The Drug-Drug Interaction Between Erlotinib and OSI-930 is Mediated Through Aldehyde Oxidase Inhibition.

The propensity for aldehyde oxidase (AO) substrates to be implicated in drug-drug interactions (DDI) is not well-understood due to the dearth of potent inhibitors that elicit in vivo inhibition of AO. While there is only one reported instance of DDI that has been ascribed to the inhibition of AO to-date, the supporting evidence for this clinical interaction is rather tenuous and its veracity has been called into question. Our group recently reported that the epidermal growth factor receptor inhibitor erlotinib engendered potent time-dependent inhibition of AO with inactivation kinetic constants in the same order of magnitude as its free circulating plasma concentrations. At the same time, it was previously reported that the concomitant administration of erlotinib with the investigational drug OSI-930 culminated in a ~2-fold increase in its systemic exposure. Although the basis underpinning this interaction remains unclear, the structure of OSI-930 contains a quinoline motif which is amenable to oxidation at the electrophilic carbon adjacent to the nitrogen atom by molybdenum-containing hydroxylases like AO. In this study, we conducted metabolite identification which revealed that OSI-930 undergoes AO metabolism to a mono-oxygenated 2-oxo metabolite and assessed its formation kinetics in human liver cytosol. Additionally, reaction phenotyping in human hepatocytes revealed that AO contributes nearly ~50% to the overall metabolism of OSI-930. Finally, modelling the interaction between erlotinib and OSI-930 using a mechanistic static model projected an ~1.85-fold increase in the systemic exposure of OSI-930 - which accurately recapitulated clinical observations. Significance Statement In this study, we delineate an AO metabolic pathway in the investigational drug OSI-930 for the first time and confirmed that it represented a major route of metabolism through reaction phenotyping in human hepatocytes. Our study provided compelling mechanistic and modelling evidence for the first instance of an AO-mediated clinical DDI stemming from the in vivo inhibition of the AO-mediated quinoline 2-oxidation pathway in OSI-930 by erlotinib.

Evaluation of Icotinib as a Potent and Selective Inhibitor of Aldehyde Oxidase for Reaction Phenotyping in Human Hepatocytes.

Aldehyde oxidase (AO) is a molybdenum cofactor-containing cytosolic enzyme that has gained prominence due to its involvement in the developmental failure of several drug candidates in first-in-human trials. Unlike cytochrome P450s (P450) and glucuronosyltransferase, AO substrates have been plagued by poor in vitro to in vivo extrapolation, leading to low systemic exposures and underprediction of human dose. However, apart from measuring a drug's AO clearance rates, it is also important to determine the relative contribution to metabolism by this enzyme (fm,AO). Although hydralazine is the most well-studied time-dependent inhibitor (TDI) of AO and is frequently employed for AO reaction phenotyping in human hepatocytes to derive fm,AO, multiple studies have expressed concerns pertaining to its utility in providing accurate estimates of fm,AO values due to its propensity to significantly inhibit P450s at the concentrations typically used for reaction phenotyping. In this study, we characterized icotinib, a cyclized analog of erlotinib, as a potent TDI of AO-inactivating human liver cytosolic zoniporide 2-oxidation equipotently with erlotinib with a maximal inactivate rate/inactivator concentration at half maximal inactivation rate (K I) ratio of 463 and 501 minute-1mM-1 , respectively. Moreover, icotinib also exhibits selectivity against P450 and elicits significantly weaker inhibition against human liver microsomal UGT1A1/3 as compared with erlotinib. Finally, we evaluated icotinib as an inhibitor of AO for reaction phenotyping in cryopreserved human hepatocytes and demonstrated that it can yield more accurate prediction of fm,AO compared with hydralazine and induce sustained suppression of AO activity at higher cell densities, which will be important for reaction phenotyping endeavors of low clearance drugs SIGNIFICANCE STATEMENT: In this study, we characterized icotinib as a potent time-dependent inhibitor of AO with ample selectivity margins against the P450s and UGT1A1/3 and demonstrated its utility for reaction phenotyping in human hepatocytes to obtain accurate estimates of fm,AO for victim DDI risk predictions. We envisage the adoption of icotinib in place of hydralazine in AO reaction phenotyping.

Radiolabel Uncovers Nonintuitive Metabolites of BIIB104: Novel Release of [14C]Cyanide from 2-Cyanothiophene and Subsequent Formation of [14C]Thiocyanate.

