Mechanistic Modeling to Predict Midazolam Metabolite Exposure from In Vitro Data

Drug-Drug Interaction Potential of Mavacamten with Midazolam: Combined Results from Clinical and Model-Based Studies

Mavacamten is a potential inducer of cytochrome P450 (CYP) 3A4 and could reduce the effectiveness of concomitant drugs that are metabolized by CYP3A4, such as midazolam. This study aimed to determine if repeat doses of mavacamten achieving clinically relevant exposures affected midazolam exposure. This was a single-center, open-label study in healthy participants. Participants received: on day 1, midazolam 5 mg; on days 2-3, mavacamten 25 mg; on days 4-16, mavacamten 15 mg; and on day 17, mavacamten 15 mg and midazolam 5 mg. Plasma concentrations of mavacamten, midazolam, and the midazolam metabolite 1'-hydroxymidazolam were measured. A physiologically based pharmacokinetic (PBPK) model was used to simulate the effect of mavacamten-mediated CYP3A4 induction on midazolam exposure by CYP2C19 phenotype. Thirteen adult participants were enrolled (46.2% were female; mean [SD] age: 34.0 [9.0] years). Compared with midazolam alone, midazolam coadministered with mavacamten decreased the maximum observed plasma concentration (Cmax), area under the drug concentration-time curve (AUC) from time zero to infinity (AUC0-inf), and AUC from time zero to last measurable concentration (AUC0-last) for midazolam by 7%, 13%, and 24%, respectively; for 1'-hydroxymidazolam, AUC0-inf and AUC0Ȁlast increased by 20% and 11%, respectively. Ten participants experienced adverse events and the majority were mild in severity. The PBPK model predicted the clinical trial data well. The PBPK simulation assessed that the overall impact of mavacamten on midazolam Cmax and AUC was predicted to be weak regardless of CYP2C19 phenotype. At clinically relevant exposures, mavacamten had a negligible effect on midazolam exposure.

Effects of Midazolam and Dexmedetomidine on Cognitive Dysfunction Following Open-Heart Surgery: A Comprehensive Review

PURPOSE

Patients undergoing open-heart surgery often face significant challenges in postoperative cognitive dysfunction (POCD). There has been growing interest in understanding how anesthesia medications, such as dexmedetomidine (DEX) and midazolam, impact cognitive function in these patients.

METHOD

This comprehensive review aims to detail the effect of DEX and midazolam on cognitive outcomes following open-heart surgery.

FINDINGS

Midazolam, a highly selective and commonly used benzodiazepine for preoperative anxiolytics and sedation has been associated with POCD. However, evidence regarding its impact on cognitive function is vague; some studies suggest a potential link between midazolam administration and cognitive impairment, while others report no effect or even an improvement in cognitive abilities. DEX is a potential neuroprotective agent in cardiac surgery. The effects of DEX on cognitive function, including a reduction in POCD incidence and severity, have been reported in several studies. It modulates the inflammatory responses, attenuates oxidative stress, and preserves cerebral perfusion. Although DEX and midazolam show promising results, their effects on cognitive function following open-heart surgery are yet to be elucidated.

CONCLUSION

Various factors, including patient characteristics, perioperative management, and surgical procedures, may influence these outcomes, highlighting the need for further research to better understand the roles of these agents in cognitive function following open-heart surgery.

Clinical Trial Data-Driven Risk Assessment of Drug-Drug Interactions: A Rapid and Accurate Decision-Making Tool

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 ork 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 andk 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 andk 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.

Physiologically Based Pharmacokinetic Modeling to Predict the Impact of Liver Cirrhosis on Glucuronidation via UGT1A4 and UGT2B7/2B4-A Case Study with Midazolam

Hepatic impairment, due to liver cirrhosis, decreases the activity of cytochrome P450 enzymes (CYPs). The use of physiologically based pharmacokinetic (PBPK) modeling to predict this effect for CYP substrates has been well-established, but the effect of cirrhosis on uridine-glucuronosyltransferase (UGT) activities is less studied and few PBPK models have been reported. UGT enzymes are involved in primary N-glucuronidation of midazolam and glucuronidation of 1'-OH-midazolam following CYP3A hydroxylation. In this study, Simcyp was used to establish PBPK models for midazolam, its primary metabolites midazolam-N-glucuronide (UGT1A4) and 1'-OH midazolam (CYP3A4/3A5), and the secondary metabolite 1'-OH-midazolam-O-glucuronide (UGT2B7/2B4), allowing to simulate the impact of liver cirrhosis on the primary and secondary glucuronidation of midazolam. The model was verified in noncirrhotic subjects before extrapolation to cirrhotic patients of Child-Pugh (CP) classes A, B, and C. Our model successfully predicted the exposures of midazolam and its metabolites in noncirrhotic and cirrhotic patients, with 86% of observed plasma concentrations within 5th-95th percentiles of predictions and observed geometrical mean of area under the plasma concentration curve between 0 hours to infinity and maximal plasma concentration within 0.7- to 1.43-fold of predictions. The simulated metabolic ratio defined as the ratio of the glucuronide metabolite AUC over the parent compound AUC (AUCglucuronide/AUCparent, metabolic ratio [MR]), was calculated for midazolam-N-glucuronide to midazolam (indicative of UGT1A4 activity) and decreased by 40% (CP A), 48% (CP B), and 75% (CP C). For 1'-OH-midazolam-O-glucuronide to 1'-OH-midazolam, the MR (indicative of UGT2B7/2B4 activity) dropped by 35% (CP A), 51% (CP B), and 64% (CP C). These predicted MRs were corroborated by the observed data. This work thus increases confidence in Simcyp predictions of the effect of liver cirrhosis on the pharmacokinetics of UGT1A4 and UGT2B7/UGT2B4 substrates. SIGNIFICANCE STATEMENT: This article presents a physiologically based pharmacokinetic model for midazolam and its metabolites and verifies the accurate simulation of pharmacokinetic profiles when using the Simcyp hepatic impairment population models. Exposure changes of midazolam-N-glucuronide and 1'-OH-midazolam-O-glucuronide reflect the impact of decreases in UGT1A4 and UGT2B7/2B4 glucuronidation activity in cirrhotic patients. The approach used in this study may be extended to verify the modeling of other uridine glucuronosyltransferase enzymes affected by liver cirrhosis.

Introducing the Dynamic Well-Stirred Model for Predicting Hepatic Clearance and Extraction Ratio

The well-stirred model (WSM) incorporating the fraction of unbound drug (fu) to account for the effect of plasma binding on intrinsic clearance has been widely used for predicting hepatic clearance under the assumption that drug protein binding reaches equilibrium instantaneously. Our theoretical analysis reveals that the effect of protein binding on intrinsic clearance is better accounted for with the dynamic free fraction (fD), a measure of drug protein binding affinity, which leads to a putative dynamic well-stirred model (dWSM) without the instantaneous equilibrium assumption. Using recombinant CYP3A4 as the in vitro clearance system, we demonstrate that the binding effect of albumin on the intrinsic clearance of both highly bound midazolam and highly free verapamil is fully corrected by their corresponding fD values, respectively. On the other hand, fu only corrects the binding effect of albumin on the intrinsic clearance of verapamil, and yields severe over-correction of the intrinsic clearance of midazolam. The results suggest that the traditional WSM is suitable for highly free drugs like verapamil but not necessarily for highly bound drugs such as midazolam due to the violation of the instantaneous equilibrium assumption or under-estimating the true free drug concentration. In comparison, the dWSM incorporating fD holds true as long as drug elimination follows steady-state kinetics, and hence, it is more broadly applicable to drugs with different protein binding characteristics. Here we demonstrate with 36 diverse drugs, that the dWSM significantly improves the accuracy of predicting human hepatic clearance and liver extraction ratio from in vitro microsomal clearance data, highlighting the importance of drug plasma protein binding kinetics in addressing the under-prediction of hepatic clearance by the WSM.

