Ontogeny of Human Liver Aldehyde Oxidase: Developmental Changes and Implications for Drug Metabolism.

Despite the increasing importance of aldehyde oxidase (AO) in the drug metabolism of clinical candidates, ontogeny data for AO are limited. The objective of our study was to characterize the age-dependent AO content and activity in the human liver cytosolic fraction (HLC) and human hepatocytes (HH). HLC (n = 121 donors) and HH (n = 50 donors) were analyzed for (1) AO protein content by quantitative proteomics and (2) enzyme activity using carbazeran as a probe substrate. AO activity showed high technical variability and poor correlation with the content in HLC samples, whereas hepatocyte samples showed a strong correlation between the content and activity. Similarly, AO content and activity showed no significant age-dependent differences in HLC samples, whereas the average AO content and activity in hepatocytes increased significantly (∼20-40-fold) from the neonatal levels (0-28 days). Based on the hepatocyte data, the age at which 50% of the adult AO content is reached (age50) was 3.15 years (0.32-13.97 years, 95% CI). Metabolite profiling of carbazeran revealed age-dependent metabolic switching and the role of non-AO mechanisms (glucuronidation and desmethylation) in carbazeran elimination. The content-activity correlation in hepatocytes improved significantly (R2 = 0.95; p < 0.0001) in samples showing <10% contribution of glucuronidation toward the overall metabolism, confirming that AO-mediated oxidation and glucuronidation are the key routes of carbazeran metabolism. Considering the confounding effect of glucuronidation on AO activity, AO content-based ontogeny data are a more direct reflection of developmental changes in protein expression. The comprehensive ontogeny data of AO in HH samples are more reliable than HLC data, which are important for developing robust physiologically based pharmacokinetic models for predicting AO-mediated metabolism in children.

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.

Industry Perspective on the Pharmacokinetic and Absorption, Distribution, Metabolism, and Excretion Characterization of Heterobifunctional Protein Degraders.

Targeted protein degraders (TPDs), specifically the bifunctional protein degraders discussed in this manuscript, consist of two linked ligands for a protein of interest and an E3 ligase, resulting in molecules that largely violate accepted physicochemical limits (e.g., Lipinski's Rule of Five) for oral bioavailability. In 2021, the IQ Consortium Degrader DMPK/ADME Working Group undertook a survey of 18 IQ member and nonmember companies working on degraders to understand whether the characterization and optimization of these molecules were different from any other beyond the Rule of Five (bRo5) compounds. Additionally, the working group sought to identify pharmacokinetic (PK)/absorption, distribution, metabolism, and excretion (ADME) areas in need of further evaluation and where additional tools could aid in more rapid advancement of TPDs to patients. The survey revealed that although TPDs reside in a challenging bRo5 physicochemical space, most respondents focus their efforts on oral delivery. Physicochemical properties required for oral bioavailability were generally consistent across the companies surveyed. Many of the member companies used modified assays to address challenging degrader properties (e.g., solubility, nonspecific binding), but only half indicated that they modified their drug discovery workflows. The survey also suggested the need for further scientific investigation in the areas of central nervous system penetration, active transport, renal elimination, lymphatic absorption, in silico/machine learning, and human pharmacokinetic prediction. Based on the survey results, the Degrader DMPK/ADME Working Group concluded that TPD evaluation does not fundamentally differ from other bRo5 compounds but requires some modification compared with traditional small molecules and proposes a generic workflow for PK/ADME evaluation of bifunctional TPDs. SIGNIFICANCE STATEMENT: Based on an industry survey, this article provides an understanding of the current state of absorption, distribution, metabolism, and excretion science pertaining to characterizing and optimizing targeted protein degraders, specifically bifunctional protein degraders, based upon responses by 18 IQ consortium members and non-members developing targeted protein degraders. Additionally, this article puts into context the differences / similarities in methods and strategies utilized for heterobifunctional protein degraders compared to other beyond Rule of Five molecules and conventional small molecule drugs.

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.

Direct Comparison of the Prediction of the Unbound Brain-to-Plasma Partitioning Utilizing Machine Learning Approach and Mechanistic Neuropharmacokinetic Model.

