showed minimal mRNA expression and minimal metabolic activity, and its contribution to overall drug metabolism is, therefore, negligible. These results indicated that newly identified dog CYP3A98, a testosterone 6 β - and estradiol 16 α -hydroxylase, was abundantly expressed in the small intestine and is likely the major CYP3A in the small intestine in combination with liver-specific CYP3A12. SIGNIFICANCE STATEMENT: Novel dog cytochromes P450 3A98 (CYP3A98) and CYP3A99 were identified and characterized to be functional and highly identical to human CYP3A4. Known CYP3A12 and new CYP3A98 efficiently catalyzed estradiol 16α-hydroxylation and midazolam 1'-hydroxylation. CYP3A98 mRNA was expressed in small intestine, whereas CYP3A12 mRNA was predominant in liver. Dog hepatic CYP3A12 and intestinal CYP3A98 are the enzymes likely responsible for the metabolic clearances of orally administered drugs, unlike human CYP3A4/5, which are in both the liver and intestine.

PB2247: PHARMACOKINETIC MODELING AND SIMULATION TO SUPPORT MITAPIVAT DOSE SELECTION USED IN PEDIATRIC PHASE III STUDIES

Background: Mitapivat (AG-348) is a first-in-class, oral, small molecule, allosteric activator of the red blood cell pyruvate kinase (PK) enzyme (PKR). The positive benefit-risk profile of mitapivat has been demonstrated in two recently completed phase 3 studies in adults with PK deficiency who are not regularly transfused (ACTIVATE, NCT03548220) or regularly transfused (ACTIVATE-T, NCT03559699). Currently, two phase 3 studies are being initiated to evaluate the efficacy and safety of mitapivat in pediatric subjects aged 1 to <18 years (yrs) with PK deficiency who are not regularly transfused (ACTIVATE-Kids, NCT05144256) or regularly transfused (ACTIVATE-KidsT, NCT05175105). Aims: Conduct a pharmacometrics analysis to support the mitapivat dose selection in the phase 3 studies in pediatric subjects. Methods: A three compartment population pharmacokinetic model with allometrically scaled parameters (clearances and volume of distribution) was applied. Dose simulations were conducted for various age subsets and body weight ranges using data from the National Health and Nutrition Examination Survey (NHANES) database. For subjects aged 1 to <2 yrs, in addition to allometric scaling, maturation factors (Salem F et al. Clin Pharmacokinet. 2014;53:625–36. Salem F et al. Clin Pharmacokinet. 2015;54:671) accounting for changes in cytochrome P450 (CYP) 3A activity were implemented. This approach was employed because mitapivat is metabolized primarily by CYP3A, and maturational changes in CYP3A ontogeny are known to occur during the first few yrs of life. The selected pediatric dose for each age subset and weight range was based on a dose that was predicted to achieve mitapivat exposure (ie, the area under the plasma concentration-time curve [AUC] during a dosing interval at steady state) similar to that achieved in adults receiving the recommended clinical dose for PK deficiency (dose titrations occurring every 4 weeks, from 5 mg twice daily [BID] to 20 mg BID, and then to the maximum recommended dose of 50 mg BID). Results: The proposed dosing scheme is shown in the Table. For subjects aged 12 to <18 yrs who weigh ≥40 kg, the recommended dose used in adults would provide a similar mitapivat AUC to that achieved in adults; the predicted difference is <20%, and therefore is not considered to be clinically meaningful. For subjects aged 12 to <18 yrs who weigh <40 kg, or subjects aged 2 to <12 yrs, dosing according to body weight (≥40 kg, ≥20 to <40 kg, and <20 kg) would yield similar mitapivat AUC ranges between pediatric and adult subjects. For subjects aged 1 to <2 yrs, the proposed doses shown in the Table are predicted to provide <5% difference in mitapivat AUC as compared with adults. Image:Summary/Conclusion: Population pharmacokinetic modeling and simulation was utilized to identify candidate doses for evaluation in mitapivat pediatric phase 3 studies. The selected doses for each pediatric age subset and body weight range are projected to provide mitapivat AUC similar to that achieved in adults receiving the recommended clinical dose.

Rifampin Drug-Drug-Interaction Studies: Reflections on the Nitrosamine Impurities Issue.

Clinical development of new drugs may require dedicated drug-drug interaction (DDI) studies, such as to evaluate the effect of cytochrome P450 3A induction on the pharmacokinetics of investigational drugs. However, as a result of N-nitrosamine impurity findings in marketed rifampin formulations, the application of rifampin in DDI studies has been halted. This mini-review considers the root cause and impact of the nitrosamine impurity as well as alternative options for the continued conduct of DDIs.

