A quantitative approach to hepatic clearance prediction of metabolism by aldehyde oxidase using custom pooled hepatocytes

Challenges and Opportunities for In Vitro-In Vivo Extrapolation of Aldehyde Oxidase-Mediated Clearance: Toward a Roadmap for Quantitative Translation

Underestimation of aldehyde oxidase (AO)-mediated clearance by current in vitro assays leads to uncertainty in human dose projections, thereby reducing the likelihood of success in drug development. In the present study we first evaluated the current drug development practices for AO substrates. Next, the overall predictive performance of in vitro-in vivo extrapolation of unbound hepatic intrinsic clearance (CLint,u) and unbound hepatic intrinsic clearance by AO (CLint,u,AO) was assessed using a comprehensive literature database of in vitro (human cytosol/S9/hepatocytes) and in vivo (intravenous/oral) data collated for 22 AO substrates (total of 100 datapoints from multiple studies). Correction for unbound fraction in the incubation was done by experimental data or in silico predictions. The fraction metabolized by AO (fmAO) determined via in vitro/in vivo approaches was found to be highly variable. The geometric mean fold errors (gmfe) for scaled CLint,u (mL/min/kg) were 10.4 for human hepatocytes, 5.6 for human liver cytosols, and 5.0 for human liver S9, respectively. Application of these gmfe's as empirical scaling factors improved predictions (45%-57% within twofold of observed) compared with no correction (11%-27% within twofold), with the scaling factors qualified by leave-one-out cross-validation. A road map for quantitative translation was then proposed following a critical evaluation on the in vitro and clinical methodology to estimate in vivo fmAO In conclusion, the study provides the most robust system-specific empirical scaling factors to date as a pragmatic approach for the prediction of in vivo CLint,u,AO in the early stages of drug development. SIGNIFICANCE STATEMENT: Confidence remains low when predicting in vivo clearance of AO substrates using in vitro systems, leading to de-prioritization of AO substrates from the drug development pipeline to mitigate risk of unexpected and costly in vivo impact. The current study establishes a set of empirical scaling factors as a pragmatic tool to improve predictability of in vivo AO clearance. Developing clinical pharmacology strategies for AO substrates by utilizing mass balance/clinical drug-drug interaction data will help build confidence in fmAO.

Dissecting Parameters Contributing to the Underprediction of Aldehyde Oxidase-Mediated Metabolic Clearance of Drugs

We investigated the effect of variability and instability in aldehyde oxidase (AO) content and activity on the scaling of in vitro metabolism data. AO content and activity in human liver cytosol (HLC) and five recombinant human AO preparations (rAO) were determined using targeted proteomics and carbazeran oxidation assay, respectively. AO content was highly variable as indicated by the relative expression factor (REF; i.e., HLC to rAO content) ranging from 0.001 to 1.7 across different in vitro systems. The activity of AO in HLC degrades at a 10-fold higher rate in the presence of the substrate as compared with the activity performed after preincubation without substrate. To scale the metabolic activity from rAO to HLC, a protein-normalized activity factor (pnAF) was proposed wherein the activity was corrected by AO content, which revealed up to sixfold higher AO activity in HLC versus rAO systems. A similar value of pnAF was observed for another substrate, ripasudil. Physiologically based pharmacokinetic (PBPK) modeling revealed a significant additional clearance (CL; 66%), which allowed for the successful prediction of in vivo CL of four other substrates, i.e., O-benzyl guanine, BIBX1382, zaleplon, and zoniporide. For carbazeran, the metabolite identification study showed that the direct glucuronidation may be contributing to around 12% elimination. Taken together, this study identified differential protein content, instability of in vitro activity, role of additional AO clearance, and unaccounted metabolic pathways as plausible reasons for the underprediction of AO-mediated drug metabolism. Consideration of these factors and integration of REF and pnAF in PBPK models will allow better prediction of AO metabolism. SIGNIFICANCE STATEMENT: This study elucidated the plausible reasons for the underprediction of aldehyde oxidase (AO)-mediated drug metabolism and provided recommendations to address them. It demonstrated that integrating protein content and activity differences and accounting for the loss of AO activity, as well as consideration of extrahepatic clearance and additional pathways, would improve the in vitro to in vivo extrapolation of AO-mediated drug metabolism using physiologically based pharmacokinetic modeling.