The mechanistic neuropharmacokinetic (neuroPK) model was established to predict unbound brain-to-plasma partitioning (Kp,uu,brain) by considering in vitro efflux activities of multiple drug resistance 1 (MDR1) and breast cancer resistance protein (BCRP). Herein, we directly compare this model to a computational machine learning approach utilizing physicochemical descriptors and efflux ratios of MDR1 and BCRP-expressing cells for predicting Kp,uu,brain in rats. Two different types of machine learning techniques, Gaussian processes (GP) and random forest regression (RF), were assessed by the time and cluster-split validation methods using 640 internal compounds. The predictivity of machine learning models based on only molecular descriptors in the time-split dataset performed worse than the cluster-split dataset, whereas the models incorporating MDR1 and BCRP efflux ratios showed similar predictivity between time and cluster-split datasets. The GP incorporating MDR1 and BCRP in the time-split dataset achieved the highest correlation (R2 = 0.602). These results suggested that incorporation of MDR1 and BCRP in machine learning is beneficial for robust and accurate prediction. Kp,uu,brain prediction utilizing the neuroPK model was significantly worse compared to machine learning approaches for the same dataset. We also investigated the predictivity of Kp,uu,brain using an external independent test set of 34 marketed drugs. Compared to machine learning models, the neuroPK model showed better predictive performance with R2 of 0.577. This work demonstrates that the machine learning model for Kp,uu,brain achieves maximum predictive performance within the chemical applicability domain, whereas the neuroPK model is applicable more widely beyond the chemical space covered in the training dataset.

Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper.

Quantitative translation of information on drug absorption, disposition, receptor engagement, and drug-drug interactions from bench to bedside requires models informed by physiological parameters that link in vitro studies to in vivo outcomes. To predict in vivo outcomes, biochemical data from experimental systems are routinely scaled using protein quantity in these systems and relevant tissues. Although several laboratories have generated useful quantitative proteomic data using state-of-the-art mass spectrometry, no harmonized guidelines exit for sample analysis and data integration to in vivo translation practices. To address this gap, a workshop was held on September 27 and 28, 2018, in Cambridge, MA, with 100 experts attending from academia, the pharmaceutical industry, and regulators. Various aspects of quantitative proteomics and its applications in translational pharmacology were debated. A summary of discussions and best practices identified by this expert panel are presented in this "White Paper" alongside unresolved issues that were outlined for future debates.

Discovery of N-((3R,4R)-4-Fluoro-1-(6-((3-methoxy-1-methyl-1H-pyrazol-4-yl)amino)-9-methyl-9H-purin-2-yl)pyrrolidine-3-yl)acrylamide (PF-06747775) through Structure-Based Drug Design: A High Affinity Irreversible Inhibitor Targeting Oncogenic EGFR Mutants with Selectivity over Wild-Type EGFR.

Mutant epidermal growth factor receptor (EGFR) is a major driver of non-small-cell lung cancer (NSCLC). Marketed first generation inhibitors, such as erlotinib, effect a transient beneficial response in EGFR mutant NSCLC patients before resistance mechanisms render these inhibitors ineffective. Secondary oncogenic EGFR mutations account for approximately 50% of relapses, the most common being the gatekeeper T790M substitution that renders existing therapies ineffective. The discovery of PF-06459988 (1), an irreversible pyrrolopyrimidine inhibitor of EGFR T790M mutants, was recently disclosed.1 Herein, we describe our continued efforts to achieve potency across EGFR oncogenic mutations and improved kinome selectivity, resulting in the discovery of clinical candidate PF-06747775 (21), which provides potent EGFR activity against the four common mutants (exon 19 deletion (Del), L858R, and double mutants T790M/L858R and T790M/Del), selectivity over wild-type EGFR, and desirable ADME properties. Compound 21 is currently being evaluated in phase-I clinical trials of mutant EGFR driven NSCLC.

Clearance Prediction of Targeted Covalent Inhibitors by In Vitro-In Vivo Extrapolation of Hepatic and Extrahepatic Clearance Mechanisms.

The concept of target-specific covalent enzyme inhibitors appears attractive from both an efficacy and a selectivity viewpoint considering the potential for enhanced biochemical efficiency associated with an irreversible mechanism. Aside from potential safety concerns, clearance prediction of covalent inhibitors represents a unique challenge due to the inclusion of nontraditional metabolic pathways of direct conjugation with glutathione (GSH) or via GSH S-transferase-mediated processes. In this article, a novel pharmacokinetic algorithm was developed using a series of Pfizer kinase selective acrylamide covalent inhibitors based on their in vitro-in vivo extrapolation of systemic clearance in rats. The algorithm encompasses the use of hepatocytes as an in vitro model for hepatic clearance due to oxidative metabolism and GSH conjugation, and the use of whole blood as an in vitro surrogate for GSH conjugation in extrahepatic tissues. Initial evaluations with clinical covalent inhibitors suggested that the scaling algorithm developed from rats may also be useful for human clearance prediction when species-specific parameters, such as hepatocyte and blood stability and blood binding, were considered. With careful consideration of clearance mechanisms, the described in vitro-in vivo extrapolation approach may be useful to facilitate candidate optimization, selection, and prediction of human pharmacokinetic clearance during the discovery and development of targeted covalent inhibitors.

