Are there differences in the catalytic activity per unit enzyme of recombinantly expressed and human liver microsomal cytochrome P450 2C9? A systematic investigation into inter-system extrapolation factors

Enzyme-mediated drug-drug interactions: a review of in vivo and in vitro methodologies, regulatory guidance, and translation to the clinic

Enzyme-mediated pharmacokinetic drug-drug interactions can be caused by altered activity of drug metabolizing enzymes in the presence of a perpetrator drug, mostly via inhibition or induction. We identified a gap in the literature for a state-of-the art detailed overview assessing this type of DDI risk in the context of drug development. This manuscript discusses in vitro and in vivo methodologies employed during the drug discovery and development process to predict clinical enzyme-mediated DDIs, including the determination of clearance pathways, metabolic enzyme contribution, and the mechanisms and kinetics of enzyme inhibition and induction. We discuss regulatory guidance and highlight the utility of in silico physiologically-based pharmacokinetic modeling, an approach that continues to gain application and traction in support of regulatory filings. Looking to the future, we consider DDI risk assessment for targeted protein degraders, an emerging small molecule modality, which does not have recommended guidelines for DDI evaluation. Our goal in writing this report was to provide early-career researchers with a comprehensive view of the enzyme-mediated pharmacokinetic DDI landscape to aid their drug development efforts.

Phase I Metabolism of Pterostilbene, a Dietary Resveratrol Derivative: Metabolite Identification, Species Differences, Isozyme Contribution, and Further Bioactivation

Pterostilbene (PTE), a dietary derivative of resveratrol, displayed pleiotropic health-promoting activities. This study aimed to explore the metabolic profiles and species differences of the phase I metabolism of PTE and to investigate subsequent detoxification after PTE bioactivation. PTE was found to be biotransformed to two pharmacologically active metabolites, pinostilbene and 3'-hydroxypterostilbene, in vivo and in vitro with substantial species differences. Human CYP1A2 was proved to be mainly responsible for the demethylation and 3'-hydroxylation of PTE, with its contribution to a demethylation of 94.5% and to a 3'-hydroxylation of 97.9%. An in vitro glutathione trapping experiment revealed the presence of an ortho-quinone intermediate formed by further oxidation of 3'-hydroxypterostilbene. Human glutathione S-transferase isoforms A2, T1, and A1 inactivated the ortho-quinone intermediate by catalyzing glutathione conjugation, implicating a potential protective pathway against PTE bioactivation-derived toxicity. Overall, this study provided a comprehensive view of PTE phase I metabolism and facilitated its further development as a promising nutraceutical.

In vitro-in silico-based prediction of inter-individual and inter-ethnic variations in the dose-dependent cardiotoxicity of R- and S-methadone in humans

New approach methodologies predicting human cardiotoxicity are of interest to support or even replace in vivo-based drug safety testing. The present study presents an in vitro–in silico approach to predict the effect of inter-individual and inter-ethnic kinetic variations in the cardiotoxicity of R- and S-methadone in the Caucasian and the Chinese population. In vitro cardiotoxicity data, and metabolic data obtained from two approaches, using either individual human liver microsomes or recombinant cytochrome P450 enzymes (rCYPs), were integrated with physiologically based kinetic (PBK) models and Monte Carlo simulations to predict inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. Chemical specific adjustment factors were defined and used to derive dose–response curves for the sensitive individuals. Our simulations indicated that Chinese are more sensitive towards methadone-induced cardiotoxicity with Margin of Safety values being generally two-fold lower than those for Caucasians for both methadone enantiomers. Individual PBK models using microsomes and PBK models using rCYPs combined with Monte Carlo simulations predicted similar inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. The present study illustrates how inter-individual and inter-ethnic variations in cardiotoxicity can be predicted by combining in vitro toxicity and metabolic data, PBK modelling and Monte Carlo simulations. The novel methodology can be used to enhance cardiac safety evaluations and risk assessment of chemicals.

Development and Performance Verification of the PBPK Model for Antazoline and Its Metabolite and Its Utilization for Pharmacological Hypotheses Formulating

Antazoline is an antihistaminic drug that is effective in the termination of paroxysmal atrial fibrillation. Despite its long presence in the market, antazoline’s ADME parameters and pharmacokinetic effects in humans are poorly characterized. The objective of this study was to fill this gap by generation of in vitro and in vivo data and the development of a physiologically based pharmacokinetic model describing antazoline and its main metabolite disposition. A set of ADME parameters for the antazoline and its hydroxy metabolite is provided based on literature data, QSAR predictions, in vitro binding and metabolic stability assays. These can be used to feed PBPK models. In our current work, the developed PBPK model simulating simultaneously the pharmacokinetic profile of antazoline and its metabolite was successfully verified against the available clinical data and the presented capability to account for the clinically observed variability. When used to feed the PD model (e.g., simulating ECG), concentration-time profiles predicted by the model enable the assessment of antazoline’s effect in various clinical scenarios with the possibility to account for population differences or CP mediated drug-drug interactions.

