Kuresh Youdim

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.

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, O6-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.

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.

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 μM substrate and 0.5 μM 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 μM 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.

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.

The time to move cytochrome P450 induction into mainstream pharmacology is long overdue

The understanding of the processes of induction of human drug-metabolizing enzymes has advanced considerably over the past decade. If we concentrate on CYP3A4, the most abundant form of cytochrome P450 and the one most involved in the clearance of the majority of pharmaceuticals, a clear

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.

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.

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

Abstract 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.

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.