Drug-Drug Interaction Studies of Esmethadone (REL-1017) Involving CYP3A4- and CYP2D6-Mediated Metabolism

BACKGROUND AND OBJECTIVE

Esmethadone (dextromethadone; d-methadone; S-methadone (+)-methadone; REL-1017) is the opioid inactive dextro-isomer of racemic methadone. Esmethadone is a low potency N-methyl-D-aspartate (NMDA) receptor channel blocker with higher affinity for GluN2D subtypes. Esmethadone showed robust, rapid, and sustained antidepressant effects in patients with major depressive disorder (MDD) with inadequate response to ongoing serotonergic antidepressant treatment.

METHODS

Here we described the results of in vitro and phase 1 clinical trials aimed at investigating the esmethadone metabolism and possible drug-drug interactions.

RESULTS

Esmethadone is primarily metabolized to EDDP (2-ethylene-1,5-dimethyl-3,3-diphenylpyrrolidine) by multiple enzymes, including CYP3A4/5 and CYP2B6. In vitro studies showed that esmethadone inhibits CYP2D6 with IC50 of 9.6 μM and is an inducer of CYP3A4/5. The clinical relevance of the inhibition of CYP2D6 and the induction of CYP3A4 were investigated by co-administering esmethadone and dextromethorphan (a substrate for CYP2D6) or midazolam (a substrate for CYP3A4) in healthy volunteers. The administration of esmethadone at the dosage of 75 mg (which is the loading dose administered to patients in MDD clinical trials) significantly increased the exposure (AUC) of both dextromethorphan and its metabolite dextrorphan by 2.71 and 3.11-fold, respectively. Esmethadone did not modify the pharmacokinetic profile of midazolam, while it increased Cmax and AUC of its metabolite 1'-hydroxymidazolam by 2.4- and 3.8-fold, respectively. A second study evaluated the effect of the CYP3A4 inhibitor cobicistat on the pharmacokinetics of esmethadone. Cobicistat slightly increase (+32%) the total exposure (AUC0-inf) of esmethadone.

CONCLUSIONS

In summary, esmethadone demonstrated a negligible effect on CYP3A4 induction and its metabolism was not meaningfully affected by strong CYP3A4 inhibitors while it increased exposure of CYP2D6-metabolized drugs.

Distribution and elimination kinetics of midazolam and metabolites after post-resuscitation care: a prospective observational study

Administration of sedatives for post-resuscitation care can complicate the determination of the optimal timing to avoid inappropriate, pessimistic prognostications. This prospective study aimed to investigate the distribution and elimination kinetics of midazolam (MDZ) and its metabolites, and their association with awakening time. The concentrations of MDZ and its seven metabolites were measured immediately and at 4, 8, 12, and 24 h after the discontinuation of MDZ infusion, using liquid chromatography-tandem mass spectrometry. The area under the time-plasma concentration curve from 0 to 24 h after MDZ discontinuation (AUClast) was calculated based on the trapezoidal rule. Of the 15 enrolled patients, seven awakened after the discontinuation of MDZ infusion. MDZ and three of its metabolites were major compounds and their elimination kinetics followed a first-order elimination profile. In the multivariable analysis, only MDZ was associated with awakening time (AUClast: R2 = 0.59, p = 0.03; AUCinf: R2 = 0.96, p < 0.001). Specifically, a 0.001% increase in MDZ AUC was associated with a 1% increase in awakening time. In the individual regression analysis between MDZ concentration and awakening time, the mean MDZ concentration at awakening time was 16.8 ng/mL. The AUC of MDZ is the only significant factor associated with the awakening time.

Is Higher Docetaxel Clearance in Prostate Cancer Patients Explained by Higher CYP3A? An In Vivo Phenotyping Study with Midazolam

Patients with prostate cancer (PCa) have a lower docetaxel exposure for both intravenous (1.8-fold) and oral administration (2.4-fold) than patients with other solid cancers, which could influence efficacy and toxicity. An altered metabolism by cytochrome P450 3A (CYP3A) due to castration status might explain the observed difference in docetaxel pharmacokinetics. In this in vivo phenotyping, pharmacokinetic study, CYP3A activity defined by midazolam clearance (CL) was compared between patients with PCa and male patients with other solid tumors. All patients with solid tumors who did not use CYP3A-modulating drugs were eligible for participation. Patients received 2 mg midazolam orally and 1 mg midazolam intravenously on 2 consecutive days. Plasma concentrations were measured with a validated liquid chromatography-tandem mass spectrometry method. Genotyping was performed for CYP3A4 and CYP3A5. Nine patients were included in each group. Oral midazolam CL was 1.26-fold higher in patients with PCa compared to patients with other solid tumors (geometric mean [coefficient of variation], 94.1 [33.5%] L/h vs 74.4 [39.1%] L/h, respectively; P = .08). Intravenous midazolam CL did not significantly differ between the 2 groups (P = .93). Moreover, the metabolic ratio of midazolam to 1'-hydroxy midazolam did not differ between the 2 groups for both oral administration (P = .67) and intravenous administration (P = .26). CYP3A4 and CYP3A5 genotypes did not influence midazolam pharmacokinetics. The observed difference in docetaxel pharmacokinetics between both patient groups therefore appears to be explained neither by a difference in midazolam CL nor by a difference in metabolic conversion rate of midazolam.