BIIB104 (formerly PF-04958242), N-((3S,4S)-4-(4-(5-cyanothiophen-2-yl)phenoxy)tetrahydrofuran-3-yl)propane-2-sulfonamide, is an α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor potentiator investigated for the treatment of cognitive impairment associated with schizophrenia. Preliminary in vitro metabolism studies with non-radiolabeled BIIB104 in rat, dog, and human liver microsomes (RLM, DLM, and HLM) showed O-dealkylation in all three species, tetrahydrofuran hydroxylation dominating in DLM and HLM, and thiophene hydroxylation prevalent in RLM. However, a subsequent rat mass balance study with [nitrile-14C]BIIB104 showed incomplete recovery of administered radioactivity (∼80%) from urine and feces over 7 days following an oral dose, and an exceptionally long plasma total radioactivity half-life. Radiochromatographic metabolite profiling and identification, including chemical derivation, revealed that [14C]cyanide was a major metabolite of [nitrile-14C]BIIB104 in RLM, but a minor and trace metabolite in DLM and HLM, respectively. Correspondingly in bile duct-cannulated rats, [14C]thiocyanate accounted for ∼53% of total radioactivity excreted over 48 hours postdose and it, as an endogenous substance, explained the exceptionally long plasma radioactivity half-life. The release of [14C]cyanide from the 2-cyanothiophene moiety is postulated to follow an epoxidation-initiated thiophene-opening based on the detection of non-radiolabeled counterpart metabolites in RLM. This unusual biotransformation serves as a lesson regarding placement of the radioactive label on an aryl nitrile when material will be used for evaluating the metabolism of a new drug candidate. Additionally, the potential cyanide metabolite of nitrile-containing drug molecules may be detected in liver microsomes with liquid chromatography-mass spectrometry following a chemical derivatization. SIGNIFICANCE STATEMENT: Using [nitrile-14C]BIIB104, non-intuitive metabolites of BIIB104 were discovered involving a novel cyanide release from the 2-cyanothiophene motif via a postulated epoxidation-initiated thiophene-opening. This unusual biotransformation serves as a lesson regarding placement of the radioactive label on an aryl nitrile when material will be used for evaluating the metabolism of a new drug candidate.

Projections of Drug-Drug Interactions Caused by Time-Dependent Inhibitors of Cytochrome P450 1A2, 2B6, 2C8, 2C9, 2C19, and 2D6 Using In Vitro Data in Static and Dynamic Models.

In vitro time-dependent inhibition (TDI) kinetic parameters for cytochrome P450 (CYP) 1A2, 2B6, 2C8, 2C9, 2C19, and 2D6, were determined in pooled human liver microsomes for 19 drugs (and 2 metabolites) for which clinical drug-drug interactions (DDI) are known. In vitro TDI data were incorporated into the projection of the magnitude of DDIs using mechanistic static models and Simcyp®. Results suggest that for the mechanistic static model, use of estimated average unbound exit concentration of the inhibitor from the liver resulted in a successful prediction of observed magnitude of clinical DDIs and was similar to Simcyp®. Overall, predictions of DDI magnitude (i.e., fold increase in AUC of a CYP-specific marker substrate) were within 2-fold of actual values. Geometric mean-fold errors were 1.7 and 1.6 for static and dynamic models, respectively. Projections of DDI from both models were also highly correlated to each other (r2 = 0.92). This investigation demonstrates that DDI can be reliably predicted from in vitro TDI data generated in HLM for several CYP enzymes. Simple mechanistic static model equations as well as more complex dynamic PBPK models can be employed in this process. Significance Statement Cytochrome P450 time-dependent inhibitors (TDI) can cause drug-drug interactions (DDI). An ability to reliably assess the potential for a new drug candidate to cause DDI is essential during drug development. In this report, TDI data for 19 drugs (and 2 metabolites) were measured and used in static and dynamic models to reliably project the magnitude of DDI resulting from inhibition of CYP1A2, 2B6, 2C8, 2C9, 2C19, and 2D6.

Human Absorption, Distribution, Metabolism, and Excretion Studies: Origins, Innovations, and Importance.

Human absorption, distribution, metabolism, and excretion (hADME) studies represent one of the most important clinical studies in terms of obtaining a comprehensive and quantitative overview of the total disposition of a drug. This article will provide background on the origins of hADME studies as well as provide an overview of technological innovations that have impacted how hADME studies are carried out and analyzed. An overview of the current state of the art for hADME studies will be provided, the impacts of advances in technology and instrumentation on the timing of and approaches to hADME studies will be discussed, and a summary of the parameters and information obtained from these studies will be offered. Additionally, aspects of the ongoing debate over the importance of animal absorption, distribution, metabolism, and excretion studies versus a "human-first, human-only strategy" will be presented. Along with the information above, this manuscript will highlight how, for over 50 years, Drug Metabolism and Disposition has served as an important outlet for the reporting of hADME studies. SIGNIFICANCE STATEMENT: Human absorption, distribution, metabolism, and excretion (hADME) studies have and will continue to be important to the understanding and development of drugs. This manuscript provides a historical perspective on the origins of hADME studies as well as advancements resulting in the current-state-of the art practice for these studies.

The Metabolism of Lufotrelvir, a Prodrug Investigated for the Treatment of SARS-COV2 in Humans Following Intravenous Administration.