Predicting human pharmacokinetics from preclinical data: clearance

We have streamlined known in vitro methods used to predict the clearance (CL) of small molecules in humans in this tutorial. There have been many publications on in vitro methods that are used at different steps of human CL prediction. The steps from initial intrinsic CL measurement in vitro to the final application of the well-stirred model to obtain predicted hepatic CL (CL_H) are somewhat complicated. Except for the experts on drug metabolism and PBPK, many drug development scientists found it hard to figure out the entire picture of human CL prediction. To help readers overcome this barrier, we introduce each method briefly and demonstrate its usage in the chain of related equations destined to the CL_H. Despite efforts in the laboratory steps, huge in vitro (predicted CL_H)-in vivo (observed CL_H) discrepancy is not rare. A simple remedy to this discrepancy is to correct human predicted CL_H using the ratio of in vitro-in vivo CL_H obtained from animal species.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Predict the Impact of CYP2C9 Genetic Polymorphisms, Co-Medication and Formulation on the Pharmacokinetics and Pharmacodynamics of Flurbiprofen

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models can serve as a powerful framework for predicting the influence as well as the interaction of formulation, genetic polymorphism and co-medication on the pharmacokinetics and pharmacodynamics of drug substances. In this study, flurbiprofen, a potent non-steroid anti-inflammatory drug, was chosen as a model drug. Flurbiprofen has absolute bioavailability of ~95% and linear pharmacokinetics in the dose range of 50–300 mg. Its absorption is considered variable and complex, often associated with double peak phenomena, and its pharmacokinetics are characterized by high inter-subject variability, mainly due to its metabolism by the polymorphic CYP2C9 (fmCYP2C9 ≥ 0.71). In this study, by leveraging in vitro, in silico and in vivo data, an integrated PBPK/PD model with mechanistic absorption was developed and evaluated against clinical data from PK, PD, drug-drug and gene-drug interaction studies. The PBPK model successfully predicted (within 2-fold) 36 out of 38 observed concentration-time profiles of flurbiprofen as well as the CYP2C9 genetic effects after administration of different intravenous and oral dosage forms over a dose range of 40–300 mg in both Caucasian and Chinese healthy volunteers. All model predictions for C_max, AUC_inf and CL/F were within two-fold of their respective mean or geometric mean values, while 90% of the predictions of C_max, 81% of the predictions of AUC_inf and 74% of the predictions of Cl/F were within 1.25 fold. In addition, the drug-drug and drug-gene interactions were predicted within 1.5-fold of the observed interaction ratios (AUC, C_max ratios). The validated PBPK model was further expanded by linking it to an inhibitory E_max model describing the analgesic efficacy of flurbiprofen and applying it to explore the effect of formulation and genetic polymorphisms on the onset and duration of pain relief. This comprehensive PBPK/PD analysis, along with a detailed translational biopharmaceutic framework including appropriately designed biorelevant in vitro experiments and in vitro-in vivo extrapolation, provided mechanistic insight on the impact of formulation and genetic variations, two major determinants of the population variability, on the PK/PD of flurbiprofen. Clinically relevant specifications and potential dose adjustments were also proposed. Overall, the present work highlights the value of a translational PBPK/PD approach, tailored to target populations and genotypes, as an approach towards achieving personalized medicine.

Application of Azamulin to Determine the Contribution of CYP3A4/5 to Drug Metabolic Clearance Using Human Hepatocytes

Early determination of CYP3A4/5 contribution to the clearance of new chemical entities is critical to inform on the risk of drug-drug interactions with CYP3A inhibitors and inducers. Several in vitro approaches (recombinant P450 enzymes, correlation analysis, chemical and antibody inhibition in human liver microsomes) are available, but they are usually labor-intensive and/or suffer from specific limitations. In the present study, we have validated the use of azamulin as a specific CYP3A inhibitor in human hepatocytes. Azamulin (3 µM) was found to significantly inhibit CYP3A4/5 (>90%), whereas other P450 enzymes were not affected (less than 20% inhibition). Because human hepatocytes were used as a test system, the effect of azamulin on other key drug-metabolizing enzymes (aldehyde oxidase, carboxylesterase, UGT, flavin monooxygenase, and sulfotransferase) was also investigated. Apart from some UGTs showing minor inhibition (∼20%-30%), none of these non-P450 enzymes were inhibited by azamulin. Use of CYP3A5-genotyped human hepatocyte batches in combination with CYP3cide demonstrated that azamulin (at 3 µM) inhibits both CYP3A4 and CYP3A5 enzymes. Finally, 11 compounds with known in vivo CYP3A4/5 contribution have been evaluated in this human hepatocyte assay. Results showed that the effect of azamulin on the in vitro intrinsic clearance of these known CYP3A4/5 substrates was predictive of the in vivo CYP3A4/5 contribution. Overall, the study showed that human hepatocytes treated with azamulin provide a fast and accurate estimation of CYP3A4/5 contribution in metabolic clearance of new chemical entities. SIGNIFICANCE STATEMENT: Accurate estimation of CYP3A4/5 contribution in drug clearance is essential to anticipate risk of drug-drug interactions and select the appropriate candidate for clinical development. The present study validated the use of azamulin as selective CYP3A4/5 inhibitor in suspended human hepatocytes and demonstrated that this novel approach provides a direct and accurate determination of the contribution of CYP3A4/5 (fraction metabolized by CYP3A4/5) in the metabolic clearance of new chemical entities.