Use of Developmental Midazolam and 1-Hydroxymidazolam Data with Pediatric Physiologically Based Modeling to Assess Cytochrome P450 3A4 and Uridine Diphosphate Glucuronosyl Transferase 2B4 Ontogeny In Vivo

Pediatric physiologically based pharmacokinetics modeling in drug development has grown in the past decade but uncertainty remains regarding ontogeny of some drug metabolizing enzymes. In this study, a midazolam and 1-hydroxymidazolam physiologically based pharmacokinetic model (PBPK) model was developed and used to define the ontogeny for hepatic cytochrome P450 (CYP) 3A4 and uridine diphosphate glucuronosyl transferase (UGT) 2B4. Data for model development and pharmacokinetic studies on intravenous midazolam in adults and pediatrics were collated from the literature. The PBPK model was verified in the adult population and then used to compare the performance of two ontogeny profiles for CYP3A4 in terms of parent drug elimination in pediatrics. Four studies also published data on the 1-hydroxymidazolam, and this was used to evaluate the known ontogeny for UGT2B4.For midazolam elimination, the Upreti CYP3A4 ontogeny performed better than Salem; mean error (bias) and mean squared error (precision) were 0.14 and 0.064 compared with 0.69 and 1.21, respectively. For 1-hydroxymidazolam elimination, the Simcyp default ontogeny of UGT2B4 appeared to perform best for studies covering the age range 0.5 to 15.7 years, while for a study in younger ages 0 to 1 years it was the Badee UGT2B4 ontogeny. In preterm neonates, overall expression of UGT appeared to be around 10% of that in adults.Identifying the optimal model of CYP3A4 ontogeny is important for the regulatory use of PBPK. The results for midazolam are conclusive but research about other CYP3A4 metabolized compounds will underpin generalizability of the CYP3A4 ontogeny. UGT2B4 ontogeny is less certain, but this study indicates the most likely scenarios. SIGNIFICANCE STATEMENT: A PBPK model for midazolam and 1-hydroxymidazolam was developed to test various ontogeny scenarios for CYP3A4 and UGT2B4. The CYP3A4 ontogeny of Upreti resulted in more accurate prediction of midazolam CL across nine clinical studies, age range birth to 18 years. 1-Hydroxy midazolam was used as a marker of UGT. The Simcyp default 'no ontogeny' profiles for UGT2B4 performed the best; however, for <1 year of age, there was some evidence of overactivity of this enzyme compared to adults.

Development of a pharmacokinetic and pharmacodynamic model for intranasal administration of midazolam in older adults: a single-site two-period crossover study

BACKGROUND

Intranasal midazolam can produce procedural sedation in frail older patients with dementia who are unable to tolerate necessary medical or dental procedures during domiciliary medical care. Little is known about the pharmacokinetics and pharmacodynamics of intranasal midazolam in older (>65 yr old) people. The aim of this study was to understand the pharmacokinetic/pharmacodynamic properties of intranasal midazolam in older people with the primary goal of developing a pharmacokinetic/pharmacodynamic model to facilitate safer domiciliary sedation care.

METHODS

We recruited 12 volunteers: ASA physical status 1-2, aged 65-80 yr, and received midazolam 5 mg intravenously and 5 mg intranasally on two study days separated by a 6 day washout period. Concentrations of venous midazolam and 1'-OH-midazolam, Modified Observer's Assessment of Alertness/Sedation (MOAA/S) score, bispectral index (BIS), arterial pressure, ECG, and respiratory parameters were measured for 10 h.

RESULTS

Time to peak effect of intranasal midazolam for BIS, MAP, and SpO₂ were 31.9 (6.2), 41.0 (7.6), and 23.1 (3.0) min, respectively. Intranasal bioavailability was lower compared with intravenous administration (F_abs 95%; 95% confidence interval: 89-100%). A three-compartment model best described midazolam pharmacokinetics following intranasal administration. A separate effect compartment linked to the dose compartment best described an observed time-varying drug-effect difference between intranasal and intravenous midazolam, suggesting direct nose-to-brain transport.

CONCLUSIONS

Intranasal bioavailability was high and sedation onset was rapid, with maximum sedative effects after 32 min. We developed a pharmacokinetic/pharmacodynamic model for intranasal midazolam for older persons and an online tool to simulate changes in MOAA/S, BIS, MAP, and SpO₂ after single and additional intranasal boluses.

CLINICAL TRIAL REGISTRATION

EudraCT (2019-004806-90).

The effects of hexabromocyclododecane on the transcriptome and hepatic enzyme activity in three human HepaRG-based models

The disruption of thyroid hormone homeostasis by hexabromocyclododecane (HBCD) in rodents is hypothesized to be due to HBCD increasing the hepatic clearance of thyroxine (T4). The extent to which these effects are relevant to humans is unclear. To evaluate HBCD effects on humans, the activation of key hepatic nuclear receptors and the consequent disruption of thyroid hormone homeostasis were studied in different human hepatic cell models. The hepatoma cell line, HepaRG, cultured as two-dimensional (2D), sandwich (SW) and spheroid (3D) cultures, and primary human hepatocytes (PHH) cultured as sandwich were exposed to 1 and 10 µM HBCD and characterized for their transcriptome changes. Pathway enrichment analysis showed that 3D models, followed by SW, had a stronger transcriptome response to HBCD, which is explained by the higher expression of hepatic nuclear receptors but also greater accumulation of HBCD measured inside cells in these models. The Pregnane X receptor pathway is one of the pathways most upregulated across the three hepatic models, followed by the constitutive androstane receptor and general hepatic nuclear receptors pathways. Lipid metabolism pathways had a downregulation tendency in all exposures and in both PHH and the three cultivation modes of HepaRG. The activity of enzymes related to PXR/CAR induction and T4 metabolism were evaluated in the three different types of HepaRG cultures exposed to HBCD for 48 h. Reference inducers, rifampicin and PCB-153 did affect 2D and SW HepaRG cultures' enzymatic activity but not 3D. HBCD did not induce the activity of any of the studied enzymes in any of the cell models and culture methods. This study illustrates that for nuclear receptor-mediated T4 disruption, transcriptome changes might not be indicative of an actual adverse effect. Clarification of the reasons for the lack of translation is essential to evaluate new chemicals' potential to be thyroid hormone disruptors by altering thyroid hormone metabolism.

Physiologically Based Pharmacokinetic Modeling for Quantitative Prediction of Exposure to a Human Disproportionate Metabolite of the Selective NaV1.7 Inhibitor DS-1971a, a Mixed Substrate of Cytochrome P450 and Aldehyde Oxidase, Using Chimeric Mice With Humanized Liver

In a previous study on the human mass balance of DS-1971a, a selective NaV1.7 inhibitor, its CYP2C8-dependent metabolite M1 was identified as a human disproportionate metabolite. The present study assessed the usefulness of pharmacokinetic evaluation in chimeric mice grafted with human hepatocytes (PXB-mice) and physiologically based pharmacokinetic (PBPK) simulation of M1. After oral administration of radiolabeled DS-1971a, the most abundant metabolite in the plasma, urine, and feces of PXB-mice was M1, while those of control SCID mice were aldehyde oxidase-related metabolites including M4, suggesting a drastic difference in the metabolism between these mouse strains. From a qualitative perspective, the metabolite profile observed in PXB-mice was remarkably similar to that in humans, but the quantitative evaluation indicated that the area under the plasma concentration-time curve (AUC) ratio of M1 to DS-1971a (M1/P ratio) was approximately only half of that in humans. A PXB-mouse-derived PBPK model was then constructed to achieve a more accurate prediction, giving an M1/P ratio (1.3) closer to that in humans (1.6) than the observed value in PXB-mice (0.69). In addition, simulated maximum plasma concentration and AUC values of M1 (3429 ng/ml and 17,116 ng·h/ml, respectively) were similar to those in humans (3180 ng/ml and 18,400 ng·h/ml, respectively). These results suggest that PBPK modeling incorporating pharmacokinetic parameters obtained with PXB-mice is useful for quantitatively predicting exposure to human disproportionate metabolites. SIGNIFICANCE STATEMENT: The quantitative prediction of human disproportionate metabolites remains challenging. This paper reports on a successful case study on the practical estimation of exposure (C max and AUC) to DS-1971a and its CYP2C8-dependent, human disproportionate metabolite M1, by PBPK simulation utilizing pharmacokinetic parameters obtained from PXB-mice and in vitro kinetics in human liver fractions. This work adds to the growing knowledge regarding metabolite exposure estimation by static and dynamic models.