Discovery of 1-{(3R,4R)-3-[({5-Chloro-2-[(1-methyl-1H-pyrazol-4-yl)amino]-7H-pyrrolo[2,3-d]pyrimidin-4-yl}oxy)methyl]-4-methoxypyrrolidin-1-yl}prop-2-en-1-one (PF-06459988), a Potent, WT Sparing, Irreversible Inhibitor of T790M-Containing EGFR Mutants.

First generation EGFR TKIs (gefitinib, erlotinib) provide significant clinical benefit for NSCLC cancer patients with oncogenic EGFR mutations. Ultimately, these patients' disease progresses, often driven by a second-site mutation in the EGFR kinase domain (T790M). Another liability of the first generation drugs is severe adverse events driven by inhibition of WT EGFR. As such, our goal was to develop a highly potent irreversible inhibitor with the largest selectivity ratio between the drug-resistant double mutants (L858R/T790M, Del/T790M) and WT EGFR. A unique approach to develop covalent inhibitors, optimization of reversible binding affinity, served as a cornerstone of this effort. PF-06459988 was discovered as a novel, third generation irreversible inhibitor, which demonstrates (i) high potency and specificity to the T790M-containing double mutant EGFRs, (ii) minimal intrinsic chemical reactivity of the electrophilic warhead, (iii) greatly reduced proteome reactivity relative to earlier irreversible EGFR inhibitors, and (iv) minimal activity against WT EGFR.

In Vitro Kinetic Characterization of Axitinib Metabolism.

N-Methyl-2-[3-((E)-2-pyridin-2-yl-vinyl)-1H-indazol-6-ylsulfanyl]-benzamide (axitinib) is an oral inhibitor of vascular endothelial growth factor receptors 1-3, which is approved for the treatment of advanced renal cell cancer. Human [(14)C]-labeled clinical studies indicate axitinib's primary route of clearance is metabolism. The aims of the in vitro experiments presented herein were to identify and characterize the enzymes involved in axitinib metabolic clearance. In vitro biotransformation studies of axitinib identified a number of metabolites including an axitinib sulfoxide, several less abundant oxidative metabolites, and glucuronide conjugates. The most abundant NADPH- and UDPGA-dependent metabolites, axitinib sulfoxide (M12) and axitinib N-glucuronide (M7) were selected for phenotyping and kinetic study. Phenotyping experiments with human liver microsomes (HLMs) using chemical inhibitors and recombinant human cytochrome P450s demonstrated axitinib was predominately metabolized by CYP3A4/5, with minor contributions from CYP2C19 and CYP1A2. The apparent substrate concentration at half-maximal velocity (Km) and Vmax values for the formation of axitinib sulfoxide by CYP3A4 or CYP3A5 were 4.0 or 1.9 µM and 9.6 or 1.4 pmol·min(-1)·pmol(-1), respectively. Using a CYP3A4-specific inhibitor (Cyp3cide) in liver microsomes expressing CYP3A5, 66% of the axitinib intrinsic clearance was attributable to CYP3A4 and 15% to CYP3A5. Axitinib N-glucuronidation was primarily catalyzed by UDP-glucuronosyltransferase (UGT) UGT1A1, which was verified by chemical inhibitors and UGT1A1 null expressers, with lesser contributions from UGTs 1A3, 1A9, and 1A4. The Km and Vmax values describing the formation of the N-glucuronide in HLM or rUGT1A1 were 2.7 µM or 0.75 µM and 8.9 or 8.3 pmol·min(-1)·mg(-1), respectively. In summary, CYP3A4 is the major enzyme involved in axitinib clearance with lesser contributions from CYP3A5, CYP2C19, CYP1A2, and UGT1A1.

Metabolism of xenobiotics by aldehyde oxidase.