Aldehyde oxidase mediated drug metabolism: an underpredicted obstacle in drug discovery and development

Aldehyde oxidase (AO) has garnered curiosity as a non-CYP metabolizing enzyme in drug development due to unexpected consequences such as toxic metabolite generation and high metabolic clearance resulting in the clinical failure of new drugs. Therefore, poor AO mediated clearance prediction in preclinical nonhuman species remains a significant obstacle in developing novel drugs. Various isoforms of AO, such as AOX1, AOX3, AOX3L1, and AOX4 exist across species, and different AO activity among humans influences the AO mediated drug metabolism. Therefore, carefully considering the unique challenges is essential in developing successful AO substrate drugs. The in vitro to in vivo extrapolation underpredicts AO mediated drug clearance due to the lack of reliable representative animal models, substrate-specific activity, and the discrepancy between absolute concentration and activity. An in vitro tool to extrapolate in vivo clearance using a yard-stick approach is provided to address the underprediction of AO mediated drug clearance. This approach uses a range of well-known AO drug substrates as calibrators for qualitative scaling new drugs into low, medium, or high clearance category drugs. So far, in vivo investigations on chimeric mice with humanized livers (humanized mice) have predicted AO mediated metabolism to the best extent. This review addresses the critical aspects of the drug discovery stage for AO metabolism studies, challenges faced in drug development, approaches to tackle AO mediated drug clearance's underprediction, and strategies to decrease the AO metabolism of drugs.

Recent advances in the translation of drug metabolism and pharmacokinetics science for drug discovery and development

Drug metabolism and pharmacokinetics (DMPK) is an important branch of pharmaceutical sciences. The nature of ADME (absorption, distribution, metabolism, excretion) and PK (pharmacokinetics) inquiries during drug discovery and development has evolved in recent years from being largely descriptive to seeking a more quantitative and mechanistic understanding of the fate of drug candidates in biological systems. Tremendous progress has been made in the past decade, not only in the characterization of physiochemical properties of drugs that influence their ADME, target organ exposure, and toxicity, but also in the identification of design principles that can minimize drug-drug interaction (DDI) potentials and reduce the attritions. The importance of membrane transporters in drug disposition, efficacy, and safety, as well as the interplay with metabolic processes, has been increasingly recognized. Dramatic increases in investments on new modalities beyond traditional small and large molecule drugs, such as peptides, oligonucleotides, and antibody-drug conjugates, necessitated further innovations in bioanalytical and experimental tools for the characterization of their ADME properties. In this review, we highlight some of the most notable advances in the last decade, and provide future perspectives on potential major breakthroughs and innovations in the translation of DMPK science in various stages of drug discovery and development.

Contribution of Extrahepatic Aldehyde Oxidase Activity to Human Clearance

Aldehyde oxidase (AOX) is a soluble, cytosolic enzyme that metabolizes various N-heterocyclic compounds and organic aldehydes. It has wide tissue distribution with highest levels found in liver, kidney, and lung. Human clearance projections of AOX substrates by in vitro assessments in isolated liver fractions (cytosol, S9) and even hepatocytes have been largely underpredictive of clinical outcomes. Various hypotheses have been suggested as to why this is the case. One explanation is that extrahepatic AOX expression contributes measurably to AOX clearance and is at least partially responsible for the often observed underpredictions. Although AOX expression has been confirmed in several extrahepatic tissues, activities therein and potential contribution to overall human clearance have not been thoroughly studied. In this work, the AOX enzyme activity using the S9 fractions of select extrahepatic human tissues (kidney, lung, vasculature, and intestine) were measured using carbazeran as a probe substrate. Measured activities were scaled to a whole-body clearance using best-available parameters and compared with liver S9 fractions. Here, the combined scaled AOX clearance obtained from the kidney, lung, vasculature, and intestine is very low and amounted to <1% of liver. This work suggests that AOX metabolism from extrahepatic sources plays little role in the underprediction of activity in human. One of the notable outcomes of this work has been the first direct demonstration of AOX activity in human vasculature. SIGNIFICANCE STATEMENT: This work demonstrates aldehyde oxidase (AOX) activity is measurable in a variety of extrahepatic human tissues, including vasculature, yet activities and potential contributions to human clearance are relatively low and insignificant when compared with the liver. Additionally, the modeling of the tissue-specific in vitro kinetic data suggests that AOX may be influenced by the tissue it resides in and thus show different affinity, activity, and modified activity over time.