Unravelling the pharmacokinetics of aflatoxin B1: In vitro determination of Michaelis–Menten constants, intrinsic clearance and the metabolic contribution of CYP1A2 and CYP3A4 in pooled human liver microsomes

Mycotoxins, fungal secondary metabolites, are ubiquitously present in food commodities. Acute exposure to high levels or chronic exposure to low levels has an impact on the human body. The phase I metabolism in the human liver, performed by cytochrome P450 (CYP450) enzymes, is accountable for more than 80% of the overall metabolism of exogenous and endogenous compounds. Mycotoxins are (partially) metabolized by CYP450 enzymes. In this study, in vitro research was performed on CYP450 probes and aflatoxin B1 (AFB1), a carcinogenic mycotoxin, to obtain pharmacokinetic data on AFB1, required for further experimental work. The CYP450 probes of choice were a CYP3A4 substrate, midazolam (MDZ) and a CYP1A2 substrate, phenacetin (PH) since these are the main metabolizing phase I enzymes of AFB1. Linearity experiments were performed on the three substrates indicating that linear conditions were achieved at a microsomal protein concentration and incubation time of 0.25 mg/ml and 5 min, 0.50 mg/ml and 20 min and 0.25 mg/ml and 5 min for MDZ, PH and AFB1, respectively. The K_m was determined in human liver microsomes and was estimated at 2.15 μM for MDZ, 40.0 μM for PH and 40.9 μM for AFB1. The associated V_max values were 956 pmol/(mg.min) (MDZ), 856 pmol/(mg.min) (PH) and 11,536 pmol/(mg.min) (AFB1). Recombinant CYP systems were used to determine CYP450-specific Michaelis–Menten values for AFB1, leading to a CYP3A4 K_m of 49.6 μM and an intersystem extrapolation factor (ISEF) corrected V_max of 43.6 pmol/min/pmol P450 and a CYP1A2 K_m of 58.2 μM and an ISEF corrected V_max of 283 pmol/min/pmol P450. An activity adjustment factor (AAF) was calculated to account for differences between microsome batches and was used as a correction factor in the determination of the human in vivo hepatic clearance for MDZ, PH and AFB1. The hepatic blood clearance corrected for the AAF CL_H,B,MDZ,AAF, CL_H,B,PH,AAF CL_{H,B,AFB1,AAF(CYP3A4)} and CL_{H,B,AFB1,AAF(CYP1A2)} were determined in HLM at 44.1 L/h, 21.7 L/h, 40.0 L/h and 38.5 L/h. Finally, inhibition assays in HLM showed that 45% of the AFB1 metabolism was performed by CYP3A4/3A5 enzymes and 49% by CYP1A2 enzymes.

CYP2C8-Mediated Formation of a Human Disproportionate Metabolite of the Selective NaV1.7 Inhibitor DS-1971a, a Mixed Cytochrome P450 and Aldehyde Oxidase Substrate

Predicting human disproportionate metabolites is difficult, especially when drugs undergo species-specific metabolism mediated by cytochrome P450s (P450s) and/or non-P450 enzymes. This study assessed human metabolites of DS-1971a, a potent Nav1.7-selective blocker, by performing human mass balance studies and characterizing DS-1971a metabolites, in accordance with the Metabolites in Safety Testing guidance. In addition, we investigated the mechanism by which the major human disproportionate metabolite (M1) was formed. After oral administration of radiolabeled DS-1971a, the major metabolites in human plasma were P450-mediated monoxidized metabolites M1 and M2 with area under the curve ratios of 27% and 10% of total drug-related exposure, respectively; the minor metabolites were dioxidized metabolites produced by aldehyde oxidase and P450s. By comparing exposure levels of M1 and M2 between humans and safety assessment animals, M1 but not M2 was found to be a human disproportionate metabolite, requiring further characterization under the Metabolites in Safety Testing guidance. Incubation studies with human liver microsomes indicated that CYP2C8 was responsible for the formation of M1. Docking simulation indicated that, in the formation of M1 and M2, there would be hydrogen bonding and/or electrostatic interactions between the pyrimidine and sulfonamide moieties of DS-1971a and amino acid residues Ser100, Ile102, Ile106, Thr107, and Asn217 in CYP2C8, and that the cyclohexane ring of DS-1971a would be located near the heme iron of CYP2C8. These results clearly indicate that M1 is the predominant metabolite in humans and a human disproportionate metabolite due to species-specific differences in metabolism. SIGNIFICANCE STATEMENT: This report is the first to show a human disproportionate metabolite generated by CYP2C8-mediated primary metabolism. We clearly demonstrate that DS-1971a, a mixed aldehyde oxidase and cytochrome P450 substrate, was predominantly metabolized by CYP2C8 to form M1, a human disproportionate metabolite. Species differences in the formation of M1 highlight the regio- and stereoselective metabolism by CYP2C8, and the proposed interaction between DS-1971a and CYP2C8 provides new knowledge of CYP2C8-mediated metabolism of cyclohexane-containing substrates.

Effect of cenobamate on the single-dose pharmacokinetics of multiple cytochrome P450 probes using a cocktail approach in healthy subjects

This study was designed to evaluate the effects of cenobamate, an antiseizure medication for focal seizures, on the pharmacokinetics of cytochrome P450 probes (bupropion, CYP2B6; midazolam, CYP3A4/5; warfarin, CYP2C9; and omeprazole, CYP2C19) in healthy subjects. Probes were administered alone on days 1 (bupropion) and 7 (midazolam/warfarin/omeprazole), and with cenobamate 100 mg/day on day 69 (midazolam) and cenobamate 200 mg/day on days 99 (bupropion) and 105 (midazolam/warfarin/omeprazole). No significant interaction was concluded if 90% confidence intervals (CIs) for geometric mean ratios (GMRs) for area under the curve (AUC) and maximum concentration of CYP substrates and/or their metabolites were within the no‐effect interval (0.80–1.25). When co‐administered with cenobamate 100 mg/day, AUC from time of administration up to the time of the last quantifiable concentration (AUC_0–last) GMR (90% CIs) for midazolam was 0.734 (0.647–0.832). When co‐administered with cenobamate 200 mg/day, AUC_0–last GMRs (90% CI) for midazolam, bupropion, S‐warfarin, and omeprazole were 0.277 (0.238–0.323), 0.615 (0.522–0.724), 1.14 (1.10–1.18), and 2.07 (1.44–2.98), respectively. Co‐administration of cenobamate with midazolam and bupropion probes led to values that were outside and below the no effect boundary, indicating that cenobamate induces the CYP3A4/5 and CYP2B6 enzymes. Co‐administration of cenobamate led to omeprazole values which were outside and above the no‐effect boundary, but with high variability, suggesting that cenobamate may moderately inhibit CYP2C19 activity. No effect on CYP2C9 was observed with the cenobamate and warfarin combination. Co‐administration of cenobamate with these probes drugs was well‐tolerated. In this study, 200 mg/day cenobamate moderately induced CYP3A4/5 (dose‐dependently; 100 mg/day was a weak inducer), was a weak inducer of CYP2B6, moderately inhibited CYP2C19, and had a negligible effect on CYP2C9.