The metabolism of lufotrelvir, a novel phosphate prodrug of PF-00835231 for the treatment of COVID-19, was evaluated in healthy human volunteers and clinical trial participants with COVID-19 following intravenous infusion. The prodrug was completely converted to PF-00835231 that was subsequently cleared by hydrolysis, hydroxylation, ketoreduction, epimerization, renal clearance, and secretion into the feces. The main circulating metabolite was a hydrolysis product (M7) that was present at concentrations greater than PF-00835231, and this was consistent between healthy volunteers and participants with COVID-19. On administration of [14C]lufotrelvir, only 63% of the dose was obtained in excreta over 10 days and total drug-related material demonstrated a prolonged terminal phase half-life in plasma. A considerable portion of the labeled material was unextractable from fecal homogenate and plasma. The position of the carbon-14 atom in the labeled material was at a leucine carbonyl, and pronase digestion of the pellet derived from extraction of the fecal homogenate showed that [14C]leucine was released. SIGNIFICANCE STATEMENT: Lufotrelvir is an experimental phosphate prodrug intravenous therapy investigated for the potential treatment of COVID-19 in a hospital setting. The overall metabolism of lufotrelvir was determined in human healthy volunteers and clinical trial participants with COVID-19. Conversion of the phosphate prodrug to the active drug PF-00835231 was complete and the subsequent metabolic clearance of the active drug was largely via amide bond hydrolysis. Substantial drug-related material was not recovered due to loss of the carbon-14 label to endogenous metabolism.

Linezolid Metabolism Is Catalyzed by Cytochrome P450 2J2, 4F2, and 1B1.

The oxazolidinone antibacterial linezolid has been in clinical use for over 20 years, yet knowledge of the contributions of specific cytochrome (CYP) 450 enzymes to the metabolic clearance of this drug were mostly unknown. In this investigation, it was revealed that three P450 enzymes that had not been previously explored in linezolid metabolism, CYP2J2, CYP4F2, and CYP1B1, catalyzed the 2-hydroxylation and de-ethyleneation of the morpholine moiety of linezolid. The intrinsic clearance for linezolid metabolism in pooled human liver microsomes was low at 0.51 µL/min/mg protein, consistent with its in vivo clearance in humans, and the KM was high (>200 µM). In recombinant human P450 enzymes, a rank order of intrinsic clearance values for linezolid 2-hydroxylation were CYP2J2 ≫ CYP4F2 > CYP2C8 > CYP1B1 ≈ CYP2D6 ≈ CYP3A4 > CYP1A1 > CYP3A5, with nine other P450 enzymes showing no linezolid metabolism. The effect of selective inhibitors for these eight P450 enzymes on linezolid metabolism in pooled human liver microsomes was evaluated to provide estimates of the relative fractional contributions of these enzymes to linezolid metabolism. These experiments suggest that CYP2J2 and CYP4F2 contribute about 50% each to linezolid hepatic metabolism. It is proposed that the oxidative metabolic clearance of linezolid is primarily catalyzed by these two unusual P450 enzymes and that this explains the lack of observation of meaningful effects of common perpetrators of drug interactions on linezolid pharmacokinetics. SIGNIFICANCE STATEMENT: Linezolid is an important antibacterial drug, but the enzymes involved in its oxidative metabolism were unknown. In this study, evidence is shown that supports an important role for two enzymes not frequently associated with the metabolism of drugs: cytochrome P450 2J2 and cytochrome P450 4F2. These observations offer insight to understand the results of clinical drug-drug interaction studies conducted on linezolid.

Intersystem Extrapolation Factors Are Substrate-Dependent for CYP3A4: Impact on Cytochrome P450 Reaction Phenotyping.

The use of intersystem extrapolation factors (ISEF) is required for the quantitative scaling of drug metabolism data generated in individually expressed cytochrome P450 (CYP) enzymes when estimating fractional contribution (fm) to metabolism by P450 enzymes in vivo. For successful prediction of fm, ISEF values must be universal across all substrates for any individual enzyme. In this study, ISEF values were generated for ten CYP3A4 selective substrates using a common source of recombinant heterologously expressed CYP3A4 (rCYP) and a pool of human liver microsomes. The resulting ISEF values for CYP3A4 were substrate-dependent and ranged 8-fold, with the highest value generated from intrinsic clearance of midazolam depletion (0.36) and the lowest from quinidine depletion (0.044). Application of these ISEF values for estimation of the fractional contribution of CYP3A4 and CYP2C19 to omeprazole clearance yielded values that ranged from 0.21-0.63 and 0.37-0.79, respectively, as compared with back-extrapolated in vivo fm values of 0.27 (CYP3A4) and 0.85 (CYP2C19) from clinical pharmacokinetic data. For risperidone, estimated fm values for CYP3A4 and CYP2D6 ranged from 0.87-0.98 and 0.02-0.13, respectively, as compared with in vivo values of 0.36 (CYP3A4) and 0.63-0.88 (CYP2D6), showing that the importance of CYP3A4 was overestimated, and the importance of CYP2D6 underestimated. Overall, these findings suggest that ISEF values for CYP3A4 can vary with the marker substrate used to derive them, thereby reducing the effectiveness of the approach of using metabolism data from rCYP3A4 with ISEF values for the prediction of fraction metabolized values in vivo. SIGNIFICANCE STATEMENT: Intersystem extrapolation factors are utilized for assigning fractional contributions of individual enzymes to drug clearance (fm) from drug metabolism data generated in recombinant P450s. The present data shows that intersystem extrapolation factors values for cytochrome P4503A4 vary with the substrate. This can lead to variable and erroneous prediction of fm.