Simulation of the Pharmacokinetics of Oseltamivir and Its Active Metabolite in Normal Populations and Patients with Hepatic Cirrhosis Using Physiologically Based Pharmacokinetic Modeling

Oseltamivir is a neuraminidase inhibitor widely used to treat and prevent influenza A and B infections, although its safety and pharmacokinetics have not been evaluated in patients with severe hepatic impairment. A physiologically based pharmacokinetic (PBPK) model of the prodrug oseltamivir and its active metabolite, oseltamivir carboxylate (OC), was established and validated to simulate their disposition in adults and predict the exposure in patients with Child-Pugh C cirrhosis (CP-C). The simulated results from PBPK modeling and the observed data after oral administration of various oseltamivir regimens were consistent according to the fold error values of less than 2. Furthermore, the clinical observations published in the literature were comparable with our pharmacokinetic predictions. In patients with CP-C, the oseltamivir C_max was approximately 2-fold increased, and its AUC was approximately 6-fold higher compared with those in normal subjects. In contrast, the AUC of OC in CP-C patients did not differ significantly from that in normal subjects, whereas its C_max was reduced by approximately 30% in the patients. Examination of drug exposure in different health conditions indicated that the oseltamivir exposure was significantly increased in conditions with elevated cirrhosis severity, which might be associated with a higher risk of adverse drug effects, e.g., neuropsychiatric adverse events (NPAEs). In conclusion, the pharmacokinetics of oseltamivir and OC were correctly predicted by PBPK modeling. The model further predicted that the pharmacokinetics of oseltamivir might be altered in liver cirrhosis, depending on the degree of severity.

Physiologically Based Pharmacokinetic Modelling of Cytochrome P450 2C9-Related Tolbutamide Drug Interactions with Sulfaphenazole and Tasisulam

Background and Objectives

Cytochrome P450 2C9 (CYP2C9) is involved in the biotransformation of many commonly used drugs, and significant drug interactions have been reported for CYP2C9 substrates. Previously published physiologically based pharmacokinetic (PBPK) models of tolbutamide are based on an assumption that its metabolic clearance is exclusively through CYP2C9; however, many studies indicate that CYP2C9 metabolism is only responsible for 80–90% of the total clearance. Therefore, these models are not useful for predicting the magnitude of CYP2C9 drug–drug interactions (DDIs). This paper describes the development and verification of SimCYP^®-based PBPK models that accurately describe the human pharmacokinetics of tolbutamide when dosed alone or in combination with the CYP2C9 inhibitors sulfaphenazole and tasisulam.

Methods

A PBPK model was optimized in SimCYP^® for tolbutamide as a CYP2C9 substrate, based on published in vitro and clinical data. This model was verified to replicate the magnitude of DDI reported with sulfaphenazole and was further applied to simulate the DDI with tasisulam, a small molecule investigated for the treatment of cancer. A clinical study (CT registration # NCT01185548) was conducted in patients with cancer to assess the pharmacokinetic interaction of tasisulum with tolbutamide. A PBPK model was built for tasisulam, and the clinical study design was replicated using the optimized tolbutamide model.

Results

The optimized tolbutamide model accurately predicted the magnitude of tolbutamide AUC increase (5.3–6.2-fold) reported for sulfaphenazole. Furthermore, the PBPK simulations in a healthy volunteer population adequately predicted the increase in plasma exposure of tolbutamide in patients with cancer (predicted AUC ratio = 4.7–5.4; measured mean AUC ratio = 5.7).

Conclusions

This optimized tolbutamide PBPK model was verified with two strong CYP2C9 inhibitors and can be applied to the prediction of CYP2C9 interactions for novel inhibitors. Furthermore, this work highlights the utility of mechanistic models in navigating the challenges in conducting clinical pharmacology studies in cancer patients.

