Mechanistic insights from comparing intrinsic clearance values between human liver microsomes and hepatocytes to guide drug design

Species-Dependent Metabolism of a Covalent nsP2 Protease Inhibitor with In Vivo Antialphaviral Activity

RA-0002034 (1) is a potent covalent inhibitor targeting the nsP2 cysteine protease. The species-dependent pharmacokinetics and metabolism of 1 were investigated to evaluate its therapeutic potential. Pharmacokinetic profiling revealed rapid clearance in mice, predominantly mediated by glutathione S-transferase (GST)-catalyzed conjugation. This metabolic liability contrasted with slower clearance observed in human hepatocytes and preclinical species, such as rats, dogs, and monkeys. Cross-species studies confirmed the dominance of GST-driven metabolism in mice, whereas oxidative pathways were more pronounced in dogs. Despite rapid systemic clearance, 1 achieved antiviral efficacy in mice, reducing chikungunya (CHIKV) viral loads in multiple tissues. These cross-species pharmacokinetic and metabolism studies support the continued evaluation of 1 as a potential antialphaviral therapeutic to further define the contribution of hepatic and non-hepatic GST metabolism to its clearance in humans.

In Vitro and In Vivo Pharmacokinetic Characterization of 7-Hydroxymitragynine, an Active Metabolite of Mitragynine, in Sprague-Dawley Rats

BACKGROUND AND OBJECTIVES

Kratom, a Southeast Asian tree, has been researched for its potential as a therapeutic for substance use disorders. The most abundant alkaloid in kratom, mitragynine, is being investigated individually for opioid use disorder. However, the active metabolite of mitragynine,7-hydroxymitragynine (7-HMG) has raised concerns because of its high binding affinity to μ-opioid receptors and abuse potential. This study examines various pharmacokinetic parameters of 7-HMG in both in vitro and in vivo models.

METHODS

In vitro pharmacokinetic properties were investigated using human colorectal adenocarcinoma cell monolayers (Caco-2 cells), rat plasma, rat liver microsomes, and rat hepatocytes to determine the permeability, plasma protein binding, and microsomal and hepatocyte stability of 7-HMG, respectively. Oral and intravenous (IV) pharmacokinetic studies of 7-HMG were performed in male Sprague-Dawley rats.

RESULTS

7-HMG exhibits high permeability across Caco-2 cells (19.7 ± 1.0 × 10-6 cm/s), with a relatively low plasma protein binding of 73.1 ± 0.6% to mitragynine. The hepatic extraction ratio was 0.3 and 0.6 in rat liver microsomes and hepatocytes, respectively, indicating that 7-HMG is an intermediate hepatic extraction compound. Oral and IV pharmacokinetic studies were performed in male rats. The volume of distribution was 2.7 ± 0.4 l/kg and the clearance was 4.0 ± 0.3 l/h/kg after IV administration. After oral dosing (5 mg/kg), a Cmax of 28.5 ± 5.0 ng/ml and Tmax of 0.3 ± 0.1 h were observed. However, the oral bioavailability of 7-HMG was only 2.7 ± 0.3%. The results demonstrate 7-HMG is rapidly absorbed but has low oral bioavailability. Mitragynine pseudoindoxyl (MGPI) is a metabolite of 7-HMG that is a more potent µ-opioid agonist than 7-HMG. The parent-to-metabolite ratio for MGPI following IV 7-HMG administration was 0.5 ± 0.1%, indicating very limited systemic exposure to MGPI.

CONCLUSIONS

This study reports the pharmacokinetic parameters of 7-HMG to help with the development of mitragynine, as a therapeutic.

Radiosynthesis and evaluation of novel 18F labeled PET ligands for imaging monoacylglycerol lipase

Monoacylglycerol lipase (MAGL) is a 33 kDa cytosolic serine hydrolase that is widely distributed in the central nervous system and peripheral tissues. MAGL hydrolyzes monoacylglycerols into fatty acids and glycerol, playing a crucial role in endocannabinoid degradation. Inhibition of MAGL in the brain elevates levels of 2-arachidonoylglycerol and leads to decreased pro-inflammatory prostaglandin and thromboxane production. As such, MAGL is considered a potential target for treating neuropsychiatric disorders, metabolic syndromes, and cancer. Based on a novel spirocyclic system, we synthesized two fluorinated carbamate scaffolds as reversible MAGL inhibitors (epimers: (R)-6, IC50 = 18.6 nM and (S)-6, IC50 = 1.6 nM). In vitro autoradiography studies of [18F](R)-6 (codenamed [18F]MAGL-2304) and [18F](S)-6 (codenamed [18F]MAGL-2305) demonstrated heterogeneous distribution and specific binding affinity to MAGL-rich brain regions. Autoradiography with MAGL knockout mouse brain tissues confirmed the binding specificity of [18F](S)-6. Dynamic PET imaging studies revealed that [18F](S)-6 exhibited limited brain uptake and homogenous distribution in rat brains. In vivo P-gp inhibition enhanced [18F](S)-6 uptake in the brain, suggesting that [18F](S)-6 constitutes a P-gp efflux substrate. This research could provide new directions in the design of MAGL PET ligands that are based on spirocyclic scaffolds.