An improved method for cytochrome p450 reaction phenotyping using a sequential qualitative-then-quantitative approach.

Cytochrome P450 reaction phenotyping to determine the fraction of metabolism values (fm) for individual enzymes is a standard study in the evaluation of a new drug. However, there are technical challenges in these studies caused by shortcomings in the selectivity of P450 inhibitors and unreliable scaling procedures for recombinant P450 (rCYP) data. In this investigation, a two-step "qualitative-then-quantitative" approach to P450 reaction phenotyping is described. In the first step, each rCYP is tested qualitatively for potential to generate metabolites. In the second step, selective inhibitors for the P450s identified in step1 are tested for their effects on metabolism using full inhibition curves. Forty-eight drugs were evaluated in step 1 and there were no examples of missing an enzyme important to in vivo clearance. Five drugs (escitalopram, fluvastatin, pioglitazone, propranolol, and risperidone) were selected for full phenotyping in step2 to determine fm values, with findings compared to fm values estimated from single inhibitor concentration data and rCYP with intersystem-extrapolation-factor corrections. The two-step approach yielded fm values for major drug clearing enzymes that are close to those estimated from clinical data: escitalopram and CYP2C19 (0.42 vs 0.36-0.82), fluvastatin and CYP2C9 (0.76 vs 0.76), pioglitazone and CYP2C8 (0.72 vs 0.73), propranolol and CYP2D6 (0.68 vs 0.37-0.56) and risperidone and CYP2D6 (0.60 vs 0.66-0.88). Reaction phenotyping data generated in this fashion should offer better input to physiologically-based pharmacokinetic models for prediction of DDI and impact of genetic polymorphisms on drug clearance. The qualitative-then-quantitative approach is proposed as a replacement to standard reaction phenotyping strategies. Significance Statement P450 reaction phenotyping is important for projecting drug-drug interactions and interpatient variability in drug exposure. However, currently recommended practices can frequently fail to provide reliable estimates of the fractional contributions of specific P450 enzymes (fm) to drug clearance. In this report, we describe a two-step qualitative-then-quantitative reaction phenotyping approach that yields more accurate estimates of fm.

Defining the Selectivity of Chemical Inhibitors Used for Cytochrome P450 Reaction Phenotyping: Overcoming Selectivity Limitations with a Six-Parameter Inhibition Curve-Fitting Approach.

The utility of chemical inhibitors in cytochrome P450 (CYP) reaction phenotyping is highly dependent on their selectivity and potency for their target CYP isoforms. In the present study, seventeen inhibitors of CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, and 3A4/5 commonly used in reaction phenotyping were evaluated for their cross-enzyme selectivity in pooled human liver microsomes. The data were evaluated using a statistical desirability analysis to identify (1) inhibitors of superior selectivity for reaction phenotyping and (2) optimal concentrations for each. Among the inhibitors evaluated, α-naphthoflavone, furafylline, sulfaphenazole, tienilic acid, N-benzylnirvanol, and quinidine were most selective, such that their respective target enzymes were inhibited by ~95% without inhibiting any other CYP enzyme by more than 10%. Other commonly employed inhibitors, such as ketoconazole and montelukast, among others, were of insufficient selectivity to yield a concentration that could adequately inhibit their target enzymes without affecting other CYP enzymes. To overcome these shortcomings, an experimental design was developed wherein dose response data from a densely sampled multi-concentration inhibition curve are analyzed by a six-parameter inhibition curve function, allowing accounting of the inhibition of off-target CYP isoforms inhibition and more reliable determination of maximum targeted enzyme inhibition. The approach was exemplified using rosiglitazone N-demethylation, catalyzed by both CYP2C8 and 3A4, and was able to discern the off-target inhibition by ketoconazole and montelukast from the inhibition of the targeted enzyme. This methodology yields more accurate estimates of CYP contributions in reaction phenotyping. Significance Statement Isoform-selective chemical inhibitors are important tools for identifying and quantifying enzyme contributions as part of a CYP reaction phenotyping assessment for projecting drug-drug interactions. However, currently employed practices fail to adequately compensate for shortcomings in inhibitor selectivity and the resulting confounding impact on estimates of the CYP enzyme contribution to drug clearance. In this report, we describe a detailed IC50 study design with 6-parameter modeling approach that yields more accurate estimates of enzyme contribution.