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

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. Two physiological based pharmacokinetics (PBPK) models were developed for VCZ and VEN using the bottom-up and top-down method. VCZ model was also developed to describe the effect of CYP2C19 polymorphism on its pharmacokinetics (PK). The reversible inhibition constant (Ki) of VCZ for CYP3A4 was calibrated using drug-drug interaction (DDI) data of midazolam and VCZ. The clinical verified VCZ and VEN model were used to predict the DDI of VCZ and VEN at clinical dosing scenario. 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 100mg when co-administered with VCZ. 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 100mg dose adjustment is still applicable in the presence of VCZ with high inter-individual viability.

Why We Need to Take a Closer Look at Genetic Contributions to CYP3A Activity

Cytochrome P450 3A (CYP3A) subfamily enzymes are involved in the metabolism of 40% of drugs in clinical use. Twin studies have indicated that 66% of the variability in CYP3A4 activity is hereditary. Yet, the complexity of the CYP3A locus and the lack of distinct drug metabolizer phenotypes has limited the identification and clinical application of CYP3A genetic variants compared to other Cytochrome P450 enzymes. In recent years evidence has emerged indicating that a substantial part of the missing heritability is caused by low frequency genetic variation. In this review, we outline the current pharmacogenomics knowledge of CYP3A activity and discuss potential future directions to improve our genetic knowledge and ability to explain CYP3A variability.

Robust physiologically based pharmacokinetic model of rifampicin for predicting drug-drug interactions via P-glycoprotein induction and inhibition in the intestine, liver, and kidney.

P‐glycoprotein (P‐gp) is an efflux transporter that plays an important role in the pharmacokinetics of its substrate, and P‐gp activities can be altered by induction and inhibition effects of rifampicin. This study aimed to establish a physiologically based pharmacokinetic (PBPK) model of rifampicin to predict the P‐gp‐mediated drug–drug interactions (DDIs) and assess the DDI impact in the intestine, liver, and kidney. The induction and inhibition parameters of rifampicin for P‐gp were estimated using two of seven DDI cases of rifampicin and digoxin and incorporated into our previously constructed PBPK model of rifampicin. The constructed rifampicin model was verified using the remaining five DDI cases with digoxin and five DDI cases with other P‐gp substrates (talinolol and quinidine). Based on the established PBPK model, following repeated dosing of 600 mg rifampicin, the deduced net effect was an approximately threefold induction in P‐gp activities in the intestine, liver, and kidney. Furthermore, in all 12 cases the predicted area under the plasma concentration–time curve ratios of the P‐gp substrates were within the predefined acceptance criteria with various dosing regimens. Intestinal effects of P‐gp–mediated DDIs had their greatest impact on the pharmacokinetics of digoxin and talinolol, with a minimal impact on the liver and kidney. For quinidine, predicted intestinal P‐gp/cytochrome P450 3A–mediated DDIs were slightly underestimated because of the complexity of nonlinearity and transporter‐enzyme interplay. These findings demonstrate that our rifampicin model can be applicable to quantitatively predict the net impact of P‐gp induction and/or inhibition on diverse P‐gp substrates and investigate the magnitude of DDIs in each tissue.

Tutorial: Statistical analysis and reporting of clinical pharmacokinetic studies.

Pharmacokinetics is the cornerstone of understanding drug absorption, distribution, metabolism, and elimination. It is also the key to describing variability in drug response caused by drug‐drug interactions (DDIs), pharmacogenetics, impaired kidney and liver function, etc. This tutorial aims to provide a guideline and step‐by‐step tutorial on essential considerations when designing clinical pharmacokinetic studies and reporting results. This includes a comprehensive guide on how to conduct the statistical analysis and a complete code for the statistical software R. As an example, we created a mock dataset simulating a clinical pharmacokinetic DDI study with 12 subjects who were administered 2 mg oral midazolam with and without an inducer of cytochrome P450 3A. We provide a step‐by‐step guide to the statistical analysis of this clinical pharmacokinetic study, including sample size/power calculation, descriptive statistics, noncompartmental analyses, and hypothesis testing. The different analyses and parameters are described in detail, and we provide a complete R code ready to use in supplementary files. Finally, we discuss important considerations when designing and reporting clinical pharmacokinetic studies. The scope of this tutorial is not limited to DDI studies, and with minor adjustments, it applies to all types of clinical pharmacokinetic studies. This work was done by early career researchers for early career researchers. We hope this tutorial may help early career researchers when getting started on their own pharmacokinetic studies. We encourage you to use this as an inspiration and starting point and continuously evolve your statistical skills.