Complex Cytochrome P450 Kinetics Due to Multisubstrate Binding and Sequential Metabolism. Part 2. Modeling of Experimental Data

Three CYP3A4 substrates, midazolam, ticlopidine, and diazepam, display non-Michaelis-Menten kinetics, form multiple primary metabolites, and are sequentially metabolized to secondary metabolites. We generated saturation curves for these compounds and analyzed the resulting datasets using a number of single-substrate and multisubstrate binding models. These models were parameterized using rate equations and numerical solutions of the ordinary differential equations. Multisubstrate binding models provided results superior to single-substrate models, and simultaneous modeling of multiple metabolites provided better results than fitting the individual datasets independently. Although midazolam datasets could be represented using standard two-substrate models, more complex models that include explicit enzyme-product complexes were needed to model the datasets for ticlopidine and diazepam. In vivo clearance predictions improved markedly with the use of in vitro parameters from the complex models versus the Michaelis-Menten equation. The results highlight the need to use sufficiently complex kinetic schemes instead of the Michaelis-Menten equation to generate accurate kinetic parameters. SIGNIFICANCE STATEMENT: The metabolism of midazolam, ticlopidine, and diazepam by CYP3A4 results in multiple metabolites and sequential metabolism. This study evaluates the use of rate equations and numerical methods to characterize the in vitro enzyme kinetics. Use of complex cytochrome P450 kinetic models is necessary to obtain accurate parameter estimates for predicting in vivo disposition.

Complex Cytochrome P450 Kinetics Due to Multisubstrate Binding and Sequential Metabolism. Part 1. Theoretical Considerations

Complexities in P450-mediated metabolism kinetics include multisubstrate binding, multiple-product formation, and sequential metabolism. Saturation curves and intrinsic clearances were simulated for single-substrate and multisubstrate models using derived velocity equations and numerical solutions of ordinary differential equations (ODEs). Multisubstrate models focused on sigmoidal kinetics because of their dramatic impact on clearance predictions. These models were combined with multiple-product formation and sequential metabolism, and simulations were performed with random error. Use of single-substrate models to characterize multisubstrate data can result in inaccurate kinetic parameters and poor clearance predictions. Comparing results for use of standard velocity equations with ODEs clearly shows that ODEs are more versatile and provide better parameter estimates. It would be difficult to derive concentration-velocity relationships for complex models, but these relationships can be easily modeled using numerical methods and ODEs. SIGNIFICANCE STATEMENT: The impact of multisubstrate binding, multiple-product formation, and sequential metabolism on the P450 kinetics was investigated. Numerical methods are capable of characterizing complicated P450 kinetics.

Prediction of cytochromes P450 3A and 2C19 modulation by both inflammation and drug interactions using physiologically based pharmacokinetics

Xenobiotics can interact with cytochromes P450 (CYPs), resulting in drug-drug interactions, but CYPs can also contribute to drug-disease interactions, especially in the case of inflammation, which downregulates CYP activities through pretranscriptional and posttranscriptional mechanisms. Interleukin-6 (IL-6), a key proinflammatory cytokine, is mainly responsible for this effect. The aim of our study was to develop a physiologically based pharmacokinetic (PBPK) model to foresee the impact of elevated IL-6 levels in combination with drug interactions with esomeprazole on CYP3A and CYP2C19. Data from a cohort of elective hip surgery patients whose CYP3A and CYP2C19 activities were measured before and after surgery were used to validate the accurate prediction of the developed models. Successive steps were to fit models for IL-6, esomeprazole, and omeprazole and its metabolite from the literature and to validate them. The models for midazolam and its metabolite were obtained from the literature. When appropriate, a correction factor was applied to convert drug concentrations from whole blood to plasma. Mean ratios between simulated and observed areas under the curve for omeprazole/5-hydroxy omeprazole, esomeprazole, and IL-6 were 1.53, 1.06, and 0.69, respectively, indicating an accurate prediction of the developed models. The impact of IL-6 and esomeprazole on the exposure to CYP3A and CYP2C19 probe substrates and respective metabolites were correctly predicted. Indeed, the ratio between predicted and observed mean concentrations were <2 for all observations (ranging from 0.51 to 1.7). The impact of IL-6 and esomeprazole on CYP3A and CYP2C19 activities after a hip surgery were correctly predicted with the developed PBPK models.

Midazolam Infusion and Disease Severity Affect the Level of Sedation in Children: A Parametric Time-to-Event Analysis

Aim

In critically ill mechanically ventilated children, midazolam is used first line for sedation, however its exact sedative effects have been difficult to quantify. In this analysis, we use parametric time-to-event (PTTE) analysis to quantify the effects of midazolam in critically ill children.

Methods

In the PTTE analysis, data was analyzed from a published study in mechanically ventilated children in which blinded midazolam or placebo infusions were administered during a sedation interruption phase until, based on COMFORT-B and NISS scores, patients became undersedated and unblinded midazolam was restarted. Using NONMEM® v.7.4.3., restart of unblinded midazolam was analysed as event. Patients in the trial were divided into internal and external validation cohorts prior to analysis.

Results

Data contained 138 events from 79 individuals (37 blinded midazolam; 42 blinded placebo). In the PTTE model, the baseline hazard was best described by a constant function. Midazolam reduced the hazard for restart of unblinded midazolam due to undersedation by 51%. In the blinded midazolam group, time to midazolam restart was 26 h versus 58 h in patients with low versus high disease severity upon admission (PRISM II < 10 versus > 21), respectively. For blinded placebo, these times were 14 h and 33 h, respectively. The model performed well in an external validation with 42 individuals.

Conclusion

The PTTE analysis effectively quantified the effect of midazolam in prolonging sedation and also the influence of disease severity on sedation in mechanically ventilated critically ill children, and provides a valuable tool to quantify the effect of sedatives.

Clinical trial number and registry URL: Netherlands Trial Register, Trial NL1913 (NTR2030), date registered 28 September 2009 https://www.trialregister.nl/trial/1913.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-021-03113-w.

MetaClass, a Comprehensive Classification System for Predicting the Occurrence of Metabolic Reactions Based on the MetaQSAR Database

(1) Background: Machine learning algorithms are finding fruitful applications in predicting the ADME profile of new molecules, with a particular focus on metabolism predictions. However, the development of comprehensive metabolism predictors is hampered by the lack of highly accurate metabolic resources. Hence, we recently proposed a manually curated metabolic database (MetaQSAR), the level of accuracy of which is well suited to the development of predictive models. (2) Methods: MetaQSAR was used to extract datasets to predict the metabolic reactions subdivided into major classes, classes and subclasses. The collected datasets comprised a total of 3788 first-generation metabolic reactions. Predictive models were developed by using standard random forest algorithms and sets of physicochemical, stereo-electronic and constitutional descriptors. (3) Results: The developed models showed satisfactory performance, especially for hydrolyses and conjugations, while redox reactions were predicted with greater difficulty, which was reasonable as they depend on many complex features that are not properly encoded by the included descriptors. (4) Conclusions: The generated models allowed a precise comparison of the propensity of each metabolic reaction to be predicted and the factors affecting their predictability were discussed in detail. Overall, the study led to the development of a freely downloadable global predictor, MetaClass, which correctly predicts 80% of the reported reactions, as assessed by an explorative validation analysis on an external dataset, with an overall MCC = 0.44.

