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 utilized for reaction phenotyping. In this study, we characterized icotinib, a cyclized analogue of erlotinib, as a potent TDI of AO - inactivating human liver cytosolic zoniporide 2-oxidation equipotently with erlotinib with a k inact/K I ratio of 463 and 501 min-1mM-1 , respectively. Moreover, icotinib also exhibits selectivity against P450 and elicits significantly weaker inhibition against human liver microsomal UGT1A1/3 as compared to 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 to 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.

A Second-Generation Oral SARS-CoV-2 Main Protease Inhibitor Clinical Candidate for the Treatment of COVID-19.

Despite the record-breaking discovery, development and approval of vaccines and antiviral therapeutics such as Paxlovid, coronavirus disease 2019 (COVID-19) remained the fourth leading cause of death in the world and third highest in the United States in 2022. Here, we report the discovery and characterization of PF-07817883, a second-generation, orally bioavailable, SARS-CoV-2 main protease inhibitor with improved metabolic stability versus nirmatrelvir, the antiviral component of the ritonavir-boosted therapy Paxlovid. We demonstrate the in vitro pan-human coronavirus antiviral activity and off-target selectivity profile of PF-07817883. PF-07817883 also demonstrated oral efficacy in a mouse-adapted SARS-CoV-2 model at plasma concentrations equivalent to nirmatrelvir. The preclinical in vivo pharmacokinetics and metabolism studies in human matrices are suggestive of improved oral pharmacokinetics for PF-07817883 in humans, relative to nirmatrelvir. In vitro inhibition/induction studies against major human drug metabolizing enzymes/transporters suggest a low potential for perpetrator drug-drug interactions upon single-agent use of PF-07817883.

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.

A Novel Milli-fluidic Liver Tissue Chip with Continuous Recirculation for Predictive Pharmacokinetics Applications.

A crucial step in lead selection during drug development is accurate estimation and optimization of hepatic clearance using in vitro methods. However, current methods are limited by factors such as lack of physiological relevance, short culture/incubation times that are not consistent with drug exposure patterns in patients, use of drug absorbing materials, and evaporation during long-term incubation. To address these technological needs, we developed a novel milli-fluidic human liver tissue chip (LTC) that was designed with continuous media recirculation and optimized for hepatic cultures using human primary hepatocytes. Here, we characterized the LTC using a series of physiologically relevant metrics and test compounds to demonstrate that we could accurately predict the PK of both low- and high-clearance compounds. The non-biological characterization indicated that the cyclic olefin copolymer (COC)-based LTC exhibited negligible evaporation and minimal non-specific binding of drugs of varying ionic states and lipophilicity. Biologically, the LTC exhibited functional and polarized hepatic culture with sustained metabolic CYP activity for at least 15 days. This long-term culture was then used for drug clearance studies for low- and high-clearance compounds for at least 12 days, and clearance was estimated for a range of compounds with high in vitro-in vivo correlation (IVIVC). We also demonstrated that LTC can be induced by rifampicin, and the culture age had insignificant effect on depletion kinetic and predicted clearance value. Thus, we used advances in bioengineering to develop a novel purpose-built platform with high reproducibility and minimal variability to address unmet needs for PK applications.

The Importance of Tracking "Missing" Metabolites: How and Why?

Technologies currently employed to find and identify drug metabolites in complex biological matrices generally yield results that offer a comprehensive picture of the drug metabolite profile. However, drug metabolites can be missed or are captured only late in the drug development process. This could be due to a variety of factors, such as metabolism that results in partial loss of the molecule, covalent bonding to macromolecules, the drug being metabolized in specific human tissues, or poor ionization in a mass spectrometer. These scenarios often draw a great deal of attention from chemistry, safety assessment, and pharmacology. This review will summarize scenarios of missing metabolites, why they are missing, and associated uncovering strategies from deeper investigations. Uncovering previously missed metabolites can have ramifications in drug development with toxicological and pharmacological consequences, and knowledge of these can help in the design of new drugs.

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.

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.

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.

Metabolism and Excretion of Nirmatrelvir in Humans Using Quantitative Fluorine Nuclear Magnetic Resonance Spectroscopy: A Novel Approach for Accelerating Drug Development.