Species Dependent Metabolism of a Covalent nsP2 Protease Inhibitor with in Vivo Anti-alphaviral Activity

RA-0002034 (1) is a potent covalent inhibitor targeting the alphavirus nsP2 cysteine protease. The species-dependent pharmacokinetics and metabolism of 1 were investigated to evaluate its therapeutic potential. Pharmacokinetic profiling revealed rapid clearance in mice, predominantly mediated by glutathione S-transferase (GST)-catalyzed conjugation. This metabolic liability contrasted with slower clearance observed in human hepatocytes and preclinical species such as rats, dogs, and monkeys. Cross-species studies confirmed the dominance of GST-driven metabolism in mice, whereas oxidative pathways were more pronounced in dogs. Despite rapid systemic clearance, 1 achieved antiviral efficacy in mice, reducing CHIKV viral loads in multiple tissues. Initial estimations of human hepatic clearance and half-life extrapolated from animal data indicate that b.i.d. dosing of 1 will be possible to maintain concentrations sufficient for antiviral activity in humans. These cross-species pharmacokinetic and metabolism studies support the continued evaluation of 1 as a promising anti-alphaviral therapeutic.

Utility of physiologically based pharmacokinetic modeling in predicting and characterizing clinical drug interactions

Physiologically based pharmacokinetic (PBPK) modeling is a mechanistic dynamic modeling approach that can be used to predict or retrospectively describe changes in drug exposure due to drug-drug interactions (DDIs). With advancements in commercially available PBPK software, PBPK DDI modeling has become a mainstream approach from early drug discovery through to late-stage drug development and is often used to support regulatory packages for new drug applications. This Minireview will briefly describe the approaches to predicting DDI using PBPK and static modeling approaches, the basic model structures and features inherent to PBPK DDI models, and key examples where PBPK DDI models have been used to describe complex DDI mechanisms. Future directions aimed at using PBPK models to characterize transporter-mediated DDI, predict DDI in special populations, and assess the DDI potential of protein therapeutics will be discussed. A summary of the 209 PBPK DDI examples published to date in 2023 will be provided. Overall, current data and trends suggest a continued role for PBPK models in the characterization and prediction of DDI for therapeutic molecules. SIGNIFICANCE STATEMENT: Physiologically based pharmacokinetic (PBPK) models have been a key tool in the characterization of various pharmacokinetic phenomena, including drug-drug interactions. This Minireview will highlight recent advancements and publications around physiologically based pharmacokinetic drug-drug interaction modeling, an important area of drug discovery and development research in light of the increasing prevalence of polypharmacology in clinical settings.

Improved N-phenylpyrrolamide inhibitors of DNA gyrase as antibacterial agents for high-priority bacterial strains

In this work, we describe an improved series of N-phenylpyrrolamide inhibitors that exhibit potent activity against DNA gyrase and are highly effective against high-priority gram-positive bacteria. The most potent compounds show low nanomolar IC50 values against Escherichia coli DNA gyrase, and in addition, compound 7c also inhibits E. coli topoisomerase IV in the nanomolar concentration range, making it a promising candidate for the development of potent dual inhibitors for these enzymes. All tested compounds show high selectivity towards the human isoform DNA topoisomerase IIα. Compounds 6a, 6d, 6e and 6f show MIC values between 0.031 and 0.0625 μg/mL against vancomycin-intermediate S. aureus (VISA) and Enterococcus faecalis strains. Compound 6g shows an inhibitory effect against the methicillin-resistant S. aureus strain (MRSA) with a MIC of 0.0625 μg/mL and against the E. faecalis strain with a MIC of 0.125 μg/mL. In a time-kill assay, compound 6d showed a dose-dependent bactericidal effect on the MRSA strain and achieved bactericidal activity at 8 × MIC after 8 h. The duration of the post-antibiotic effect (PAE) on the MRSA strain for compound 6d was 2 h, which corresponds to the PAE duration for ciprofloxacin. The compounds were not cytotoxic at effective concentrations, as determined in an MTS assay on the MCF-7 breast cancer cell line.

