Model-Based Assessments of CYP-Mediated Drug-Drug Interaction Risk of Alectinib: Physiologically Based Pharmacokinetic Modeling Supported Clinical Development.

Alectinib is a selective anaplastic lymphoma kinase (ALK) inhibitor approved for the treatment of ALK-positive non-small cell lung cancer. Alectinib and its major active metabolite M4 exhibited drug-drug interaction (DDI) potential through cytochrome P450 (CYP) enzymes CYP3A4 and CYP2C8 in vitro. Clinical relevance of the DDI risk was investigated as part of a rapid development program to fulfill the breakthrough therapy designation. Therefore, a strategy with a combination of physiologically based pharmacokinetic (PBPK) modeling and limited clinical trials focused on generating informative data for modeling was made to ensure extrapolation ability of DDI risk. The PBPK modeling has provided mechanistic insight into the low victim DDI risk of alectinib through CYP3A4 by a novel two-dimensional analysis for fmCYP3A4 and FG , and demonstrated negligible CYPs 2C8 and 3A4 enzyme-modulating effects at clinically relevant exposure. This work supports that alectinib can be prescribed without dose adjustment for CYP-mediated DDI liabilities.

In vitro metabolism of alectinib, a novel potent ALK inhibitor, in human: contribution of CYP3A enzymes.

1. The in vitro metabolism of alectinib, a potent and highly selective oral anaplastic lymphoma kinase inhibitor, was investigated. 2. The main metabolite (M4) in primary human hepatocytes was identified, which is produced by deethylation at the morpholine ring. Three minor metabolites (M6, M1a, and M1b) were also identified, and a minor peak of hydroxylated alectinib (M5) was detected as a possible precursor of M4, M1a, and M1b. 3. M4, an important active major metabolite, was produced and further metabolized to M6 by CYP3A, indicating that CYP3A enzymes were the principal contributors to this route. M5 is possibly produced by CYP3A and other isoforms as the primary step in metabolism, followed by oxidation to M4 mainly by CYP3A. Alternatively, M5 could be oxidized to M1a and M1b via an NAD-dependent process. None of the non-CYP3A-mediated metabolism appeared to be major. 4. In conclusion, this study suggests that involvement of multiple enzymes in the metabolism of alectinib reduces its potential for drug-drug interactions.

Optimum designs for non-linear mixed effects models in the presence of covariates.

In this article, we present a new method for optimizing designs of experiments for non-linear mixed effects models, where a categorical factor with covariate information is a design variable combined with another design factor. The work is motivated by the need to efficiently design preclinical experiments in enzyme kinetics for a set of Human Liver Microsomes. However, the results are general and can be applied to other experimental situations where the variation in the response due to a categorical factor can be partially accounted for by a covariate. The covariate included in the model explains some systematic variability in a random model parameter. This approach allows better understanding of the population variation as well as estimation of the model parameters with higher precision.

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.

Simultaneous determination of multiple CYP inhibition constants using a cocktail-probe approach.

To identify cytochrome P450 (CYP) drug-drug interaction (DDI) potential of a new chemical entity, the use of a specific clinically relevant probe substrate in the presence of a test compound is common place. In early discovery of new chemical entities, a balance of rigor, the ability to predict clinical DDI, and throughput is desired in an in vitro assay. This chapter describes a high-throughput CYP-mediated DDI assay method that balances these characteristics. The method utilizes a cassette approach using a cocktail of five selective probe substrates for the major clinically relevant CYPs involved in drug interactions. CYP1A2, 2C9, 2C19, 2D6, and 3A activities are assessed with liquid chromatography/tandem mass spectrometry (LC-MS/MS) quantification of metabolite formation. The method also outlines specific inhibitors to evaluate dynamic range and as a positive control. The benefits and needs for caution of this method are noted and discussed.

Application of PBPK modelling in drug discovery and development at Pfizer.

Early prediction of human pharmacokinetics (PK) and drug-drug interactions (DDI) in drug discovery and development allows for more informed decision making. Physiologically based pharmacokinetic (PBPK) modelling can be used to answer a number of questions throughout the process of drug discovery and development and is thus becoming a very popular tool. PBPK models provide the opportunity to integrate key input parameters from different sources to not only estimate PK parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. Using examples from the literature and our own company, we have shown how PBPK techniques can be utilized through the stages of drug discovery and development to increase efficiency, reduce the need for animal studies, replace clinical trials and to increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however, some limitations need to be addressed to realize its application and utility more broadly.