Predicted contributions of cytochrome P450s to drug metabolism in human liver microsomes using relative activity factor were dependent on probes

Contributions of cytochrome P450 (CYP450) isoforms to drug metabolism are often predicted using relative activity factor (RAF) method, assuming RAF values were independent of probe. We aimed to report probe-dependent characteristic of RAF values using CYP3A4 or CYP2C9 probes. Metabolism of four CYP3A4 probes (testosterone, midazolam, verapamil and atorvastatin) and three CYP2C9 probes (tolbutamide, diclofenac and S-warfarin) in human liver microsomes (HLM) and cDNA-expressed recombinant CYP450 (Rec-CYP450) systems were characterized and RAF_CL value was estimated as ratio of probe intrinsic clearance in HLM to that in Rec-CYP450. CYP450i contributions to metabolic reaction of a probe were predicted using other probes and compared with data from specific inhibitions. Contributions of CYP3A4 and CYP2C9 to metabolism of deoxypodophyllotoxin and nateglinide were also predicted. RAF values were dependent on probes, leading to probe-dependently predicted contributions. Predicted contributions of CYP3A4 to formations of 6β-hydroxytestosterone, 1'-hydroxymidazolam, norverapamil, ortho-hydroxyatorvastatin and para-hydroxyatorvastatin using other probes were 47.46-219.46%, 21.62-98.87%, 186.49-462.44%, 21.87-101.15% and 53.62-247.97%, respectively. Predicted contributions of CYP3A4 and CYP2C9 to nateglinide metabolism were 8.18-37.84% and 36.08-94.04%, separately. In conclusion, CYP450i contribution to drug metabolism in HLM estimated using RAF approach were probe-dependent. Therefore, contribution of each isoform must be confirmed by multiple probes.

Estimation of fractions metabolized by hepatic CYP enzymes using a concept of inter-system extrapolation factors (ISEFs) - a comparison with the chemical inhibition method

BACKGROUND

For estimation of fractions metabolized (fm) by different hepatic recombinant human CYP enzymes (rhCYP), calculation of inter-system extrapolation factors (ISEFs) has been proposed.

METHODS

ISEF values for CYP1A2, CYP2C19 and CYP3A4/5 were measured. A CYP2C9 ISEF was taken from a previous report. Using a set of compounds, fractions metabolized by CYP enzymes (fm,CYP) values calculated with the ISEFs based on rhCYP data were compared with those from the chemical inhibition data. Oral pharmacokinetics (PK) profiles of midazolam were simulated using the physiologically based pharmacokinetics (PBPK) model with the CYP3A ISEF. For other CYPs, the in vitro fm,CYP values were compared with the reference fm,CYP data back-calculated with, e.g. modeling of test substrates by feeding clinical PK data.

RESULTS

In vitro-in vitro fm,CYP3A4 relationship between the results from rhCYP incubation and chemical inhibition was drawn as an exponential correlation with R2=0.974. A midazolam PBPK model with the CYP3A4/5 ISEFs simulated the PK profiles within twofold error compared to the clinical observations. In a limited number of cases, the in vitro methods could not show good performance in predicting fm,CYP1A2, fm,CYP2C9 and fm,CYP2C19 values as reference data.

CONCLUSIONS

The rhCYP data with the measured ISEFs provided reasonable calculation of fm,CYP3A4 values, showing slight over-estimation compared to chemical inhibition.

Quantitative in vitro phenotyping and prediction of drug interaction potential of CYP2B6 substrates as victims

1. Determination of f_{m, CYP} for a compound is critical to assess the potential risk of a drug candidate as a victim of DDI. Several compounds are identified as CYP2B6 substrates, but the f_{m, CYP2B6} values are not determined quantitatively. 2. Two methods of reaction phenotyping, the chemical inhibition method and metabolism in rCYP enzymes, were used to determine the relative contributions of the enzymes. Chemical inhibition method was also conducted in the presence of BSA (0.5% w/v). 3. The results confirm with the earlier studies concerning the identity of the CYP2B6 enzyme. The f_{m, CYP2B6} values for artemisinin, bupropion, clopidogrel, ketamine, selegiline, sertraline and ticlopidine were 0.24, 0.28, 0.15, 0.45, 0.46, 0.42 and 0.54, respectively, in HLM determined by chemical inhibition method. The f_{m, CYP2B6} values for artemisinin, bupropion, clopidogrel, ketamine, selegiline, sertraline and ticlopidine were 0.46, 0.17, 0.15, 0.60, 0.51, 0.66 and 0.77, respectively, in HLM determined by chemical inhibition method in the presence of BSA (0.5% w/v). 4. Bupropion metabolism is majorly mediated by CYP2C19 (0.41) with a minor contribution from CYP2B6 (0.16) in the presence of BSA. Ticlopidine is a time-dependent inhibitor of both CYP2B6 and CYP2C19 that can inhibit the bupropion metabolism by 50-60%.