Metabolism by Aldehyde Oxidase: Drug Design and Complementary Approaches to Challenges in Drug Discovery

Aldehyde oxidase (AO) catalyzes oxidations of azaheterocycles and aldehydes, amide hydrolysis, and diverse reductions. AO substrates are rare among marketed drugs, and many candidates failed due to poor pharmacokinetics, interspecies differences, and adverse effects. As most issues arise from complex and poorly understood AO biology, an effective solution is to stop or decrease AO metabolism. This perspective focuses on rational drug design approaches to modulate AO-mediated metabolism in drug discovery. AO biological aspects are also covered, as they are complementary to chemical design and important when selecting the experimental system for risk assessment. The authors' recommendation is an early consideration of AO-mediated metabolism supported by computational and in vitro experimental methods but not an automatic avoidance of AO structural flags, many of which are versatile and valuable building blocks. Preferably, consideration of AO-mediated metabolism should be part of the multiparametric drug optimization process, with the goal to improve overall drug-like properties.

Aldehyde oxidase and its role as a drug metabolizing enzyme

Aldehyde oxidase (AO) is a cytosolic enzyme that belongs to the family of structurally related molybdoflavoproteins like xanthine oxidase (XO). The enzyme is characterized by broad substrate specificity and marked species differences. It catalyzes the oxidation of aromatic and aliphatic aldehydes and various heteroaromatic rings as well as reduction of several functional groups. The references to AO and its role in metabolism date back to the 1950s, but the importance of this enzyme in the metabolism of drugs has emerged in the past fifteen years. Several reviews on the role of AO in drug metabolism have been published in the past decade indicative of the growing interest in the enzyme and its influence in drug metabolism. Here, we present a comprehensive monograph of AO as a drug metabolizing enzyme with emphasis on marketed drugs as well as other xenobiotics, as substrates and inhibitors. Although the number of drugs that are primarily metabolized by AO are few, the impact of AO on drug development has been extensive. We also discuss the effect of AO on the systemic exposure and clearance these clinical candidates. The review provides a comprehensive analysis of drug discovery compounds involving AO with the focus on developmental candidates that were reported in the past five years with regards to pharmacokinetics and toxicity. While there is only one known report of AO-mediated clinically relevant drug-drug interaction (DDI), a detailed description of inhibitors and inducers of AO known to date has been presented here and the potential risks associated with DDI. The increasing recognition of the importance of AO has led to significant progress in predicting the site of AO-mediated metabolism using computational methods. Additionally, marked species difference in expression of AO makes it is difficult to predict human clearance with high confidence. The progress made towards developing in vivo, in vitro and in silico approaches for predicting AO metabolism and estimating human clearance of compounds that are metabolized by AO have also been discussed.

Species differences in metabolism of a new antiepileptic drug candidate, DSP-0565 [2-(2'-fluoro[1,1'-biphenyl]-2-yl)acetamide]

The metabolism and pharmacokinetics of DSP-0565 [2-(2'-fluoro[1,1'-biphenyl]-2-yl)acetamide], an antiepileptic drug candidate, was investigated in rats, dogs, and humans. In human hepatocytes, [¹⁴ C]DSP-0565 was primarily metabolized via amide bond hydrolysis to (2'-fluoro[1,1'-biphenyl]-2-yl)acetic acid (M8), while in rat and dog hepatocytes, it was primarily metabolized via both hydrolysis to M8 and hydroxylation at the benzene ring or the benzyl site to oxidized metabolites. After single oral administration of [¹⁴ C]DSP-0565 to rats and dogs, the major radioactivity fraction was recovered in the urine (71-72% of dose) with a much smaller fraction recovered in feces (23-25% of dose). As primary metabolites in their excreta, M8, oxidized metabolites, and glucuronide of DSP-0565 were detected. The contribution of metabolic pathways was estimated from metabolite profiles in their excreta: the major metabolic pathway was oxidation (57-62%) and the next highest was the hydrolysis pathway (23-33%). These results suggest that there are marked species differences in the metabolic pathways of DSP-0565 between humans and animals. Finally, DSP-0565 human oral clearance (CL/F) was predicted using in vitro-in vivo extrapolation (IVIVE) with/without animal scaling factors (SF, in vivo intrinsic clearance/in vitro intrinsic clearance). The SF improved the underestimation of IVIVE (fold error = 0.22), but the prediction was overestimated (fold error = 2.4-3.3). In contrast, the use of SF for hydrolysis pathway was the most accurate for the prediction (fold error = 1.0-1.4). Our findings suggest that understanding of species differences in metabolic pathways between humans and animals is important for predicting human metabolic clearance when using animal SF.