Optimum design of experiments for enzyme inhibition kinetic models.

We find closed-form expressions for the D-optimum designs for three- and four-parameter nonlinear models arising in kinetic models for enzyme inhibition. We calculate the efficiency of designs over a range of parameter values and make recommendations for design when the parameter values are not well known. In a three-parameter experimental example, a standard design has an efficiency of 18.2% of the D-optimum design. Experimental results from a standard design with 120 trials and a D-optimum design with 21 trials give parameter estimates that are in close agreement. The estimated standard errors of these parameter estimates confirm our theoretical results on efficiency and thus on the serious savings that can be made by the use of D-optimum designs.

In vitro-in vivo correlation for intrinsic clearance for drugs metabolized by human aldehyde oxidase.

The ability to predict in vivo clearance from in vitro intrinsic clearance for compounds metabolized by aldehyde oxidase has not been demonstrated. To date, there is no established scaling method for predicting aldehyde oxidase-mediated clearance using in vitro or animal data. This challenge is exacerbated by the fact that rats and dogs, two of the laboratory animal species commonly used to develop in vitro-in vivo correlations of clearance, differ from humans with regard to expression of aldehyde oxidase. The objective of this investigation was to develop an in vitro-in vivo correlation of intrinsic clearance for aldehyde oxidase, using 11 drugs known to be metabolized by this enzyme. The set consisted of methotrexate, XK-469, (+/-)-4-(4-cyanoanilino)-5,6-dihydro-7-hydroxy-7H-cyclopenta[d]pyrimidine (RS-8359), zaleplon, 6-deoxypenciclovir, zoniporide, O(6)-benzylguanine, N-[(2'-dimethylamino)ethyl]acridine-4-carboxamide (DACA), carbazeran, PF-4217903, and PF-945863. These compounds were assayed using two in vitro systems (pooled human liver cytosol and liver S-9 fractions) to calculate scaled unbound intrinsic clearance, and they were then compared with calculated in vivo unbound intrinsic clearance. The investigation provided a relative scale that can be used for in vitro-in vivo correlation of aldehyde oxidase clearance and suggests limits as to when a potential new drug candidate that is metabolized by this enzyme will possess acceptable human clearance, or when structural modification is required to reduce aldehyde oxidase catalyzed metabolism.

Potential application of D-optimal designs in the efficient investigation of cytochrome P450 inhibition kinetic models.

Correctly chosen d-optimal designs provide efficient experimental schemes when the aim of the investigation is to obtain precise estimates of parameters. In the current work, estimates of parameters refer to the enzyme kinetic parameters V(max) and K(m), but they also refer to the inhibition constant K(i). In general, this experimental approach is performed on a grid of values of the design variables. However, this approach may not be very efficient, in the sense that the parameter estimates (V(max), K(m), and K(i)) have unnecessarily high variances. For good estimates of parameters, the most efficient designs consist of clusters of replicates of a few sets of experimental conditions. The current study compares the application of such d-optimal designs with that of a conventional approach in assessing the competitive inhibitory potency of fluconazole and sertraline toward CYP2C9 and 2D6, respectively. In each instance, the parameter estimates, namely V(max), K(m), and K(i), were predicted well using the d-optimal design compared with those measured using the rich data sets, for both inhibitors. We show that d optimality can provide more efficient designs for estimating the model parameters, including K(i). We also show that real cost savings can be made by carefully planning studies that use the theory of optimal experimental design.

A review of LC-MS techniques and high-throughput approaches used to investigate drug metabolism by cytochrome P450s.

One of the major challenges facing the pharmaceutical industry today is finding new ways to increase productivity, decrease costs whilst still ultimately developing new therapies that enhance human health. To help address these challenges the utilisation of analytical technologies and high-throughput automated platforms has been employed; in order to perform more experiments in a shorter time frame with increased data quality. One of the main in vitro techniques to assess new chemical entities in a discovery setting has been the use of recombinant liver enzymes, microsomes and hepatocytes. These techniques can help predict in vivo metabolism, clearance and potential drug-drug interactions of these new compounds by cytochrome P450s (the major drug metabolising enzymes). This in vitro methodology has been totally transformed in recent times by the use of automated liquid handling and HPLC tandem mass spectrometry detection techniques (LC-MS/MS). This review aims looking at recent advances in the methodology used to investigate drug metabolism by cytochrome P450s; including an up to date summary of high-throughput platforms including the use of automation and LC-MS/MS to facilitate greater throughput, chromatographic resolution and data quality.