Disposition of Nirmatrelvir, an Orally Bioavailable Inhibitor of SARS-CoV-2 3C-Like Protease, across Animals and Humans.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3C-like protease inhibitor PF-07321332 (nirmatrelvir), in combination with ritonavir (Paxlovid), was recently granted emergency use authorization by multiple regulatory agencies for the treatment of coronavirus disease 2019 (COVID-19) in adults and pediatric patients. Disposition studies on nirmatrelvir in animals and in human reagents, which were used to support clinical studies, are described herein. Plasma clearance was moderate in rats (27.2 ml/min per kg) and monkeys (17.1 ml/min per kg), resulting in half-lives of 5.1 and 0.8 hours, respectively. The corresponding oral bioavailability was moderate in rats (34%-50%) and low in monkeys (8.5%), primarily due to oxidative metabolism along the gastrointestinal tract in this species. Nirmatrelvir demonstrated moderate plasma protein binding in rats, monkeys, and humans with mean unbound fractions ranging from 0.310 to 0.478. The metabolism of nirmatrelvir was qualitatively similar in liver microsomes and hepatocytes from rats, monkeys, and humans; prominent metabolites arose via cytochrome P450 (CYP450)-mediated oxidations on the P1 pyrrolidinone ring, P2 6,6-dimethyl-3-azabicyclo[3.1.0]hexane, and the tertiary-butyl group at the P3 position. Reaction phenotyping studies in human liver microsomes revealed that CYP3A4 was primarily responsible (fraction metabolized = 0.99) for the oxidative metabolism of nirmatrelvir. Minor clearance mechanisms involving renal and biliary excretion of unchanged nirmatrelvir were also noted in animals and in sandwich-cultured human hepatocytes. Nirmatrelvir was a reversible and time-dependent inhibitor as well as inducer of CYP3A activity in vitro. First-in-human pharmacokinetic studies have demonstrated a considerable boost in the oral systemic exposure of nirmatrelvir upon coadministration with the CYP3A4 inhibitor ritonavir, consistent with the predominant role of CYP3A4 in nirmatrelvir metabolism. SIGNIFICANCE STATEMENT: The manuscript describes the preclinical disposition, metabolism, and drug-drug interaction potential of PF-07321332 (nirmatrelvir), an orally active peptidomimetic-based inhibitor of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3CL protease, which has been granted emergency use authorization by multiple regulatory agencies around the globe for the treatment of coronavirus disease 2019 (COVID-19) in COVID-19-positive adults and pediatric patients who are at high risk for progression to severe COVID-19, including hospitalization or death.

Static and Dynamic Projections of Drug-Drug Interactions Caused by Cytochrome P450 3A Time-Dependent Inhibitors Measured in Human Liver Microsomes and Hepatocytes.

Cytochrome P450 3A (CYP3A) is a frequent target for time-dependent inhibition (TDI) that can give rise to drug-drug interactions (DDI). Yet many drugs that exhibit in vitro TDI for CYP3A do not result in DDI. There were 23 drugs with published clinical DDI evaluated for CYP3A TDI in human liver microsomes (HLM) and hepatocytes (HHEP), and these data were used in static and dynamic models for projecting DDI caused by inactivation of CYP3A in both liver and intestine. TDI parameters measured in HHEP, particularly the maximal rate of enzyme inactivation, were generally lower than those measured in HLM. In static models, the use of estimated average unbound organ exit concentrations offered the most accurate projections of DDI with geometric mean fold errors of 2.0 and 1.7 for HLM and HHEP, respectively. Use of maximum organ entry concentrations yielded marked overestimates of DDI. When evaluated in a binary fashion (i.e., projection of DDI of 1.25-fold or greater), data from HLM offered the greatest sensitivity (100%) and specificity (67%) and yielded no missed DDI when average unbound organ exit concentrations were used. In dynamic physiologically based pharmacokinetic modeling, accurate projections of DDI were obtained with geometric mean fold errors of 1.7 and 1.6 for HLM and HHEP, respectively. Sensitivity and specificity were 100% and 67% when using TDI data generated in HLM and Simcyp modeling. Overall, DDI caused by CYP3A-mediated TDI can be reliably projected using dynamic or static models. For static models, average organ unbound exit concentrations should be used as input values otherwise DDI will be markedly overestimated. SIGNIFICANCE STATEMENT: CYP3A time-dependent inhibitors (TDI) are important in the design and development of new drugs. The prevalence of CYP3A TDI is high among newly synthesized drug candidates, and understanding the potential need for running clinical drug-drug interaction (DDI) studies is essential during drug development. Ability to reliably predict DDI caused by CYP3A TDI has been difficult to achieve. We report a thorough evaluation of CYP3A TDI and demonstrate that DDI can be predicted when using appropriate models and input parameters generated in human liver microsomes or hepatocytes.

Development of Robust Quantitative Structure-Activity Relationship Models for CYP2C9, CYP2D6, and CYP3A4 Catalysis and Inhibition.