Aldehyde oxidase (AO) is a cytosolic molybdoflavoprotein whose contribution to the metabolism and clearance of xenobiotics-containing heterocyclic rings has attracted increased interest in recent years. This unit details methods for identification and confirmation of AO as a metabolic pathway as well as a method for estimating clearance of compounds that are AO substrates.

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.

Relative contributions of cytochrome CYP3A4 versus CYP3A5 for CYP3A-cleared drugs assessed in vitro using a CYP3A4-selective inactivator (CYP3cide).

Metabolism by cytochrome P4503A (CYP3A) is the most prevalent clearance pathway for drugs. Designation of metabolism by CYP3A commonly refers to the potential contribution by one or both of two enzymes, CYP3A4 and CYP3A5. The metabolic turnover of 32 drugs known to be largely metabolized by CYP3A was examined in human liver microsomes (HLMs) from CYP3A5 expressers (*1/*1 genotype) and nonexpressers (*3/*3 genotype) in the presence and absence of ketoconazole and CYP3cide (a selective CYP3A4 inactivator) to calculate the contribution of CYP3A5 to metabolism. Drugs with the highest contribution of CYP3A5 included atazanavir, vincristine, midazolam, vardenafil, otenabant, verapamil, and tacrolimus, whereas 17 of the 32 tested showed negligible CYP3A5 contribution. For specific reactions in HLMs from *1/*1 donors, CYP3A5 contributes 55% and 44% to midazolam 1'- and 4-hydroxylation, 16% to testosterone 6ß-hydroxylation, 56% and 19% to alprazolam 1'- and 4-hydroxylation, 10% to tamoxifen N-demethylation, and 58% to atazanavir p-hydroxylation. Comparison of the in vitro observations to clinical pharmacokinetic data showed only a weak relationship between estimated contribution by CYP3A5 and impact of CYP3A5 genotype on oral clearance, in large part because of the scatter in clinical data and the low numbers of study subjects used in CYP3A5 pharmacogenetics studies. These data should be useful in guiding which drugs should be evaluated for differences in pharmacokinetics and metabolism between subjects expressing CYP3A5 and those who do not express this enzyme.

Why do most human liver cytosol preparations lack xanthine oxidase activity?

When investigating the potential for xanthine oxidase (XO)-mediated metabolism of a new chemical entity in vitro, selective chemical inhibition experiments are typically used. Most commonly, these inhibition experiments are performed using the inhibitor allopurinol (AP) and commercially prepared human liver cytosol (HLC) as the enzyme source. For reasons detailed herein, it is also a common practice to perfuse livers with solutions containing AP prior to liver harvest. The exposure to AP in HLC preparations could obviously pose a problem for measuring in vitro XO activity. To investigate this potential problem, an HPLC-MS/MS assay was developed to determine whether AP and its primary metabolite, oxypurinol, are retained within the cytosol for livers that were treated with AP during liver harvest. Differences in enzymatic activity for XO and aldehyde oxidase (AO) in human cytosol that can be ascribed to AP exposure were also evaluated. The results confirmed the presence of residual AP (some) and oxypurinol (all) human liver cytosol preparations that had been perfused with an AP-containing solution. In every case where oxypurinol was detected, XO activity was not observed. In contrast, the presence of AP and oxypurinol did not appear to have an impact on AO activity. Pooled HLC that was purchased from a commercial source also contained residual oxypurinol and did not show any XO activity. In the future, it is recommended that each HLC batch is screened for oxypurinol and/or XO activity prior to testing for XO-mediated metabolism of a new chemical entity.

Targeting small cell lung cancer harboring PIK3CA mutation with a selective oral PI3K inhibitor PF-4989216.