Comparison of different algorithms for predicting clinical drug-drug interactions, based on the use of CYP3A4 in vitro data: predictions of compounds as precipitants of interaction.

Cytochrome P450 3A4 (CYP3A4) is the most important enzyme in drug metabolism and because it is the most frequent target for pharmacokinetic drug-drug interactions (DDIs) it is highly desirable to be able to predict CYP3A4-based DDIs from in vitro data. In this study, the prediction of clinical DDIs for 30 drugs on the pharmacokinetics of midazolam, a probe substrate for CYP3A4, was done using in vitro inhibition, inactivation, and induction data. Two DDI prediction approaches were used, which account for effects at both the liver and intestine. The first was a model that simultaneously combines reversible inhibition, time-dependent inactivation, and induction data with static estimates of relevant in vivo concentrations of the precipitant drug to provide point estimates of the average magnitude of change in midazolam exposure. This model yielded a success rate of 88% in discerning DDIs with a mean -fold error of 1.74. The second model was a computational physiologically based pharmacokinetic model that uses dynamic estimates of in vivo concentrations of the precipitant drug and accounts for interindividual variability among the population (Simcyp). This model yielded success rates of 88 and 90% (for "steady-state" and "time-based" approaches, respectively) and mean -fold errors of 1.59 and 1.47. From these findings it can be concluded that in vivo DDIs for CYP3A4 can be predicted from in vitro data, even when more than one biochemical phenomenon occurs simultaneously.

An automated, high-throughput, 384 well Cytochrome P450 cocktail IC50 assay using a rapid resolution LC-MS/MS end-point.

The current study focused on the development of an automated IC50 cocktail assay in a miniaturized 384 well assay format. This was developed in combination with a significantly shorter high pressure liquid chromatography (HPLC) separation and liquid chromatography-mass spectrometry (LC-MS/MS) run-time; than those currently reported in the literature. The 384-well assay used human liver microsomes in conjunction with a cocktail of probe substrates metabolized by the five major CYPs (tacrine for CYP1A2, diclofenac for CYP2C9, (S)-mephenytoin for CYP2C19, dextromethorphan for CYP2D6 and midazolam for CYP3A4). To validate the usefulness of the automated and analytical methodologies, IC50 determinations were performed for a series of test compounds known to exhibit inhibition across these five major P450s. Eight compounds (sertraline, disulfuram, ticlopidine fluconazole, fluvoxamine, ketoconazole, miconazole, paroxetine, flunitrazepam) were studied as part of a cocktail assay, and against each CYPs individually. The data showed that the IC50s generated with cocktail incubations did not differ to a great extent from those obtained in the single probe experiments and hence unlikely to significantly influence the predicted clinical DDI risk. In addition the present method offered a significant advantage over some of the existing cocktail analytical methodology in that separation can be achieved with run times as short as 1 min without compromising data integrity. Although numerous studies have been reported to measure CYP inhibition in a cocktail format the need to support growing discovery libraries not only relies on higher throughput assays but quicker analytical run times. The current study reports a miniaturized high-throughput cocktail IC50 assay, in conjunction with a robust, rapid resolution LC-MS/MS end-point offered increased sample throughput without compromising analytical sensitivity or analyte resolution.