Incorporation of the Time-Varying Postprandial Increase in Splanchnic Blood Flow into a PBPK Model to Predict the Effect of Food on the Pharmacokinetics of Orally Administered High-Extraction Drugs

Following a meal, a transient increase in splanchnic blood flow occurs that can result in increased exposure to orally administered high-extraction drugs. Typically, physiologically based pharmacokinetic (PBPK) models have incorporated this increase in blood flow as a time-invariant fed/fasted ratio, but this approach is unable to explain the extent of increased drug exposure. A model for the time-varying increase in splanchnic blood flow following a moderate- to high-calorie meal (TV-Q _Splanch) was developed to describe the observed data for healthy individuals. This was integrated within a PBPK model and used to predict the contribution of increased splanchnic blood flow to the observed food effect for two orally administered high-extraction drugs, propranolol and ibrutinib. The model predicted geometric mean fed/fasted AUC and C _max ratios of 1.24 and 1.29 for propranolol, which were within the range of published values (within 1.0-1.8-fold of values from eight clinical studies). For ibrutinib, the predicted geometric mean fed/fasted AUC and C _max ratios were 2.0 and 1.84, respectively, which was within 1.1-fold of the reported fed/fasted AUC ratio but underestimated the reported C _max ratio by up to 1.9-fold. For both drugs, the interindividual variability in fed/fasted AUC and C _max ratios was underpredicted. This suggests that the postprandial change in splanchnic blood flow is a major mechanism of the food effect for propranolol and ibrutinib but is insufficient to fully explain the observations. The proposed model is anticipated to improve the prediction of food effect for high-extraction drugs, but should be considered with other mechanisms.

Characterization of human cytochrome P450 mediated bioactivation of amodiaquine and its major metabolite N-desethylamodiaquine

AIMS

Oxidative bioactivation of amodiaquine (AQ) by cytochrome P450s to a reactive quinoneimine is considered as an important mechanism underlying its idiosyncratic hepatotoxicity. However, because internal exposure to its major metabolite N-desethylamodiaquine (DEAQ) is up to 240-fold higher than AQ, bioactivation of DEAQ might significantly contribute to covalent binding. The aim of the present study was to compare the kinetics of bioactivation of AQ and DEAQ by human liver microsomes (HLM) and to characterize the CYPs involved in bioactivation of AQ and DEAQ.

METHODS

Glutathione was used to trap reactive metabolites formed in incubations of AQ and DEAQ with HLM and recombinant human cytochrome P450s (hCYPs). Kinetics of bioactivation of AQ and DEAQ in HLM and involvement of hCYPs were characterized by measuring corresponding glutathione conjugates (AQ-SG and DEAQ-SG) using a high-performance liquid chromatography method.

RESULTS

Bioactivation of AQ and DEAQ in HLM both exhibited Michaelis-Menten kinetics. For AQ bioactivation, enzyme kinetical parameters were K_m , 11.5 ± 2.0 μmol l^-1 , V_max , 59.2 ± 3.2 pmol min^-1  mg^-1 and CL_int , 5.15 μl min^-1  mg^-1 . For DEAQ, parameters for bioactivation were K_m , 6.1 ± 1.3 μmol l^-1 , V_max , 5.5 ± 0.4 pmol min^-1  mg^-1 and CL_int 0.90 μl min^-1  mg^-1 . Recombinant hCYPs and inhibition studies with HLM showed involvement of CYP3A4, CYP2C8, CYP2C9 and CYP2D6 in bioactivation.

CONCLUSIONS

The major metabolite DEAQ is likely to be quantitatively more important than AQ with respect to hepatic exposure to reactive metabolites in vivo. High expression of CYP3A4, CYP2C8, CYP2C9, and CYP2D6 may be risk factors for hepatotoxicity caused by AQ-therapy.

Towards a rational design of solid drug nanoparticles with optimised pharmacological properties