PURPOSE: Constitutive activation of phosphoinositide 3-kinase (PI3K) occurs frequently in many human tumors via either gene mutation in the p110α catalytic subunit of PI3K or functional loss of tumor suppressor PTEN. Patients with small-cell lung cancer (SCLC) have very poor prognosis and survival rates such that an effective targeted therapy is in strong demand for these patients. In this study, we characterized the highly selective oral PI3K inhibitor, PF-4989216, in preclinical SCLC models to investigate whether targeting the PI3K pathway is an effective targeted therapy option for SCLCs that harbor a PIK3CA mutation. EXPERIMENTAL DESIGN: A panel of SCLC cell lines with PIK3CA mutation or PTEN loss were treated with PF-4989216 in several in vitro assays, including PI3K pathway signaling, cell viability, apoptosis, cell-cycle progression, and cell transformation. SCLC cell lines that were sensitive in vitro to PF-4989216 were further evaluated by in vivo animal studies to determine the pharmacokinetic/pharmacodynamic relationship and tumor growth inhibition (TGI) by PF-4989216 treatment. RESULTS: PF-4989216 inhibited PI3K downstream signaling and subsequently led to apoptosis induction, and inhibition in cell viability, transformation, and xenograft tumor growth in SCLCs harboring PIK3CA mutation. In SCLCs with PTEN loss, PF-4989216 also inhibited PI3K signaling but did not induce BCL2-interacting mediator (BIM)-mediated apoptosis nor was there any effect on cell viability or transformation. These results implicate differential tumorigenesis and apoptosis mechanisms in SCLCs harboring PIK3CA mutation versus PTEN loss. CONCLUSIONS: Our results suggest that PF-4989216 is a potential cancer drug candidate for patients with SCLC with PIK3CA mutation but not PTEN loss.

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.

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.

Strategies for a comprehensive understanding of metabolism by aldehyde oxidase.

INTRODUCTION: Aldehyde oxidase (AO) is a drug-metabolizing molybdo-flavoenzyme with profound species differences in expression and activity toward various substrates. The contribution of this enzyme to the metabolism and clearance of heterocyclic-containing xenobiotics appears to have increased in recent years, but has not always been identified prior to clinical studies. As a result, drug candidates have been negatively impacted in development. AREAS COVERED: This review provides the most recent in vitro and in vivo strategies for the drug metabolism-pharmacokinetic (DMPK) scientist. The review details approaches for confirmation of AO as an operable metabolic pathway, estimating clearance and fraction of total metabolism, and identification of an appropriate surrogate species for human AO activity for evaluating safety of clinically relevant metabolites. EXPERT OPINION: As the role of AO in metabolism of new drug molecules continues to emerge, it is critical that DMPK scientists have the most updated methodologies to enable formulation of a thorough experimental plan to understand the potential implications of this metabolic pathway. Whether it is higher-than-expected clearance, contributing to an unfavorable half-life, or the formation of an AO-derived disproportionate human metabolite (DHM), such a plan would serve to minimize complications or attrition of drug candidates due to unforeseen issues in the clinic.

Selective mechanism-based inactivation of CYP3A4 by CYP3cide (PF-04981517) and its utility as an in vitro tool for delineating the relative roles of CYP3A4 versus CYP3A5 in the metabolism of drugs.

CYP3cide (PF-4981517; 1-methyl-3-[1-methyl-5-(4-methylphenyl)-1H-pyrazol-4-yl]-4-[(3S)-3-piperidin-1-ylpyrrolidin-1-yl]-1H-pyrazolo[3,4-d]pyrimidine) is a potent, efficient, and specific time-dependent inactivator of human CYP3A4. When investigating its inhibitory properties, an extreme metabolic inactivation efficiency (k(inact)/K(I)) of 3300 to 3800 ml · min⁻¹ · µmol⁻¹ was observed using human liver microsomes from donors of nonfunctioning CYP3A5 (CYP3A5 *3/*3). This observed efficiency equated to an apparent K(I) between 420 and 480 nM with a maximal inactivation rate (k(inact)) equal to 1.6 min⁻¹. Similar results were achieved with testosterone, another CYP3A substrate, and other sources of the CYP3A4 enzyme. To further illustrate the abilities of CYP3cide, its partition ratio of inactivation was determined with recombinant CYP3A4. These studies produced a partition ratio approaching unity, thus underscoring the inactivation capacity of CYP3cide. When CYP3cide was tested at a concentration and preincubation time to completely inhibit CYP3A4 in a library of genotyped polymorphic CYP3A5 microsomes, the correlation of the remaining midazolam 1'-hydroxylase activity to CYP3A5 abundance was significant (R² value equal to 0.51, p value of <0.0001). The work presented here supports these findings by fully characterizing the inhibitory properties and exploring CYP3cide's mechanism of action. To aid the researcher, multiple commercially available sources of CYP3cide were established, and a protocol was developed to quantitatively determine CYP3A4 contribution to the metabolism of an investigational compound. Through the establishment of this protocol and the evidence provided here, we believe that CYP3cide is a very useful tool for understanding the relative roles of CYP3A4 versus CYP3A5 and the impact of CYP3A5 genetic polymorphism on a compound's pharmacokinetics.