A fast and simple method for the simultaneous analysis of midazolam, 1-hydroxymidazolam, 4-hydroxymidazolam and 1-hydroxymidazolam glucuronide in human serum, plasma and urine

For the quantification of the sedative and anesthetic drug midazolam and its main (active) metabolites 1-hydroxymidazolam, 4-hydroxymidazolam and 1-hydroxymidazolam glucuronide in human serum, human EDTA plasma, human heparin plasma and human urine a single accurate method by ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) has been developed. Protein precipitation as sample preparation, without the need of a time-consuming deglucuronidation step for the quantification of 1-hydroxymidazolam glucuronide, resulted in a simple and rapid assay suitable for clinical practice with a total runtime of only 1.1  min. The four components and the isotope-labeled internal standards were separated on a C₁₈ column and detection was performed with a triple-stage quadrupole mass spectrometer operating in positive ionization mode. The method was validated based on the "Guidance for Industry Bioanalytical Method Validation" (Food and Drug Administration, FDA) and the "Guideline on bioanalytical method validation" of the European Medicines Agency (EMA). Linearity was proven over the ranges of 5-1500 μg/L for midazolam, 1-hydroxymidazolam and 4-hydroxymidazolam and 25-5000 μg/L for 1-hydroxymidazolam glucuronide, using a sample volume of 100 μL. Matrix comparison indicated that the assay is also applicable to other human matrices like EDTA and heparin plasma and urine. Stability experiments showed good results for the stability of midazolam, 1-hydroxymidazolam and 1-hydroxymidazolam glucuronide in serum, EDTA and heparin plasma and urine stored for 7 days under different conditions. At room temperature, 4-hydroxymidazo-lam is stable for 7 days in EDTA plasma, but stable for only 3 days in serum and heparin plasma and less than 24 h in urine. All four compounds were found to be stable in serum, EDTA plasma, heparin plasma and urine for 7 days after sample preparation and for 3 freeze-thaw cycles. The assay has been applied in therapeutic drug monitoring of midazolam for (pediatric) intensive care patients.

PBPK modeling of CYP3A and P-gp substrates to predict drug-drug interactions in patients undergoing Roux-en-Y gastric bypass surgery

Roux-en-Y gastric bypass surgery (RYGBS) is an effective surgical intervention to reduce mortality in morbidly obese patients. Following RYGBS, the disposition of drugs may be affected by anatomical alterations and changes in intestinal and hepatic drug metabolizing enzyme activity. The aim of this study was to better understand the drug-drug interaction (DDI) potential of CYP3A and P-gp inhibitors. The impacts of RYGBS on the absorption and metabolism of midazolam, acetaminophen, digoxin, and their major metabolites were simulated using physiologically-based pharmacokinetic (PBPK) modeling. PBPK models for verapamil and posaconazole were built to evaluate CYP3A- and P-gp-mediated DDIs pre- and post-RYGBS. The simulations suggest that for highly soluble drugs, such as verapamil, the predicted bioavailability was comparable pre- and post-RYGBS. For verapamil inhibition, RYGBS did not affect the fold-change of the predicted inhibited-to-control plasma AUC ratio or predicted inhibited-to-control peak plasma concentration ratio for either midazolam or digoxin. In contrast, the predicted bioavailability of posaconazole, a poorly soluble drug, decreased from 12% pre-RYGBS to 5% post-RYGBS. Compared to control, the predicted posaconazole-inhibited midazolam plasma AUC increased by 2.0-fold pre-RYGBS, but only increased by 1.6-fold post-RYGBS. A similar trend was predicted for pre- and post-RYGBS inhibited-to-control midazolam peak plasma concentration ratios (2.0- and 1.6-fold, respectively) following posaconazole inhibition. Absorption of highly soluble drugs was more rapid post-RYGBS, resulting in higher predicted midazolam peak plasma concentrations, which was further increased following inhibition by verapamil or posaconazole. To reduce the risk of a drug-drug interaction in patients post-RYGBS, the dose or frequency of object drugs may need to be decreased when administered with highly soluble inhibitor drugs, especially if toxicities are associated with plasma peak concentrations.

A Novel Study Design Using Continuous Intravenous and Intraduodenal Infusions of Midazolam and Voriconazole for Mechanistic Quantitative Assessment of Hepatic and Intestinal CYP3A Inhibition

The extent of a drug-drug interaction (DDI) mediated by cytochrome P450 (CYP) 3A inhibitors is highly variable during a dosing interval, as it depends on the temporal course of victim and perpetrator drug concentrations at intestinal and hepatic CYP3A expression sites. Capturing the time course of inhibition is therefore difficult using standard DDI studies assessing changes in area under the curve; thus, a novel design was developed. In a 4-period changeover pilot study, 6 healthy men received intraduodenal or intravenous infusions of the CYP3A substrate midazolam (MDZ) at a rate of 0.26 mg/h for 24 hours. This was combined with intraduodenal or intravenous infusion of the CYP3A inhibitor voriconazole (VRZ), administered at rates of 7.5 mg/h from 8 to 16 hours and of 15 mg/h from 16 to 24 hours, after starting midazolam administration. Plasma and urine concentrations of VRZ, MDZ, and its major metabolites were quantified by liquid chromatography-tandem mass spectrometry and analyzed by semiphysiological population pharmacokinetic nonlinear mixed-effects modeling. A model including mechanism-based inactivation of the metabolizing enzymes (maximum inactivation rate constant k_inact , 2.83 h^-1 ; dissociation rate constant K I , 9.33 μM) described the pharmacokinetics of VRZ well. By introducing competitive inhibition by VRZ on primary and secondary MDZ metabolism, concentration-time profiles, MDZ and its metabolites were captured appropriately. The model provides estimates of local concentrations of substrate and inhibitor at the major CYP3A expression sites and thus of the respective dynamic extent of inhibition. A combination of intravenous and intraduodenal infusions of inhibitors and substrates has the potential to provide a more accurate assessment of DDIs occurring in both gut wall and liver.

Effective Application of Metabolite Profiling in Drug Design and Discovery

At one time, biotransformation was a descriptive activity in pharmaceutical development, viewed simply as structural elucidation of drug metabolites, completed only once compounds entered clinical development. Herein, we present our strategic approach using structural elucidation to enable chemistry design/SAR development. The approach considers four questions that often present themselves to medicinal chemists optimizing their compounds for candidate selection: (1) What are the important clearance mechanisms that mediate the disposition of my molecule? (2) Can metabolic liabilities be modulated in a favorable way? (3) Does my compound undergo bioactivation to a reactive metabolite? (4) Do any of the metabolites possess activity, either on- or off-target? An additional question necessary to support compound development relates to metabolites in safety testing (MIST) and our approach also addresses this question. The value in structural elucidation is derived from its application to better design molecules, guide their clinical development, and underwrite patient safety.