Solid drug nanoparticles (SDNs) are a nanotechnology with favourable characteristics to enhance drug delivery and improve the treatment of several diseases, showing benefit for improved oral bioavailability and injectable long‐acting medicines. The physicochemical properties and composition of nanoformulations can influence the absorption, distribution, and elimination of nanoparticles; consequently, the development of nanoparticles for drug delivery should consider the potential role of nanoparticle characteristics in the definition of pharmacokinetics. The aim of this study was to investigate the pharmacological behaviour of efavirenz SDNs and the identification of optimal nanoparticle properties and composition. Seventy‐seven efavirenz SDNs were included in the analysis. Cellular accumulation was evaluated in HepG2 (hepatic) and Caco‐2 (intestinal), CEM (lymphocyte), THP1 (monocyte), and A‐THP1 (macrophage) cell lines. Apparent intestinal permeability (P_app) was measured using a monolayer of Caco‐2 cells. The P_app values were used to evaluate the potential benefit on pharmacokinetics using a physiologically based pharmacokinetic model. The generated SDNs had an enhanced intestinal permeability and accumulation in different cell lines compared to the traditional formulation of efavirenz. Nanoparticle size and excipient choice influenced efavirenz apparent permeability and cellular accumulation, and this appeared to be cell line dependent. These findings represent a valuable platform for the design of SDNs, giving an empirical background for the selection of optimal nanoparticle characteristics and composition. Understanding how nanoparticle components and physicochemical properties influence pharmacological patterns will enable the rational design of SDNs with desirable pharmacokinetics.

Reaction phenotyping: advances in the experimental strategies used to characterize the contribution of drug-metabolizing enzymes

During the process of drug discovery, the pharmaceutical industry is faced with numerous challenges. One challenge is the successful prediction of the major routes of human clearance of new medications. For compounds cleared by metabolism, accurate predictions help provide an early risk assessment of their potential to exhibit significant interpatient differences in pharmacokinetics via routes of metabolism catalyzed by functionally polymorphic enzymes and/or clinically significant metabolic drug-drug interactions. This review details the most recent and emerging in vitro strategies used by drug metabolism and pharmacokinetic scientists to better determine rates and routes of metabolic clearance and how to translate these parameters to estimate the amount these routes contribute to overall clearance, commonly referred to as fraction metabolized. The enzymes covered in this review include cytochrome P450s together with other enzymatic pathways whose involvement in metabolic clearance has become increasingly important as efforts to mitigate cytochrome P450 clearance are successful. Advances in the prediction of the fraction metabolized include newly developed methods to differentiate CYP3A4 from the polymorphic enzyme CYP3A5, scaling tools for UDP-glucuronosyltranferase, and estimation of fraction metabolized for substrates of aldehyde oxidase.

Incorporating population variability and susceptible subpopulations into dosimetry for high-throughput toxicity testing

Momentum is growing worldwide to use in vitro high-throughput screening (HTS) to evaluate human health effects of chemicals. However, the integration of dosimetry into HTS assays and incorporation of population variability will be essential before its application in a risk assessment context. Previously, we employed in vitro hepatic metabolic clearance and plasma protein binding data with in vitro in vivo extrapolation (IVIVE) modeling to estimate oral equivalent doses, or daily oral chemical doses required to achieve steady-state blood concentrations (Css) equivalent to media concentrations having a defined effect in an in vitro HTS assay. In this study, hepatic clearance rates of selected ToxCast chemicals were measured in vitro for 13 cytochrome P450 and five uridine 5'-diphospho-glucuronysyltransferase isozymes using recombinantly expressed enzymes. The isozyme-specific clearance rates were then incorporated into an IVIVE model that captures known differences in isozyme expression across several life stages and ethnic populations. Comparison of the median Css for a healthy population against the median or the upper 95th percentile for more sensitive populations revealed differences of 1.3- to 4.3-fold or 3.1- to 13.1-fold, respectively. Such values may be used to derive chemical-specific human toxicokinetic adjustment factors. The IVIVE model was also used to estimate subpopulation-specific oral equivalent doses that were directly compared with subpopulation-specific exposure estimates. This study successfully combines isozyme and physiologic differences to quantitate subpopulation pharmacokinetic variability. Incorporation of these values with dosimetry and in vitro bioactivities provides a viable approach that could be employed within a high-throughput risk assessment framework.

Physiology-based IVIVE predictions of tramadol from in vitro metabolism data

PURPOSE

To predict the tramadol in vivo pharmacokinetics in adults by using in vitro metabolism data and an in vitro-in vivo extrapolation (IVIVE)-linked physiologically-based pharmacokinetic (PBPK) modeling and simulation approach (Simcyp®).

METHODS

Tramadol metabolism data was gathered using metabolite formation in human liver microsomes (HLM) and recombinant enzyme systems (rCYP). Hepatic intrinsic clearance (CLintH) was (i) estimated from HLM corrected for specific CYP450 contributions from a chemical inhibition assay (model 1); (ii) obtained in rCYP and corrected for specific CYP450 contributions by study-specific intersystem extrapolation factor (ISEF) values (model 2); and (iii) scaled back from in vivo observed clearance values (model 3). The model-predicted clearances of these three models were evaluated against observed clearance values in terms of relative difference of their geometric means, the fold difference of their coefficients of variation, and relative CYP2D6 contribution.