In Vitro-In Vivo Extrapolation and Hepatic Clearance-Dependent Underprediction

Accurately predicting the hepatic clearance of compounds using in vitro to in vivo extrapolation (IVIVE) is crucial within the pharmaceutical industry. However, several groups have recently highlighted the serious error in the process. Although empirical or regression-based scaling factors may be used to mitigate the common underprediction, they provide unsatisfying solutions because the reasoning behind the underlying error has yet to be determined. One previously noted trend was intrinsic clearance-dependent underprediction, highlighting the limitations of current in vitro systems. When applying these generated in vitro intrinsic clearance values during drug development and making first-in-human dose predictions for new chemical entities though, hepatic clearance is the parameter that must be estimated using a model of hepatic disposition, such as the well-stirred model. Here, we examine error across hepatic clearance ranges and find a similar hepatic clearance-dependent trend, with high clearance compounds not predicted to be so, demonstrating another gap in the field.

Quantitative Prediction of Human Hepatic Clearance for P450 and Non-P450 Substrates from In Vivo Monkey Pharmacokinetics Study and In Vitro Metabolic Stability Tests Using Hepatocytes

Accurate prediction of human pharmacokinetics for drugs remains challenging, especially for non-cytochrome P450 (P450) substrates. Hepatocytes might be suitable for predicting hepatic intrinsic clearance (CL_int) of new chemical entities, because they can be applied to various compounds regardless of the metabolic enzymes. However, it was reported that hepatic CL_int is underestimated in hepatocytes. The purpose of the present study was to confirm the predictability of human hepatic clearance for P450 and non-P450 substrates in hepatocytes and the utility of animal scaling factors for the prediction using hepatocytes. CL_int values for 30 substrates of P450, UDP-glucuronosyltransferase, flavin-containing monooxygenase, esterases, reductases, and aldehyde oxidase in human microsomes, human S9 and human, rat, and monkey hepatocytes were estimated. Hepatocytes were incubated in serum of each species. Furthermore, CL_int values in human hepatocytes were corrected with empirical, monkey, and rat scaling factors. CL_int values in hepatocytes for most compounds were underestimated compared to observed values regardless of the metabolic enzyme, and the predictability was improved by using the scaling factors. The prediction using human hepatocytes corrected with monkey scaling factor showed the highest predictability for both P450 and non-P450 substrates among the predictions using liver microsomes, liver S9, and hepatocytes with or without scaling factors. CL_int values by this method for 80% and 90% of all compounds were within 2- and 3-fold of observed values, respectively. This method is accurate and useful for estimating new chemical entities, with no need to care about cofactors, localization of metabolic enzymes, or protein binding in plasma and incubation mixture.

Lack of Exposure in a First-in-Man Study Due to Aldehyde Oxidase Metabolism: Investigated by Use of 14C-microdose, Humanized Mice, Monkey Pharmacokinetics, and In Vitro Methods

Inclusion of a microdose of ¹⁴C-labeled drug in the first-in-man study of new investigational drugs and subsequent analysis by accelerator mass spectrometry has become an integrated part of drug development at Lundbeck. It has been found to be highly informative with regard to investigations of the routes and rates of excretion of the drug and the human metabolite profiles according to metabolites in safety testing guidance and also when additional metabolism-related issues needed to be addressed. In the first-in-man study with the NCE Lu AF09535, contrary to anticipated, surprisingly low exposure was observed when measuring the parent compound using conventional bioanalysis. Parallel accelerator mass spectrometry analysis revealed that the low exposure was almost exclusively attributable to extensive metabolism. The metabolism observed in humans was mediated via a human specific metabolic pathway, whereas an equivalent extent of metabolism was not observed in preclinical species. In vitro, incubation studies in human liver cytosol revealed involvement of aldehyde oxidase (AO) in the biotransformation of Lu AF09535. In vivo, substantially lower plasma exposure of Lu AF09535 was observed in chimeric mice with humanized livers compared with control animals. In addition, Lu AF09535 exhibited very low oral bioavailability in monkeys despite relatively low clearance after intravenous administration in contrast to the pharmacokinetics in rats and dogs, both showing low clearance and high bioavailability. The in vitro and in vivo methods applied were proved useful for identifying and evaluating AO-dependent metabolism. Different strategies to integrate these methods for prediction of in vivo human clearance of AO substrates were evaluated.