Drug‐Drug Interactions and Disease Status Are Associated With Irinotecan‐Induced Hepatotoxicity: A Cross‐Sectional Study in Shanghai

Irinotecan-induced hepatotoxicity can cause severe clinical complications in patients; however, the underlying mechanism and factors affecting hepatotoxicity have rarely been investigated. In this cross-sectional study, we screened all clinical, demographic, medication, and genetic variables among 126 patients receiving irinotecan and explored potential associations with the incidence and time to onset of irinotecan-induced hepatotoxicity. Approximately 38.9% of the patients suffered from hepatotoxicity after irinotecan administration. The presence of cardiovascular diseases increases the incidence of hepatotoxicity ≈2.9-fold and doubles the hazard of time to hepatotoxicity. Patients with liver metastasis had a >4-fold higher risk of hepatotoxicity and a 3.5-fold increased hazard of time to hepatotoxicity compared to those without liver metastasis. Patients who took cytochrome P450 (CYP) 3A inducers had a 4.4-fold increased incidence of hepatotoxicity, and furthermore, concomitant use of platinum-based antineoplastics revealed 4.2 times the hazard of time to hepatotoxicity compared to those receiving antimetabolites. The cumulative dose of irinotecan (5-9 cycles) increased hepatotoxicity by 8.5 times. However, the genotypes and phenotypes of UGT1A1*28/*6 failed to be predictive factors of hepatotoxicity. The findings of this study suggest that irinotecan-induced hepatotoxicity is not directly associated with genetic variables but is mostly related to concomitant use of CYP3A4 inducers and platinum, as well as the presence of liver metastasis and cardiovascular disease. Thus, close monitoring of liver function is recommended, especially in patients with liver impairment or using CYP3A inducers and platinum antineoplastic drugs, which may be the best way to prevent hepatotoxicity.

Utilization of CYP3A‐Specific Inhibitors to Study Cytochrome P450 CYP3A7 Activity in Neonatal Human Liver Microsomes

CYP3A7 is a member of the cytochrome P450 (CYP) 3A enzyme sub‐family that accounts for ~50% of the total CYP content in neonate and fetal livers. The amount of other CYP3A enzymes, CYP3A4 and CYP3A5, expressed in neonates is low but highly variable, and therefore, the activity of individual enzyme isoforms is difficult to differentiate. Recent studies report that CYP3cide, clobetasol propionate, and azamulin are specific inhibitors for CYP3A4, CYP3A5, and CYP3A4/5, respectively. However, the inhibitory effects towards CYP3A7 were not investigated for the latter two compounds, and the use of these compounds to study CYP3A7 activity has not been reported/investigated. Thus, we sought to characterize these compounds further and utilize them to isolate and study the activity of CYP3A7 in neonatal human liver microsomes. We have examined three substrate probes—dibenzylfluorescein, luciferin‐PPXE, and midazolam—to determine the IC50 values and mechanism‐based inactivation parameters (Ki, Kinact) of the purported isoform specific inhibitors. We discovered that azamulin was unable to selectively inhibit any of the CYP3As, but CYP3cide and clobetasol propionate exhibited IC50values for CYP3A4 and CYP3A5 two to three orders of magnitude lower than CYP3A7. CYP3cide and clobetasol propionate were further tested in mixtures of CYP3A4, CYP3A5, and CYP3A7 to mimic the neonatal human liver microsome environment and ascertain their effectiveness in isolating CYP3A7 activity. We were able to inhibit CYP3A4 without disturbing CYP3A7 activity using CYP3cide at concentrations below 5 μM. The majority of CYP3A5 activity was inhibited using low clobetasol propionate concentrations, but using higher concentrations also inhibited CYP3A7 activity due to its lower selectivity. These findings provide valuable insight regarding testing conditions to investigate the metabolism of new drug candidates and help determine drug safety in neonates.