RESULTS

Model 1 underpredicted, while model 2 overpredicted the total tramadol clearance by -27 and +22%, respectively. The CYP2D6 contribution was underestimated in both models 1 and 2. Also, the variability on the clearance of those models was slightly underpredicted. Additionally, blood-to-plasma ratio and hepatic uptake factor were identified as most influential factors in the prediction of the hepatic clearance using a sensitivity analysis.

CONCLUSION

IVIVE-PBPK proved to be a useful tool in combining tramadol's low turnover in vitro metabolism data with system-specific physiological information to come up with reliable PK predictions in adults.

Antiretroviral solid drug nanoparticles with enhanced oral bioavailability: production, characterization, and in vitro-in vivo correlation

Nanomedicine strategies have produced many commercial products. However, no orally dosed HIV nanomedicines are available clinically to patients. Although nanosuspensions of drug particles have demonstrated many benefits, experimentally achieving >25 wt% of drug relative to stabilizers is highly challenging. In this study, the emulsion-templated freeze-drying technique for nanoparticles formation is applied for the first time to optimize a nanodispersion of the leading non-nucleoside reverse transcriptase inhibitor efavirenz, using clinically acceptable polymers and surfactants. Dry monoliths containing solid drug nanoparticles with extremely high drug loading (70 wt% relative to polymer and surfactant stabilizers) are stable for several months and reconstitute in aqueous media to provide nanodispersions with z-average diameters of 300 nm. The solid drug nanoparticles exhibit reduced cytoxicity and increased in vitro transport through model gut epithelium. In vivo studies confirm bioavailability benefits with an approximately four-fold higher pharmacokinetic exposure after oral administration to rodents, and predictive modeling suggests dose reduction with the new formulation may be possible.

Prediction of warfarin maintenance dose in Han Chinese patients using a mechanistic model based on genetic and non-genetic factors

BACKGROUND AND OBJECTIVES

Many attempts have been made to predict the warfarin maintenance dose in patients beginning warfarin therapy using a descriptive model based on multiple linear regression. Here we report the first attempt to develop a comprehensive mechanistic model integrating in vitro-in vivo extrapolation (IVIVE) with a pharmacokinetic-pharmacodynamic model to predict the warfarin maintenance dose in Han Chinese patients. The model incorporates demographic factors [sex, age, body weight (BW)] and the genetic polymorphisms of cytochrome P450 (CYP) 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1).

METHODS

Information on the various factors, mean warfarin daily dose and International Normalized Ratio (INR) was available for a cohort of 197 Han Chinese patients. Based on in vitro enzyme kinetic parameters for S-warfarin metabolism, demographic data for Han Chinese and some scaling factors, the S-warfarin clearance (CL) was predicted for patients in the cohort with different CYP2C9 genotypes using IVIVE. The plasma concentration of S-warfarin after a single oral dose was simulated using a one-compartment pharmacokinetic model with first-order absorption and a lag time and was combined with a mechanistic coagulation model to simulate the INR response. The warfarin maintenance dose was then predicted based on the demographic data and genotypes of CYP2C9 and VKORC1 for each patient and using the observed steady-state INR (INRss) as a target value. Finally, sensitivity analysis was carried out to determine which factor(s) affect the warfarin maintenance dose most strongly.

RESULTS

The predictive performance of this mechanistic model is not inferior to that of our previous descriptive model. There were significant differences in the mean warfarin daily dose in patients with different CYP2C9 and VKORC1 genotypes. Using IVIVE, the predicted mean CL of S-warfarin for patients with CYP2C9*1/*3 (0.092 l/h, n = 11) was 57 % less than for those with wild-type *1/*1 (0.215 l/h, n = 186). In addition, *1/*1 patients needed about 1 week to reach steady state, whereas *1/*3 patients needed about 2 weeks. In terms of the predicted INRss values, only ten patients had INRss values outside the expected therapeutic range (1.5-2.8). To evaluate our mechanistic model, we predicted the warfarin maintenance dose for 183 patients and explained 42 % of its variation, which is comparable to our previous prediction using a descriptive model based on multiple linear regression. The mean predicted/observed warfarin doses (mg/day) for different combinations of CYP2C9 and VKORC1 genotypes were 1.54/3.75 (n = 1) for *1/*1 and GG, 3.33/3.66 (n = 36) for *1/*1 and AG, 2.31/2.41 (n = 136) for *1/*1 and AA, and 1.56/1.69 (n = 10) for *1/*3 and AA, respectively. Sensitivity analysis indicated BW and genetic polymorphisms of CYP2C9 and VKORC1 were important factors affecting the warfarin maintenance dose in the study population.