Cytochrome P450 enzymes are responsible for the metabolism of >75% of marketed drugs, making it essential to identify the contributions of individual cytochromes P450 to the total clearance of a new candidate drug. Overreliance on one cytochrome P450 for clearance levies a high risk of drug-drug interactions; and considering that several human cytochrome P450 enzymes are polymorphic, it can also lead to highly variable pharmacokinetics in the clinic. Thus, it would be advantageous to understand the likelihood of new chemical entities to interact with the major cytochrome P450 enzymes at an early stage in the drug discovery process. Typical screening assays using human liver microsomes do not provide sufficient information to distinguish the specific cytochromes P450 responsible for clearance. In this regard, we experimentally assessed the metabolic stability of ∼5000 compounds for the three most prominent xenobiotic metabolizing human cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4, and used the data sets to develop quantitative structure-activity relationship models for the prediction of high-clearance substrates for these enzymes. Screening library included the NCATS Pharmaceutical Collection, comprising clinically approved low-molecular-weight compounds, and an annotated library consisting of drug-like compounds. To identify inhibitors, the library was screened against a luminescence-based cytochrome P450 inhibition assay; and through crossreferencing hits from the two assays, we were able to distinguish substrates and inhibitors of these enzymes. The best substrate and inhibitor models (balanced accuracies ∼0.7), as well as the data used to develop these models, have been made publicly available (https://opendata.ncats.nih.gov/adme) to advance drug discovery across all research groups. SIGNIFICANCE STATEMENT: In drug discovery and development, drug candidates with indiscriminate cytochrome P450 metabolic profiles are considered advantageous, since they provide less risk of potential issues with cytochrome P450 polymorphisms and drug-drug interactions. This study developed robust substrate and inhibitor quantitative structure-activity relationship models for the three major xenobiotic metabolizing cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4. The use of these models early in drug discovery will enable project teams to strategize or pivot when necessary, thereby accelerating drug discovery research.

Production of active recombinant human aldehyde oxidase (AOX) in the baculovirus expression vector system (BEVS) and deployment in a pre-clinical fraction-of-control AOX compound exposure assay.

Human aldehyde oxidase (AOX) has emerged as a key enzyme activity for consideration in modern drug discovery. The enzyme catalyzes the oxidation of a wide variety of compounds, most notably azaheterocyclics that often form the building blocks of small molecule therapeutics. Failure to consider and assess AOX drug exposure early in the drug development cycle can have catastrophic consequences for novel compounds entering the clinic. AOX is a complex molybdopterin-containing iron-sulfur flavoprotein comprised of two identical 150 kDa subunits that has proven difficult to produce in recombinant form, and a commercial source of the purified human enzyme is currently unavailable. Thus, the potential exposure of novel drug development candidates to human AOX metabolism is usually assessed by using extracts of pooled human liver cytosol as a source of the enzyme. This can complicate the assignment of AOX-specific compound exposure due to its low activity and the presence of contaminating enzymes that may have overlapping substrate specificities. Herein is described a two-step process for the isolation of recombinant human AOX dimers to near homogeneity following production in the baculovirus expression vector system (BEVS). The deployment of this BEVS-produced recombinant human AOX as a substitute for human liver extracts in a fraction-of-control AOX compound-exposure screening assay is described. The ability to generate this key enzyme activity readily in a purified recombinant form provides for a more accurate and convenient approach to the assessment of new compound exposure to bona fide AOX drug metabolism.

Cytochrome P450 3A Time-Dependent Inhibition Assays Are Too Sensitive for Identification of Drugs Causing Clinically Significant Drug-Drug Interactions: A Comparison of Human Liver Microsomes and Hepatocytes and Definition of Boundaries for Inactivation Rate Constants.

Time-dependent inhibition (TDI) of CYP3A is an important mechanism underlying numerous drug-drug interactions (DDIs), and assays to measure this are done to support early drug research efforts. However, measuring TDI of CYP3A in human liver microsomes (HLMs) frequently yields overestimations of clinical DDIs and thus can lead to the erroneous elimination of many viable drug candidates from further development. In this investigation, 50 drugs were evaluated for TDI in HLMs and suspended human hepatocytes (HHEPs) to define appropriate boundary lines for the TDI parameter rate constant for inhibition (kobs) at a concentration of 30 µM. In HLMs, a kobs value of 0.002 minute-1 was statistically distinguishable from control; however, many drugs show kobs greater than this but do not cause DDI. A boundary line defined by the drug with the lowest kobs that causes a DDI (diltiazem) was established at 0.01 minute-1 Even with this boundary, of the 33 drugs above this value, only 61% cause a DDI (true positive rate). A corresponding analysis was done using HHEPs; kobs of 0.0015 minute-1 was statistically distinguishable from control, and the boundary was established at 0.006 minute-1 Values of kobs in HHEPs were almost always lower than those in HLMs. These findings offer a practical guide to the use of TDI data for CYP3A in early drug-discovery research. SIGNIFICANCE STATEMENT: Time-dependent inhibition of CYP3A is responsible for many drug interactions. In vitro assays are employed in early drug research to identify and remove CYP3A time-dependent inhibitors from further consideration. This analysis demonstrates suitable boundaries for inactivation rates to better delineate drug candidates for their potential to cause clinically significant drug interactions.