Application of CYP3A4 in vitro data to predict clinical drug-drug interactions; predictions of compounds as objects of interaction.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: Numerous retrospective analyses have shown the utility of in vitro systems for predicting potential drug-drug interactions (DDIs). Prediction of DDIs from in vitro data is commonly obtained using estimates of enzyme K(i), inhibitor and substrate concentrations and absorption rate for substrate and inhibitor. WHAT THIS STUDY ADDS: Using a generic approach for all test compounds, the findings from the current study showed the use of recombinant P450s provide a more robust in vitro measure of P450 contribution (fraction metabolized, f(m)) than that achieved when using chemical inhibitors in combination with human liver microsomes, for the prediction of potential CYP3A4 drug-drug interactions prior to clinical investigation. The current study supported the use of SIMCYP(R), a modelling and simulation software in utilizing the in vitro measures in the prediction of potential drug-drug interactions. AIMS: The aim of this study was to explore and optimize the in vitro and in silico approaches used for predicting clinical DDIs. A data set containing clinical information on the interaction of 20 Pfizer compounds with ketoconazole was used to assess the success of the techniques. METHODS: The study calculated the fraction and the rate of metabolism of 20 Pfizer compounds via each cytochrome P450. Two approaches were used to determine fraction metabolized (f(m)); 1) by measuring substrate loss in human liver microsomes (HLM) in the presence and absence of specific chemical inhibitors and 2) by measuring substrate loss in individual cDNA expressed P450s (also referred to as recombinant P450s (rhCYP)) The fractions metabolized via each CYP were used to predict the drug-drug interaction due to CYP3A4 inhibition by ketoconazole using the modelling and simulation software SIMCYP. RESULTS: When in vitro data were generated using Gentest supersomes, 85% of predictions were within two-fold of the observed clinical interaction. Using PanVera baculosomes, 70% of predictions were predicted within two-fold. In contrast using chemical inhibitors the accuracy was lower, predicting only 37% of compounds within two-fold of the clinical value. Poorly predicted compounds were found to either be metabolically stable and/or have high microsomal protein binding. The use of equilibrium dialysis to generate accurate protein binding measurements was especially important for highly bound drugs. CONCLUSIONS: The current study demonstrated that the use of rhCYPs with SIMCYP provides a robust in vitro system for predicting the likelihood and magnitude of changes in clinical exposure of compounds as a consequence of CYP3A4 inhibition by a concomitantly administered drug.

Induction of cytochrome P450: assessment in an immortalized human hepatocyte cell line (Fa2N4) using a novel higher throughput cocktail assay.

Over recent years the application of cocktail studies to measure biological markers has become increasingly popular. The current study investigated a novel approach in assessing cytochrome P450 (P450) enzyme induction in an immortalized cell line using a cocktail of five P450 substrate probes compared with the traditional single-probe approach. The findings reported herein support use of a cocktail approach to assess the induction of the major P450s, namely, CYP3A4, CYP1A2, and CYP2C9. CYP2C19 and CYP2D6 could also be followed as part of the cocktail approach reported. Response to prototypical inducers did not differ to those observed in the presence of the specific probes alone. Consequently, this approach requires significantly fewer sample numbers if screening the induction potential of more than one P450. Moreover, these studies highlight the utility of the immortalized cell line Fa2N4 as a robust model system for induction studies. In conclusion, the current experimental setup is an improvement on current approaches used to assess P450 induction, significantly increasing sample throughput.

Minimizing polymorphic metabolism in drug discovery: evaluation of the utility of in vitro methods for predicting pharmacokinetic consequences associated with CYP2D6 metabolism.

Minimizing interindividual variability in drug exposure is an important goal for drug discovery. The reliability of the selective CYP2D6 inhibitor quinidine was evaluated in a retrospective analysis using a standardized approach that avoids laboratory-to-laboratory variation. The goal was to evaluate the reliability of in vitro metabolism studies for predicting extensive metabolizer (EM)/poor metabolizer (PM) exposure differences. Using available literature, 18 CYP2D6 substrates were selected for further analysis. In vitro microsomal studies were conducted at 1 microM substrate and 0.5 microM P450 to monitor substrate depletion. An estimate of the fraction metabolized by CYP2D6 in microsomes was derived from the rate constant determined with and without 1 microM quinidine for 11 substrates. Clearance in EM and PM subjects and fractional recovery of metabolites were taken from the literature. A nonlinear relationship between the contribution of CYP2D6 and decreased oral clearance for PMs relative to EMs was evident. For drugs having <60% CYP2D6 involvement in vivo, a modest difference between EM and PM exposure was observed (<2.5-fold). For major CYP2D6 substrates (>60%), more dramatic exposure differences were observed (3.5- to 53-fold). For compounds primarily eliminated by hepatic P450 and with sufficient turnover to be evaluated in vitro, the fraction metabolized by CYP2D6 in vitro compared favorably with the in vivo data. The in vitro estimation of fraction metabolized using quinidine as a specific inhibitor provided an excellent predictive tool. Results from microsomal substrate depletion experiments can be used with confidence to select compounds in drug discovery using a cutoff of >60% metabolism by CYP2D6.