Typically human absorption, distribution, metabolism, and excretion (ADME) studies are executed using radiolabeled (e.g., carbon-14) material, the synthesis of which is a time-consuming activity. In this study, we were able to assess the metabolism and excretion of unlabeled nirmatrelvir (PF-07321332) within the first-in-human study via a novel application of quantitative fluorine (19 F) nuclear magnetic resonance (NMR) spectroscopy in place of a standard radiolabel ADME study. Six healthy participants received a single 300-mg oral dose of nirmatrelvir (in combination with ritonavir), and excreta were collected up to 10 days. Virtually all drug-related material was recovered within 5 days, and mass balance was achieved with 84.9 ± 8.9% (range = 70.7-95.5%) of the administered dose recovered in urine and feces. The excretion of fluorine-containing material in urine and feces was 47.0% and 33.7%, respectively. Unchanged nirmatrelvir represented 82.5% of the normalized drug-related material with a carboxylic acid metabolite M5, derived from hydrolysis of the P2 amide bond, present at 12.1% of dose. Nirmatrelvir was the only drug-related entity observed in plasma. Approximately 4.2% of the dose was excreted as metabolite M8 (measured by liquid chromatography-mass spectrometry), which was 19 F NMR silent due to hydrolysis of the trifluoroacetamide moiety. Hydrolysis of nirmatrelvir to M5 and M8 was shown to occur in cultures of human gut microflora. This successful demonstration of quantitative 19 F NMR spectroscopy to establish the mass-balance, excretion, and metabolic profile of nirmatrelvir offers an advantageous means to execute human ADME studies for fluorine-containing compounds early in drug development.

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.

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 oral SARS-CoV-2 Mpro inhibitor clinical candidate for the treatment of COVID-19.

The worldwide outbreak of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global pandemic. Alongside vaccines, antiviral therapeutics are an important part of the healthcare response to countering the ongoing threat presented by COVID-19. Here, we report the discovery and characterization of PF-07321332, an orally bioavailable SARS-CoV-2 main protease inhibitor with in vitro pan-human coronavirus antiviral activity and excellent off-target selectivity and in vivo safety profiles. PF-07321332 has demonstrated oral activity in a mouse-adapted SARS-CoV-2 model and has achieved oral plasma concentrations exceeding the in vitro antiviral cell potency in a phase 1 clinical trial in healthy human participants.

Preclinical characterization of an intravenous coronavirus 3CL protease inhibitor for the potential treatment of COVID19.

COVID-19 caused by the SARS-CoV-2 virus has become a global pandemic. 3CL protease is a virally encoded protein that is essential across a broad spectrum of coronaviruses with no close human analogs. PF-00835231, a 3CL protease inhibitor, has exhibited potent in vitro antiviral activity against SARS-CoV-2 as a single agent. Here we report, the design and characterization of a phosphate prodrug PF-07304814 to enable the delivery and projected sustained systemic exposure in human of PF-00835231 to inhibit coronavirus family 3CL protease activity with selectivity over human host protease targets. Furthermore, we show that PF-00835231 has additive/synergistic activity in combination with remdesivir. We present the ADME, safety, in vitro, and in vivo antiviral activity data that supports the clinical evaluation of PF-07304814 as a potential COVID-19 treatment.

Consideration of the Unbound Drug Concentration in Enzyme Kinetics.

The study of enzyme kinetics in drug metabolism involves assessment of rates of metabolism and inhibitory potencies over a suitable concentration range. In all but the very simplest in vitro system, these drug concentrations can be influenced by a variety of nonspecific binding reservoirs that can reduce the available concentration to the enzyme system(s) under investigation. As a consequence, the apparent kinetic parameters, such as Km or Ki, that are derived can deviate from the true values. There are a number of sources of these nonspecific binding depots or barriers, including membrane permeation and partitioning, plasma or serum protein binding, and incubational binding. In the latter case, this includes binding to the assay apparatus as well as biological depots, depending on the characteristics of the in vitro matrix being used. Given the wide array of subcellular, cellular, and recombinant enzyme systems utilized in drug metabolism, each of these has different components which can influence the free drug concentration. The physicochemical properties of the test compound are also paramount in determining the influential factors in any deviation between true and apparent kinetic behavior. This chapter describes the underlying mechanisms determining the free drug concentration in vitro and how these factors can be accounted for in drug metabolism studies, illustrated with case studies from the literature.

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.