Challenges and Opportunities with Non-CYP Enzymes Aldehyde Oxidase, Carboxylesterase, and UDP-Glucuronosyltransferase: Focus on Reaction Phenotyping and Prediction of Human Clearance

Over the years, significant progress has been made in reducing metabolic instability due to cytochrome P450-mediated oxidation. High-throughput metabolic stability screening has enabled the advancement of compounds with little to no oxidative metabolism. Furthermore, high lipophilicity and low aqueous solubility of presently pursued chemotypes reduces the probability of renal excretion. As such, these low microsomal turnover compounds are often substrates for non-CYP-mediated metabolism. UGTs, esterases, and aldehyde oxidase are major enzymes involved in catalyzing such metabolism. Hepatocytes provide an excellent tool to identify such pathways including elucidation of major metabolites. To predict human PK parameters for P450-mediated metabolism, in vitro-in vivo extrapolation using hepatic microsomes, hepatocytes, and intestinal microsomes has been actively investigated. However, such methods have not been sufficiently evaluated for non-P450 enzymes. In addition to the involvement of the liver, extrahepatic enzymes (intestine, kidney, lung) are also likely to contribute to these pathways. While there has been considerable progress in predicting metabolic pathways and clearance primarily mediated by the liver, progress in characterizing extrahepatic metabolism and prediction of clearance has been slow. Well-characterized in vitro systems or in vivo animal models to assess drug-drug interaction potential and intersubject variability due to polymorphism are not available. Here we focus on the utility of appropriate in vitro studies to characterize non-CYP-mediated metabolism and to understand the enzymes involved followed by pharmacokinetic studies in the appropriately characterized surrogate species. The review will highlight progress made in establishing in vitro-in vivo correlation, predicting human clearance and avoiding costly clinical failures when non-CYP-mediated metabolic pathways are predominant.

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.

A perspective on the prediction of drug pharmacokinetics and disposition in drug research and development

Prediction of human pharmacokinetics of new drugs, as well as other disposition attributes, has become a routine practice in drug research and development. Prior to the 1990s, drug disposition science was used in a mostly descriptive manner in the drug development phase. With the advent of in vitro methods and availability of human-derived reagents for in vitro studies, drug-disposition scientists became engaged in the compound design phase of drug discovery to optimize and predict human disposition properties prior to nomination of candidate compounds into the drug development phase. This has reaped benefits in that the attrition rate of new drug candidates in drug development for reasons of unacceptable pharmacokinetics has greatly decreased. Attributes that are predicted include clearance, volume of distribution, half-life, absorption, and drug-drug interactions. In this article, we offer our experience-based perspectives on the tools and methods of predicting human drug disposition using in vitro and animal data.

Prediction of hepatic plasma clearance in vivo from gel-entrapped rat and human hepatocytes

This paper aimed to evaluate the applicability of gel-entrapped rat and human hepatocytes in the prediction of hepatic plasma clearance (CLh,plasma) in vivo. The in vitro intrinsic clearances (CLint,in vitro) for the selected compounds were determined from the substrate disappearance rate, and further used to predict CLh,plasma using 3 classical mathematical models (well-stirred, parallel-tube, and dispersion) and disregarding drug binding. As a result, the predicted values from gel-entrapped rat hepatocytes were mostly within 2 SE of the literature data with a high correlation coefficient (R2) of 0.88–0.91. The predicted data with human hepatocytes also fitted well with the clinical data, indicating a high accuracy in prediction of in-vivo clearance. With respect to the mathematical model for predicting CLh,plasma, the parallel-tube and dispersion models produced a better prediction than the well-stirred model, and we suggest using the parallel-tube model because it is less complex mathematically. In conclusion, gel-entrapped hepatocytes predicted the drug clearance well and seemed to be a useful tool in the process of drug discovery.

Discovery of the Highly Potent PI3K/mTOR Dual Inhibitor PF-04979064 through Structure-Based Drug Design

PI3K, AKT, and mTOR are key kinases from PI3K signaling pathway being extensively pursued to treat a variety of cancers in oncology. To search for a structurally differentiated back-up candidate to PF-04691502, which is currently in phase I/II clinical trials for treating solid tumors, a lead optimization effort was carried out with a tricyclic imidazo[1,5]naphthyridine series. Integration of structure-based drug design and physical properties-based optimization yielded a potent and selective PI3K/mTOR dual kinase inhibitor PF-04979064. This manuscript discusses the lead optimization for the tricyclic series, which both improved the in vitro potency and addressed a number of ADMET issues including high metabolic clearance mediated by both P450 and aldehyde oxidase (AO), poor permeability, and poor solubility. An empirical scaling tool was developed to predict human clearance from in vitro human liver S9 assay data for tricyclic derivatives that were AO substrates.