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

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

Prediction of Metabolite-to-Parent Drug Exposure: Derivation and Application of a Mechanistic Static Model

In the development of new drugs, the prediction of metabolite‐to‐parent plasma exposure ratio in humans prior to administration in a clinical study has emerged as an important need. In this work, we derived a mechanistic static model based on first principles to estimate metabolite‐to‐parent plasma exposure ratio, considering the contribution of liver and gut metabolism and drug transport. Knowledge (or assumptions) of mechanisms of clearance and organs involved is required. Input parameters needed included intrinsic clearance, fraction of clearance to the metabolite of interest, various binding values, and, in some cases, active transport clearance. The principles are illustrated with four drugs that yield six metabolites, with one in which clearance is dependent on a pathway subject to genetic polymorphism. Overall, the approach yielded metabolite‐to‐parent ratios within about twofold of the actual values and, thus, can be valuable in decision making in the drug development process.

Complex DDI by Fenebrutinib and the Use of Transporter Endogenous Biomarkers to Elucidate the Mechanism of DDI

Mechanistic understanding of complex clinical drug-drug interactions (DDIs) with potential involvement of multiple elimination pathways has been challenging, especially given the general lack of specific probe substrates for transporters. Here, we conducted a clinical DDI study to evaluate the interaction potential of fenebrutinib using midazolam (MDZ; CYP3A), simvastatin (CYP3A and OATP1B), and rosuvastatin (BCRP and OATP1B) as probe substrates. Fenebrutinib (200 mg) increased the area under the curve (AUC) of these probe substrates twofold to threefold. To evaluate the mechanism of the observed DDIs, we measured the concentration of coproporphyrin I (CP-I) and coproporphyrin III (CP-III), endogenous biomarkers of OATP1B. There was no change in CP-I or CP-III levels with fenebrutinib, suggesting that the observed DDIs were caused by inhibition of CYP3A and BCRP rather than OATP1B, likely due to increased bioavailability. This is the first published account using an endogenous transporter biomarker to understand the mechanism of complex DDIs involving multiple elimination pathways.

Biotransformation of the Mycotoxin Enniatin B1 by CYP P450 3A4 and Potential for Drug-Drug Interactions

Enniatins (ENNs) are fungal secondary metabolites that frequently occur in grain in temperate climates. Their toxic potency is connected to their ionophoric character and lipophilicity. The biotransformation of ENNs predominantly takes place via cytochrome P450 3A (CYP 3A)-dependent oxidation reactions. Possible interaction with ENNs is relevant since CYP3A4 is the main metabolic enzyme for numerous drugs and contaminants. In the present study, we have determined the kinetic characteristics and inhibitory potential of ENNB1 in human liver microsomes (HLM) and CYP3A4-containing nanodiscs (ND). We showed in both in vitro systems that ENNB1 is mainly metabolised by CYP3A4, producing at least eleven metabolites. Moreover, ENNB1 significantly decreased the hydroxylation rates of the typical CYP3A4-substrate midazolam (MDZ). Deoxynivalenol (DON), which is the most prevalent mycotoxin in grain and usually co-occurrs with the ENNs, was not metabolised by CYP3A4 or binding to its active site. Nevertheless, DON affected the efficiency of this biotransformation pathway both in HLM and ND. The metabolite formation rates of ENNB1 and the frequently used drugs progesterone (PGS) and atorvastatin (ARVS) lactone were noticeably reduced, which indicated a certain affinity of DON to the enzyme with subsequent conformational changes. Our results emphasise the importance of drug-drug interaction studies, also with regard to natural toxins.

Prolonged Anesthetic Recovery after Continuous Infusion of Midazolam in 2 Domestic Cats (Felis catus)

Two healthy research cats involved in a randomized, blinded prospective pharmacodynamics study evaluating midazolam continuous-rate infusion as a means to decrease sevoflurane concentrations experienced unexpectedly prolonged recoveries. Midazolam loading doses, infusion rates, and the targeted plasma midazolam concentrations at steady-state were determined by pharmacokinetic modeling based on the results of a preliminary pharmacokinetic study using a single dose of midazolam. In the pharmacodynamics study, cats remained oversedated after recovery from anesthesia, and plasma concentrations of midazolam and its primary metabolite (1-hydroxymidazolam) remained elevated. The use of flumazenil was unsuccessful in timely treatment of oversedation. Administration of intravenous lipid emulsion was used in one of the cats to facilitate recovery and appeared to be effective in both reducing the depth of midazolam-induced oversedation and significantly reducing the plasma concentration of 1-hydroxymidazolam. The effects after the administration of both treatment modalities on clinical signs and plasma drug concentrations in cats are discussed. The observations suggest that cats may eliminate 1-hydroxymidazolam more slowly than expected; consequently dose adjustments may be required when continuous infusion of midazolam is intended. In addition, intravenous lipid emulsion may facilitate recovery from midazolam oversedation, particularly in cases unresponsive to traditional treatment modalities. However, further investigations are warranted to delineate the efficacy of this modality in the treatment of midazolam oversedation.

In Vitro and In Vivo Correlation of Hepatic Fraction of Metabolism by P450 in Dogs

1-Aminobenzotriazole (ABT) has been widely used as a nonspecific mechanism-based inhibitor of cytochrome P450 (P450) enzymes. It is extensively used in preclinical studies to determine the relative contribution of oxidative metabolism mediated by P450 in vitro and in vivo. The aim of present study was to understand the translation of fraction metabolized by P450 in dog hepatocytes to in vivo using ABT, for canagliflozin, known to be cleared by P450-mediated oxidation and UDP-glucuronosyltransferases-mediated glucuronidation, and 3 drug discovery project compounds mainly cleared by hepatic metabolism. In a dog hepatocyte, intrinsic clearance assay with and without preincubation of ABT, 3 Lilly compounds exhibited a wide range of fraction metabolized by P450. Subsequent metabolite profiling in dog hepatocytes demonstrated a combination of metabolism by P450 and UDP-glucuronosyltransferases. In vivo, dogs were pretreated with 50 mg/kg ABT or vehicle at 2 h before intravenous administration of canagliflozin and Lilly compounds. The areas under the concentration-time curve (AUC) were compared for the ABT-pretreated and vehicle-pretreated groups. The measured AUC_ABT/AUC_veh ratios were correlated to fraction of metabolism by P450 in dog hepatocytes, suggesting that in vitro ABT inhibition in hepatocytes is useful to rank order compounds for in vivo fraction of metabolism assessment.