Determination of arbutin in vitro and in vivo by LC-MS/MS: Pre-clinical evaluation of natural product arbutin for its early medicinal properties

ETHNOPHARMACOLOGICAL RELEVANCE

Arbutin is a naturally occurring glucoside extracted from plants, known for its antioxidant and tyrosinase inhibiting properties. It is widely used in cosmetic and pharmaceutical industries. With in-depth study of arbutin, its application in disease treatment is expanding, presenting promising development prospects. However, reports on the metabolic stability, plasma protein binding rate, and pharmacokinetic properties of arbutin are scarce.

AIM OF THE STUDY

The aim of this study is to enrich the data of metabolic stability and pharmacokinetics of arbutin through the early pre-clinical evaluation, thereby providing some experimental basis for advancing arbutin into clinical research.

MATERIALS AND METHODS

We developed an efficient and rapid liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for determining arbutin in plasma. We investigated the metabolic and pharmacokinetic properties of arbutin through in vitro metabolism assay, cytochrome enzymes P450 (CYP450) inhibition studies, plasma protein binding rate analysis, Caco-2 cell permeability tests, and rat pharmacokinetics to understand its in vivo performance.

RESULTS

In vitro studies show that arbutin is stable, albeit with some species differences. It exhibits low plasma protein binding (35.35 ± 11.03% ∼ 40.25 ± 2.47%), low lipophilicity, low permeability, short half-life (0.42 ± 0.30 h) and high oral bioavailability (65 ± 11.6%). Arbutin is primarily found in the liver and kidneys and is eliminated in the urine. It does not significantly inhibit CYP450 up to 10 μM, suggesting a low potential for drug interactions. Futhermore, preliminary toxicological experiments indicate arbutin's safety, supporting its potential as a therapeutic agent.

CONCLUSION

This study provides a comprehensive analysis the drug metabolism and pharmacokinetics (DMPK) of arbutin, enriching our understanding of its metabolism stability and pharmacokinetics properties, It establishes a foundation for further structural optimization, pharmacological studies, and the clinical development of arbutin.

An Integrated Hepatocyte Stability Assay for Simultaneous Metabolic Stability Assessment and Metabolite Profiling

The determination of metabolic stability is critical for drug discovery programs, allowing for the optimization of chemical entities and compound prioritization. As such, it is common to perform high-volume in vitro metabolic stability experiments early in the lead optimization process to understand metabolic liabilities. Additional metabolite identification experiments are subsequently performed for a more comprehensive understanding of the metabolic clearance routes to aid medicinal chemists in the structural design of compounds. Collectively, these experiments require extensive sample preparation and a substantial amount of time and resources. To overcome the challenges, a high-throughput integrated assay for simultaneous hepatocyte metabolic stability assessment and metabolite profiling was developed. This assay platform consists of four parts: 1) an automated liquid-handling system for sample preparation and incubation, 2) a liquid chromatography and high-resolution mass spectrometry-based system to simultaneously monitor the parent compound depletion and metabolite formation, 3) an automated data analysis and report system for hepatic clearance assessment; and 4) streamlined autobatch processing for software-based metabolite profiling. The assay platform was evaluated using eight control compounds with various metabolic rates and biotransformation routes in hepatocytes across three species. Multiple sample preparation and data analysis steps were evaluated and validated for accuracy, repeatability, and metabolite coverage. The combined utility of an automated liquid-handling instrument, a high-resolution mass spectrometer, and multiple streamlined data processing software improves the process of these highly demanding screening assays and allows for simultaneous determination of metabolic stability and metabolite profiles for more efficient lead optimization during early drug discovery. SIGNIFICANCE STATEMENT: Metabolic stability assessment and metabolite profiling are pivotal in drug discovery to fully comprehend metabolic liabilities for chemical entity optimization and lead selection. Process of these assays can be repetitive and resource demanding. Here, we developed an integrated hepatocyte stability assay that combines automation, high-resolution mass spectrometers, and batch-processing software to improve and combine the workflow of these assays. The integrated approach allows simultaneous metabolic stability assessment and metabolite profiling, significantly accelerating screening and lead optimization in a resource-effective manner.