Direct and Sequential Bioactivation of Pemigatinib to a Reactive Iminium Ion Intermediate Culminates in Mechanism‐Based Inactivation of Cytochrome P450 3A

Mechanism‐based inactivation (MBI) is a unique phenomenon in drug metabolism that arises when an enzyme metabolically activates a drug to a chemically reactive intermediate and primes it for irreversible binding, leading to an irrevocable loss of catalytic activity that is only restored upon de novo synthesis of the implicated enzyme. Our laboratory recently established the MBI of cytochrome P450 3A (CYP3A) by the fibroblast growth factor receptor (FGFR) inhibitors erdafitinib and infigratinib. Serendipitously, our preliminary data has also revealed that pemigatinib (PEM) – another clinically approved FGFR1‐3 inhibitor – similarly elicited time‐dependent inhibition of CYP3A. This was rather unexpected as it was previously purported that PEM did not pose any metabolism‐dependent liabilities due to the absence of glutathione‐related conjugates in metabolic profiling experiments conducted in human liver microsomes. Consequently, we posited that PEM is bioactivated by CYP3A to a hard electrophile, thereby allowing it to elude glutathione trapping and detection in the aforementioned reactive metabolite screen. Here, we confirmed that PEM inhibited both CYP3A isoforms in a time‐, concentration‐, and cofactor‐dependent manner consistent with MBI – with KI, kinact, and partition ratio of 8.69 and 11.95 μM, 0.108 and 0.042 min−1, and ~44 and ~47 for CYP3A4 and CYP3A5 respectively, when rivaroxaban was employed as the probe substrate. While the rate of inactivation was diminished by coincubation with an alternative substrate (testosterone) or direct inhibitor of CYP3A (ketoconazole), the inclusion of nucleophilic trapping agents afforded no such protection. Furthermore, the lack of catalytic activity recovery following dialysis and oxidation with potassium ferricyanide coupled with the absence of a spectrally resolvable peak in the Soret region collectively implied that the underlying mechanism of inactivation was not elicited via the formation of pseudoirreversible metabolite‐intermediate complexes. Utilizing cyanide trapping and high‐resolution mass spectrometry, we illuminated the direct and sequential oxidative bioactivation of PEM and its major O‐desmethylated metabolite at its distal morpholine moiety to a reactive iminium ion intermediate that could covalently modify the CYP3A apoprotein and/or prosthetic heme and culminate in its MBI. Finally, structural determinants gleaned from our in silicocovalent docking simulations suggested that the discrepancies in MBI potencies between both CYP3A isoforms might be alluded to the propensity for PEM to interact more favourably with an accessible active‐site serine residue in position 312 of CYP3A4 as compared to CYP3A5. Further physiologically based pharmacokinetic modelling studies are currently underway to better discern the clinical implications of our findings.

Interindividual Variability in Cytochrome P450 3A and 1A Activity Influences Sunitinib Metabolism and Bioactivation.

Sunitinib is an orally administered tyrosine kinase inhibitor associated with idiosyncratic hepatotoxicity; however, the mechanisms of this toxicity remain unclear. We have previously shown that cytochromes P450 1A2 and 3A4 catalyze sunitinib metabolic activation via oxidative defluorination leading to a chemically reactive, potentially toxic quinoneimine, trapped as a glutathione (GSH) conjugate (M5). The goals of this study were to determine the impact of interindividual variability in P450 1A and 3A activity on sunitinib bioactivation to the reactive quinoneimine and sunitinib N-dealkylation to the primary active metabolite N-desethylsunitinib (M1). Experiments were conducted in vitro using single-donor human liver microsomes and human hepatocytes. Relative sunitinib metabolite levels were measured by liquid chromatography-tandem mass spectrometry. In human liver microsomes, the P450 3A inhibitor ketoconazole significantly reduced M1 formation compared to the control. The P450 1A2 inhibitor furafylline significantly reduced defluorosunitinib (M3) and M5 formation compared to the control but had minimal effect on M1. In CYP3A5-genotyped human liver microsomes from 12 individual donors, M1 formation was highly correlated with P450 3A activity measured by midazolam 1'-hydroxylation, and M3 and M5 formation was correlated with P450 1A2 activity estimated by phenacetin O-deethylation. M3 and M5 formation was also associated with P450 3A5-selective activity. In sandwich-cultured human hepatocytes, the P450 3A inducer rifampicin significantly increased M1 levels. P450 1A induction by omeprazole markedly increased M3 formation and the generation of a quinoneimine-cysteine conjugate (M6) identified as a downstream metabolite of M5. The nonselective P450 inhibitor 1-aminobenzotriazole reduced each of these metabolites (M1, M3, and M6). Collectively, these findings indicate that P450 3A activity is a key determinant of sunitinib N-dealkylation to the active metabolite M1, and P450 1A (and potentially 3A5) activity influences sunitinib bioactivation to the reactive quinoneimine metabolite. Accordingly, modulation of P450 activity due to genetic and/or nongenetic factors may impact the risk of sunitinib-associated toxicities.