Improved Predictions of Drug-Drug Interactions Mediated by Time-Dependent Inhibition of CYP3A

Time-dependent inactivation (TDI) of cytochrome P450s (CYPs) is a leading cause of clinical drug-drug interactions (DDIs). Current methods tend to overpredict DDIs. In this study, a numerical approach was used to model complex CYP3A TDI in human-liver microsomes. The inhibitors evaluated included troleandomycin (TAO), erythromycin (ERY), verapamil (VER), and diltiazem (DTZ) along with the primary metabolites N-demethyl erythromycin (NDE), norverapamil (NV), and N-desmethyl diltiazem (NDD). The complexities incorporated into the models included multiple-binding kinetics, quasi-irreversible inactivation, sequential metabolism, inhibitor depletion, and membrane partitioning. The resulting inactivation parameters were incorporated into static in vitro-in vivo correlation (IVIVC) models to predict clinical DDIs. For 77 clinically observed DDIs, with a hepatic-CYP3A-synthesis-rate constant of 0.000 146 min-1, the average fold difference between the observed and predicted DDIs was 3.17 for the standard replot method and 1.45 for the numerical method. Similar results were obtained using a synthesis-rate constant of 0.000 32 min-1. These results suggest that numerical methods can successfully model complex in vitro TDI kinetics and that the resulting DDI predictions are more accurate than those obtained with the standard replot approach.

Estimation of Circulating Drug Metabolite Exposure in Human Using In Vitro Data and Physiologically Based Pharmacokinetic Modeling: Example of a High Metabolite/Parent Drug Ratio

(R)-4-((4-(((4-((tetrahydrofuran-3-yl)oxy)benzo[d]isoxazol-3-yl)oxy)methyl)piperidin-1-yl)methyl)tetrahydro-2H-pyran-4-ol (TBPT), a serotonin-4 receptor partial agonist, is metabolized to two metabolites: an N-dealkylation product [(R)-3-(piperidin-4-ylmethoxy)-4-((tetrahydrofuran-3-yl)oxy)benzo[d]isoxazole (M1)] and a cyclized oxazolidine structure [7-(((4-(((R)-tetrahydrofuran-3-yl)oxy)benzo[d]isoxazol-3-yl)oxy)methyl)octahydro-3H (M2)]. After administration of TBPT to humans the exposure to M1 was low and the exposure to M2 was high, relative to the parent drug, despite this being the opposite in vitro. In this study, projection of the plasma metabolite/parent (M/P) ratios for M1 and M2 was attempted using in vitro metabolism, binding, and permeability data in static and dynamic physiologically based pharmacokinetic (PBPK) models. In the static model, the fraction of parent clearance yielding the metabolite (which also required taking into account secondary metabolites of M1 and M2), the clearance of the metabolites and parent, and an estimate of the availability of the metabolites from the liver were combined to yield estimated parent/metabolite ratios of 0.32 and 23 for M1 and M2, respectively. PBPK modeling that used in vitro and physicochemical data input yielded estimates of 0.26 and 20, respectively. The actual values were 0.12 for M1/TBPT and 58 for M2/TBPT. Thus, the ratio for M1 was overpredicted, albeit at values less than unity. The ratio for M2/TBPT was underpredicted, and the high ratio of 58 may exceed a limiting ceiling of the approach. Nevertheless, when considered in the context of determining whether a potential circulating metabolite may be quantitatively important prior to administration of a drug for the first time to humans, the approaches succeeded in highlighting the importance of M2 (M/P ratio >> 1) relative to M1, despite M1 being much greater than M2 in vitro.

Quantitative Prediction of Drug-Drug Interactions Involving Inhibitory Metabolites in Drug Development: How Can Physiologically Based Pharmacokinetic Modeling Help?

This subteam under the Drug Metabolism Leadership Group (Innovation and Quality Consortium) investigated the quantitative role of circulating inhibitory metabolites in drug-drug interactions using physiologically based pharmacokinetic (PBPK) modeling. Three drugs with major circulating inhibitory metabolites (amiodarone, gemfibrozil, and sertraline) were systematically evaluated in addition to the literature review of recent examples. The application of PBPK modeling in drug interactions by inhibitory parent-metabolite pairs is described and guidance on strategic application is provided.

The Use of In Vitro Data and Physiologically-Based Pharmacokinetic Modeling to Predict Drug Metabolite Exposure: Desipramine Exposure in Cytochrome P4502D6 Extensive and Poor Metabolizers Following Administration of Imipramine

Major circulating drug metabolites can be as important as the drugs themselves in efficacy and safety, so establishing methods whereby exposure to major metabolites following administration of parent drug can be predicted is important. In this study, imipramine, a tricyclic antidepressant, and its major metabolite desipramine were selected as a model system to develop metabolite prediction methods. Imipramine undergoes N-demethylation to form the active metabolite desipramine, and both imipramine and desipramine are converted to hydroxylated metabolites by the polymorphic enzyme CYP2D6. The objective of the present study is to determine whether the human pharmacokinetics of desipramine following dosing of imipramine can be predicted using static and dynamic physiologically-based pharmacokinetic (PBPK) models from in vitro input data for CYP2D6 extensive metabolizer (EM) and poor metabolizer (PM) populations. The intrinsic metabolic clearances of parent drug and metabolite were estimated using human liver microsomes (CYP2D6 PM and EM) and hepatocytes. Passive diffusion clearance of desipramine, used in the estimation of availability of the metabolite, was predicted from passive permeability and hepatocyte surface area. The predicted area under the curve (AUCm/AUCp) of desipramine/imipramine was 12- to 20-fold higher in PM compared with EM subjects following i.v. or oral doses of imipramine using the static model. Moreover, the PBPK model was able to recover simultaneously plasma profiles of imipramine and desipramine in populations with different phenotypes of CYP2D6. This example suggested that mechanistic PBPK modeling combined with information obtained from in vitro studies can provide quantitative solutions to predict in vivo pharmacokinetics of drugs and major metabolites in a target human population.

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

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

A Pharmacokinetic Modeling Approach to Predict the Contribution of Active Metabolites to Human Efficacious Dose

A preclinical drug candidate, MRK-1 (Merck candidate drug parent compound), was found to elicit tumor regression in a mouse xenograft model. Analysis of samples from these studies revealed significant levels of two circulating metabolites, whose identities were confirmed by comparison with authentic standards using liquid chromatography-tandem mass spectrometry. These metabolites were found to have an in vitro potency similar to that of MRK-1 against the pharmacological target and were therefore thought to contribute to the observed efficacy. To predict this contribution in humans, a pharmacokinetic (PK) modeling approach was developed. At the mouse efficacious dose, the areas under the plasma concentration time curves (AUCs) of the active metabolites were normalized by their in vitro potency compared with MRK-1. These normalized metabolite AUCs were added to that of MRK-1 to yield a composite efficacious unbound AUC, expressed as "parent drug equivalents," which was used as the target AUC for predictions of the human efficacious dose. In vitro and preclinical PK studies afforded predictions of the PK of MRK-1 and the two active metabolites in human as well as the relative pathway flux to each metabolite. These were used to construct a PK model (Berkeley Madonna, version 8.3.18; Berkeley Madonna Inc., University of California, Berkeley, CA) and to predict the human dose required to achieve the target parent equivalent exposure. These predictions were used to inform on the feasibility of the human dose in terms of size, frequency, formulation, and likely safety margins, as well as to aid in the design of preclinical safety studies.