Moving beyond Binary Predictions of Human Drug-Induced Liver Injury (DILI) toward Contrasting Relative Risk Potential.

The hepatic risk matrix (HRM) was developed and used to differentiate lead clinical and back-up drug candidates against competitor/marketed drugs within the same pharmaceutical class for their potential to cause human drug-induced liver injury (DILI). The hybrid HRM scoring system blends physicochemical properties (Rule of Two Model: dose and lipophilicity or Partition Model: dose, ionization state, lipophilicity, and fractional carbon bond saturation) with common toxicity mechanisms (cytotoxicity, mitochondrial dysfunction, and bile salt export pump (BSEP) inhibition) that promote DILI. HRM scores are based on bracketed safety margins (<1, 1-10, 10-100, and >100× clinical Cmax,total). On the basis of well-established clinical safety experience of marketed/withdrawn drug candidates, the background analysis consists of 200 drugs from the Liver Toxicity Knowledge Base annotated as Most-DILI- (79), Less-DILI- (56), No-DILI- (47), and Ambiguous-DILI-concern (18) drugs. Scores were generated for over 21 internal and 7 external drug candidates discontinued for unacceptable incidence/magnitude of liver transaminase elevations during clinical trials or withdrawn for liver injury severity. Both hybrid scoring systems identified 70-80% Most-DILI-concern drugs, but more importantly, stratified successful/unsuccessful drug candidates for liver safety (incidence/severity of transaminase elevations and approved drug labels). Incorporating other mechanisms (reactive metabolite and cytotoxic metabolite generation and hepatic efflux transport inhibition, other than BSEP) to the HRM had minimal beneficial impact in DILI prediction/stratification. As is, the hybrid scoring system was positioned for portfolio assessments to contrast DILI risk potential of small molecule drug candidates in early clinical development. This stratified approach for DILI prediction aided decisions regarding drug candidate progression, follow-up mechanistic work, back-up selection, clinical dose selection, and due diligence assessments in favor of compounds with less implied clinical hepatotoxicity risk.

Enzalutamide and Apalutamide: In Vitro Chemical Reactivity Studies and Activity in a Mouse Drug Allergy Model.

Enzalutamide and apalutamide are two androgen receptor inhibitors approved for the treatment of castration-resistant prostate cancer (CRPC) and nonmetastatic castration-resistant prostate cancer (nmCRPC), respectively. Apalutamide is associated with an increased incidence of skin rash above the placebo groups in the SPARTAN trial in nmCRPC and in the TITAN trial in metastatic castration-sensitive prostate cancer patients. On the contrary, the rate of skin rash across all clinical trials (including PROSPER [nmCRPC]) for enzalutamide is similar to the placebo. We hypothesized that the apalutamide-associated increased skin rash in patients could be linked to a structural difference. The 2-cyanophenyl and dimethyl moieties in enzalutamide are substituted in apalutamide with 2-cyanopyridine and cyclobutyl, respectively. In our evaluations, the 2-cyanopyridine moiety of apalutamide was chemically reactive with the thiol nucleophile glutathione, resulting in rearranged thiazoline products. Radiolabeled apalutamide, but not radiolabeled enzalutamide, was shown to react with mouse and human plasma proteins. Thiol nucleophiles decreased the extent of covalent binding to the model protein bovine serum albumin, whereas amine and alcohol nucleophiles had no effect, suggesting reactivity with cysteine of proteins. Subcutaneous administration of apalutamide dose dependently increased lymphocyte cellularity in draining lymph nodes in a mouse drug allergy model (MDAM). Enzalutamide, and its known analogue RD162 in which the cyanophenyl was retained but the dimethyl was replaced by cyclobutyl, demonstrated substantially less covalent binding activity and negative results in the MDAM assay. Collectively, these data support the hypothesis that the 2-cyanopyridine moiety in apalutamide may react with cysteine in proteins forming haptens, which may trigger an immune response, as indicated by the activity of apalutamide in the MDAM assay, which in turn may be leading to increased potential for skin rash versus placebo in patients in the SPARTAN and TITAN clinical trials.

Role of Molybdenum-Containing Enzymes in the Biotransformation of the Novel Ghrelin Receptor Inverse Agonist PF-5190457: A Reverse Translational Bed-to-Bench Approach.