CONCLUSION

The mechanistic model reported is the first to integrate IVIVE with a pharmacokinetic-pharmacodynamic model to describe the association of the warfarin maintenance dose with sex, age, BW and the genotypes of CYP2C9 and VKORC1. The model was effective in predicting S-warfarin clearance and in simulating its plasma concentration-time curve in a cohort of Han Chinese patients. In addition, the model accurately predicted the INR response and warfarin maintenance dose in a cohort of Han Chinese patients.

Application of physiologically based pharmacokinetic modeling to predict acetaminophen metabolism and pharmacokinetics in children

Acetaminophen (APAP) is a widely used analgesic and antipyretic drug that undergoes extensive phase I and II metabolism. To better understand the kinetics of this process and to characterize the dynamic changes in metabolism and pharmacokinetics (PK) between children and adults, we developed a physiologically based PK (PBPK) model for APAP integrating in silico, in vitro, and in vivo PK data into a single model. The model was developed and qualified for adults and subsequently expanded for application in children by accounting for maturational changes from birth. Once developed and qualified, it was able to predict clinical PK data in neonates (0–28 days), infants (29 days to <2 years), children (2 to <12 years), and adolescents (12–17 years) following intravenous and orally administered APAP. This approach represents a general strategy for projecting drug exposure in children, in the absence of pediatric PK information, using previous drug- and system-specific information of adults and children through PBPK modeling.

A role for cytochrome b5 in the In vivo disposition of anticancer and cytochrome P450 probe drugs in mice

The role of microsomal cytochrome b5 (Cyb5) in defining the rate of drug metabolism and disposition has been intensely debated for several decades. Recently we described mouse models involving the hepatic or global deletion of Cyb5, demonstrating its central role in in vivo drug disposition. We have now used the cytochrome b5 complete null (BCN) model to determine the role of Cyb5 in the metabolism of ten pharmaceuticals metabolized by a range of cytochrome P450s, including five anticancer drugs, in vivo and in vitro. The extent to which metabolism was significantly affected by the absence of Cyb5 was substrate-dependent; AUC increased (75-245%) and clearance decreased (35-72%) for phenacetin, metoprolol, and chlorzoxazone. Tolbutamide disposition was not significantly altered by Cyb5 deletion, while for midazolam clearance was decreased by 66%. The absence of Cyb5 had no effect on gefitinib and paclitaxel disposition, while significant changes in the in vivo pharmacokinetics were measured for: cyclophosphamide [maximum plasma concentration (Cmax) and terminal half-life increased 55% and 40%, respectively], tamoxifen (AUClast and Cmax increased 370% and 233%, respectively), and anastrozole (AUC and terminal half-life increased 125% and 62%, respectively; clearance down 80%). These data provide strong evidence that both hepatic and extrahepatic Cyb5 levels are an important determinant of in vivo drug disposition catalyzed by a range of cytochrome P450s, including currently prescribed anticancer agents, and that individuality in Cyb5 expression could be a significant determinant in rates of drug disposition in man.

Use of a physiologically-based pharmacokinetic model to simulate artemether dose adjustment for overcoming the drug-drug interaction with efavirenz

Purpose

To treat malaria, HIV-infected patients normally receive artemether (80 mg twice daily) concurrently with antiretroviral therapy and drug-drug interactions can potentially occur. Artemether is a substrate of CYP3A4 and CYP2B6, antiretrovirals such as efavirenz induce these enzymes and have the potential to reduce artemether pharmacokinetic exposure. The aim of this study was to develop an in vitro in vivo extrapolation (IVIVE) approach to model the interaction between efavirenz and artemether. Artemether dose adjustments were then simulated in order to predict optimal dosing in co-infected patients and inform future interaction study design.

Methods

In vitro data describing the chemical properties, absorption, distribution, metabolism and elimination of efavirenz and artemether were obtained from published literature and included in a physiologically based pharmacokinetic model (PBPK) to predict drug disposition simulating virtual clinical trials. Administration of efavirenz and artemether, alone or in combination, were simulated to mirror previous clinical studies and facilitate validation of the model and realistic interpretation of the simulation. Efavirenz (600 mg once daily) was administered to 50 virtual subjects for 14 days. This was followed by concomitant administration of artemether (80 mg eight hourly) for the first two doses and 80 mg (twice daily) for another two days.

Results

Simulated pharmacokinetics and the drug-drug interaction were in concordance with available clinical data. Efavirenz induced first pass metabolism and hepatic clearance, reducing artemether C_max by 60% and AUC by 80%. Dose increases of artemether, to correct for the interaction, were simulated and a dose of 240 mg was predicted to be sufficient to overcome the interaction and allow therapeutic plasma concentrations of artemether.

Conclusions

The model presented here provides a rational platform to inform the design for a clinical drug interaction study that may save time and resource while the optimal dose is determined empirically. Wider application of IVIVE could help researchers gain a better understanding of the molecular mechanisms underpinning variability in drug disposition.