Examination of the Impact of CYP3A4/5 on Drug–Drug Interaction between Schizandrol A/Schizandrol B and Tacrolimus (FK-506): A Physiologically Based Pharmacokinetic Modeling Approach

Schizandrol A (SZA) and schizandrol B (SZB) are two active ingredients of Wuzhi capsule (WZC), a Chinese proprietary medicine commonly prescribed to alleviate tacrolimus (FK-506)-induced hepatoxicity in China. Due to their inhibitory effects on cytochrome P450 (CYP) 3A enzymes, SZA/SZB may display drug–drug interaction (DDI) with tacrolimus. To identify the extent of this DDI, the enzymes’ inhibitory profiles, including a 50% inhibitory concentration (IC50) shift, reversible inhibition (RI) and time-dependent inhibition (TDI) were examined with pooled human-liver microsomes (HLMs) and CYP3A5-genotyped HLMs. Subsequently, the acquired parameters were integrated into a physiologically based pharmacokinetic (PBPK) model to quantify the interactions between the SZA/SZB and the tacrolimus. The metabolic studies indicated that the SZB displayed both RI and TDI on CYP3A4 and CYP3A5, while the SZA only exhibited TDI on CYP3A4 to a limited extent. Moreover, our PBPK model predicted that multiple doses of SZB would increase tacrolimus exposure by 26% and 57% in CYP3A5 expressers and non-expressers, respectively. Clearly, PBPK modeling has emerged as a powerful approach to examine herb-involved DDI, and special attention should be paid to the combined use of WZC and tacrolimus in clinical practice.

Physiologically-Based Pharmacokinetic-Led Guidance for Patients With Cystic Fibrosis Taking Elexacaftor-Tezacaftor-Ivacaftor With Nirmatrelvir-Ritonavir for the Treatment of COVID-19.

Cystic fibrosis transmembrane conductance regulator (CFTR) modulating therapies, including elexacaftor‐tezacaftor‐ivacaftor, are primarily eliminated through cytochrome P450 (CYP) 3A–mediated metabolism. This creates a therapeutic challenge to the treatment of coronavirus disease 2019 (COVID‐19) with nirmatrelvir‐ritonavir in people with cystic fibrosis (CF) due to the potential for significant drug–drug interactions (DDIs). However, the population with CF is more at risk of serious illness following COVID‐19 infection and hence it is important to manage the DDI risk and provide treatment options. CYP3A‐mediated DDI of elexacaftor‐tezacaftor‐ivacaftor was evaluated using a physiologically‐based pharmacokinetic modeling approach. Modeling was performed incorporating physiological information and drug‐dependent parameters of elexacaftor‐tezacaftor‐ivacaftor to predict the effect of ritonavir (the CYP3A inhibiting component of the combination) on the pharmacokinetics of elexacaftor‐tezacaftor‐ivacaftor. The elexacaftor‐tezacaftor‐ivacaftor models were verified using independent clinical pharmacokinetic and DDI data of elexacaftor‐tezacaftor‐ivacaftor with a range of CYP3A modulators. When ritonavir was administered on Days 1 through 5, the predicted area under the curve (AUC) ratio of ivacaftor (the most sensitive CYP3A substrate) on Day 6 was 9.31, indicating that its metabolism was strongly inhibited. Based on the predicted DDI, the dose of elexacaftor‐tezacaftor‐ivacaftor should be reduced when coadministered with nirmatrelvir‐ritonavir to elexacaftor 200 mg–tezacaftor 100 mg–ivacaftor 150 mg on Days 1 and 5, with delayed resumption of full‐dose elexacaftor‐tezacaftor‐ivacaftor on Day 9, considering the residual inhibitory effect of ritonavir as a mechanism‐based inhibitor. The simulation predicts a regimen of elexacaftor‐tezacaftor‐ivacaftor administered concomitantly with nirmatrelvir‐ritonavir in people with CF that will likely decrease the impact of the drug interaction.

23P Pharmacokinetic boosting of osimertinib with cobicistat in patients with non-small cell lung cancer: The OSIBOOST trial

Exposure to osimertinib (osi), a 3rd generation TKI for treatment of non-small cell lung cancer (NSCLC) and a sensitizing epidermal growth factor receptor (EGFR) mutation is variable between patients (pts). We evaluated the boosting capacity of cobicistat (cobi), a strong Cytochrome P450 3A (CYP3A)-inhibitor, on osi exposure in pts with NSCLC and low osi plasma trough concentration.