(R)-2-(2-methylimidazo[2,1-b]thiazol-6-yl)-1-(2-(5-(6-methylpyrimidin-4-yl)-2,3-dihydro-1H-inden-1-yl)-2,7-diazaspiro[3.5]nonan-7-yl)ethan-1-one (PF-5190457) was identified as a potent and selective inverse agonist of the ghrelin receptor [growth hormone secretagogue receptor 1a (GHS-R1a)]. The present translational bed-to-bench work characterizes the biotransformation of this compound in vivo and then further explores in vitro metabolism in fractions of human liver and primary hepatocytes. Following oral administration of PF-5190457 in a phase 1b clinical study, hydroxyl metabolites of the compound were observed, including one that had not been observed in previously performed human liver microsomal incubations. PF-6870961 was biosynthesized using liver cytosol, and the site of hydroxylation was shown to be on the pyrimidine using nuclear magnetic resonance spectroscopy. The aldehyde oxidase (AO) inhibitor raloxifene and the xanthine oxidase inhibitor febuxostat inhibited the formation of PF-6870961 in human liver cytosol, suggesting both enzymes were involved in the metabolism of the drug. However, greater inhibition was observed with raloxifene, indicating AO is a dominant enzyme in the biotransformation. The intrinsic clearance of the drug in human liver cytosol was estimated to be 0.002 ml/min per milligram protein. This study provides important novel information at three levels: 1) it provides additional new information on the recently developed novel compound PF-5190457, the first GHS-R1a blocker that has moved to development in humans; 2) it provides an example of a reverse translational approach where a discovery in humans was brought back, validated, and further investigated at the bench level; and 3) it demonstrates the importance of considering the molybdenum-containing oxidases during the development of new drug entities. SIGNIFICANCE STATEMENT: PF-5190457 is a novel ghrelin receptor inverse agonist that is currently undergoing clinical development for treatment of alcohol use disorder. PF-6870961, a major hydroxyl metabolite of the compound, was observed in human plasma, but was absent in human liver microsomal incubations. PF-6870961 was biosynthesized using liver cytosol, and the site of hydroxylation on the pyrimidine ring was characterized. Inhibitors of aldehyde oxidase and xanthine oxidase inhibited the formation of PF-6870961 in human liver cytosol, suggesting both enzymes were involved in the metabolism of the drug. This information is important for patient selection in subsequent clinical studies.

Emerging Models of Drug Metabolism, Transporters, and Toxicity.

This commentary summarizes expert mini-reviews and original research articles that have been assembled in a special issue on novel models of drug metabolism and disposition. The special issue consists of research articles or reviews on novel static or micro-flow based models of the intestine, liver, eye, and kidney. This issue reviews static intestinal systems like mucosal scrapings and cryopreserved intestinal enterocytes, as well as novel bioengineered or chemically engineered intestinal models derived from primary human tissue, iPSCs, enteroids, and crypts. Experts have reviewed hepatic systems like cryopermeabilized Metmax hepatocytes and longer term, hepatocyte coculture system from HµREL, yielding in vivo-like primary and secondary drug metabolite profiles. Additional liver models, including micropattern hepatocyte coculture, 3D liver spheroids, and microflow systems, applicable to the study of drug disposition and toxicology have also been reviewed. In this commentary, we have outlined expert opinions and current efforts on hepatic- and nephrotoxicity models. Ocular disposition models including corneal permeability models have been included within this special issue. This commentary provides a summary of in vivo mini-reviews of the issue, which have discussed the applications and drawbacks of pig and humanized mice models of P450, UGT, and rat organic anionic transporting polypeptide 1a4. While not extensively reviewed, novel positron emissions tomography imaging-based approaches to study the distribution of xenobiotics have been highlighted. This commentary also outlines in vitro and in vivo models of drug metabolism derived from breakthrough genetic, chromosomal, and tissue engineering techniques. The commentary concludes by providing a futuristic view of the novel models discussed in this issue.

Trend Analysis of a Database of Intravenous Pharmacokinetic Parameters in Humans for 1352 Drug Compounds.

We report a trend analysis of human intravenous pharmacokinetic data on a data set of 1352 drugs. The aim in building this data set and its detailed analysis was to provide, as in the previous case published in 2008, an extended, robust, and accurate resource that could be applied by drug metabolism, clinical pharmacology, and medicinal chemistry scientists to a variety of scaling approaches. All in vivo data were obtained or derived from original references, either through the literature or regulatory agency reports, exclusively from studies utilizing intravenous administration. Plasma protein binding data were collected from other available sources to supplement these pharmacokinetic data. These parameters were analyzed concurrently with a range of physicochemical properties, and resultant trends and patterns within the data are presented. In addition, the date of first disclosure of each molecule was reported and the potential "temporal" impact on data trends was analyzed. The findings reported here are consistent with earlier described trends between pharmacokinetic behavior and physicochemical properties. Furthermore, the availability of a large data set of pharmacokinetic data in humans will be important to further pursue analyses of physicochemical properties, trends, and modeling efforts and should propel our deeper understanding (especially in terms of clearance) of the absorption, distribution, metabolism, and excretion behavior of drug compounds.