The reaction of flavanols with nitrous acid protects against N-nitrosamine formation and leads to the formation of nitroso derivatives which inhibit cancer cell growth.

Studies have suggested that diets rich in polyphenols such as flavonoids may lead to a reduced risk of gastrointestinal cancers. We demonstrate the ability of monomeric and dimeric flavanols to scavenge reactive nitrogen species derived from nitrous acid. Both epicatechin and dimer B2 (epicatechin dimer) inhibited nitrous acid-induced formation of 3-nitrotyrosine and the formation of the carcinogenic N-nitrosamine, N-nitrosodimethylamine. The reaction of monomeric and dimeric epicatechin with nitrous acid led to the formation of mono- and di-nitroso flavanols, whereas the reaction with hesperetin resulted primarily in the formation of nitrated products. Although, epicatechin was transferred across the jejunum of the small intestine yielding metabolites, its nitroso form was not absorbed. Dimer B2 but not epicatechin monomer inhibited the proliferation of, and triggered apoptosis in, Caco-2 cells. The latter was accompanied by caspase-3 activation and reductions in Akt phosphorylation, suggesting activation of apoptosis via inhibition of prosurvival signaling. Furthermore, the dinitroso derivative of dimer B2, and to a lesser extent the dinitroso-epicatechin, also induced significant toxic effects in Caco-2 cells. The inhibitory effects on cellular proliferation were paralleled by early inhibition of ERK 1/2 phosphorylation and later reductions in cyclin D1 levels, indicating modulation of cell cycle regulation in Caco-2 cells. These effects highlight multiple routes in which dietary derived flavanols may exert beneficial effects in the gastrointestinal tract.

Flavonoids and the brain: interactions at the blood-brain barrier and their physiological effects on the central nervous system.

Over the past few years there has been an exponential growth in the number of reports describing the effects of nutritional modulation on aging and age-related diseases. Specific attention has been directed toward the beneficial effects afforded by dietary antioxidants, in particular those from fruit and vegetables, in ameliorating age-related deficits in brain performance. The rationale for studying the effects of dietary intervention stems from evidence implicating free radicals in aspects related to the aging process. Age-dependent neuropathology is a cumulative response to alterations induced by reactive oxygen species. Therefore cognitive aging, according to this hypothesis, should be slowed, and possibly even reversed, by appropriately increasing levels of antioxidants or decreasing overproduction of free radicals in the body.

The flavone hispidulin, a benzodiazepine receptor ligand with positive allosteric properties, traverses the blood-brain barrier and exhibits anticonvulsive effects.

The functional characterization of hispidulin (4',5,7-trihydroxy-6-methoxyflavone), a potent benzodiazepine (BZD) receptor ligand, was initiated to determine its potential as a modulator of central nervous system activity. After chemical synthesis, hispidulin was investigated at recombinant GABA(A)/BZD receptors expressed by Xenopus laevis oocytes. Concentrations of 50 nm and higher stimulated the GABA-induced chloride currents at tested receptor subtypes (alpha(1-3,5,6)beta(2)gamma(2)S) indicating positive allosteric properties. Maximal stimulation at alpha(1)beta(2)gamma(2)S was observed with 10 microm hispidulin. In contrast to diazepam, hispidulin modulated the alpha(6)beta(2)gamma(2)S-GABA(A) receptor subtype. When fed to seizure-prone Mongolian gerbils (Meriones unguiculatus) in a model of epilepsy, hispidulin (10 mg kg(-1) body weight (BW) per day) and diazepam (2 mg kg(-1) BW per day) markedly reduced the number of animals suffering from seizures after 7 days of treatment (30 and 25% of animals in the respective treatment groups, vs 80% in the vehicle group). Permeability across the blood-brain barrier for the chemically synthesized, (14)C-labelled hispidulin was confirmed by a rat in situ perfusion model. With an uptake rate (K(in)) of 1.14 ml min(-1) g(-1), measurements approached the values obtained with highly penetrating compounds such as diazepam. Experiments with Caco-2 cells predict that orally administered hispidulin enters circulation in its intact form. At a concentration of 30 microm, the flavone crossed the monolayer without degradation as verified by the absence of glucuronidated metabolites.