Characterization and Applications of Permeabilized Hepatocytes in Drug Discovery

Hepatocytes are one of the most physiologically relevant in vitro liver systems for human translation of clearance and drug-drug interactions (DDI). However, the cell membranes of hepatocytes can limit the entry of certain compounds into the cells for metabolism and DDI. Passive permeability through hepatocytes can be different in vitro and in vivo, which complicates the human translation. Permeabilized hepatocytes offer a useful tool to probe mechanistic understanding of permeability-limited metabolism and DDI. Incubation with saponin of 0.01% at 0.5 million cells/mL and 0.05% at 5 million cells/mL for 5 min at 37°C completely permeabilized the plasma membrane of hepatocytes, while leaving the membranes of subcellular organelles intact. Permeabilized hepatocytes maintained similar enzymatic activity as intact unpermeabilized hepatocytes and can be stored at -80°C for at least 7 months. This approach reduces costs by preserving leftover hepatocytes. The relatively low levels of saponin in permeabilized hepatocytes had no significant impact on the enzymatic activity. As the cytosolic contents leak out from permeabilized hepatocytes, cofactors need to be added to enable metabolic reactions. Cytosolic enzymes will no longer be present if the media are removed after cells are permeabilized. Hence permeabilized hepatocytes with and without media removal may potentially enable reaction phenotyping of cytosolic enzymes. Although permeabilized hepatocytes work similarly as human liver microsomes and S9 fractions experimentally requiring addition of cofactors, they behave more like hepatocytes maintaining enzymatic activities for over 4 h. Permeabilized hepatocytes are a great addition to the drug metabolism toolbox to provide mechanistic insights.

Development of Potent and Selective Monoacylglycerol Lipase Inhibitors. SARs, Structural Analysis, and Biological Characterization

New potent, selective monoacylglycerol lipase (MAGL) inhibitors based on the azetidin-2-one scaffold ((±)-5a-v, (±)-6a-j, and (±)-7a-d) were developed as irreversible ligands, as demonstrated by enzymatic and crystallographic studies for (±)-5d, (±)-5l, and (±)-5r. X-ray analyses combined with extensive computational studies allowed us to clarify the binding mode of the compounds. 5v was identified as selective for MAGL when compared with other serine hydrolases. Solubility, in vitro metabolic stability, cytotoxicity, and absence of mutagenicity were determined for selected analogues. The most promising compounds ((±)-5c, (±)-5d, and (±)-5v) were used for in vivo studies in mice, showing a decrease in MAGL activity and increased 2-arachidonoyl-sn-glycerol levels in forebrain tissue. In particular, 5v is characterized by a high eudysmic ratio and (3R,4S)-5v is one of the most potent irreversible inhibitors of h/mMAGL identified thus far. These results suggest that the new MAGL inhibitors have therapeutic potential for different central and peripheral pathologies.

Discovery of Orally Available and Brain Penetrant AEP Inhibitors

Alzheimer's Disease (AD) is the most widespread form of dementia, with one of the pathological hallmarks being the formation of neurofibrillary tangles (NFTs). These tangles consist of phosphorylated Tau fragments. Asparagine endopeptidase (AEP) is a key Tau cleaving enzyme that generates aggregation-prone Tau fragments. Inhibition of AEP to reduce the level of toxic Tau fragment formation could represent a promising therapeutic strategy. Here, we report the first orthosteric, selective, orally bioavailable, and brain penetrant inhibitors with an irreversible binding mode. We outline the development of the series starting from reversible molecules and demonstrate the link between inhibition of AEP and reduction of Tau N368 fragment both in vitro and in vivo.

The Comparison of Machine Learning and Mechanistic In Vitro-In Vivo Extrapolation Models for the Prediction of Human Intrinsic Clearance

Accurate prediction of human pharmacokinetics (PK) remains one of the key objectives of drug metabolism and PK (DMPK) scientists in drug discovery projects. This is typically performed by using in vitro-in vivo extrapolation (IVIVE) based on mechanistic PK models. In recent years, machine learning (ML), with its ability to harness patterns from previous outcomes to predict future events, has gained increased popularity in application to absorption, distribution, metabolism, and excretion (ADME) sciences. This study compares the performance of various ML and mechanistic models for the prediction of human IV clearance for a large (645) set of diverse compounds with literature human IV PK data, as well as measured relevant in vitro end points. ML models were built using multiple approaches for the descriptors: (1) calculated physical properties and structural descriptors based on chemical structure alone (classical QSAR/QSPR); (2) in vitro measured inputs only with no structure-based descriptors (ML IVIVE); and (3) in silico ML IVIVE using in silico model predictions for the in vitro inputs. For the mechanistic models, well-stirred and parallel-tube liver models were considered with and without the use of empirical scaling factors and with and without renal clearance. The best ML model for the prediction of in vivo human intrinsic clearance (CLint) was an in vitro ML IVIVE model using only six in vitro inputs with an average absolute fold error (AAFE) of 2.5. The best mechanistic model used the parallel-tube liver model, with empirical scaling factors resulting in an AAFE of 2.8. The corresponding mechanistic model with full in silico inputs achieved an AAFE of 3.3. These relative performances of the models were confirmed with the prediction of 16 Pfizer drug candidates that were not part of the original data set. Results show that ML IVIVE models are comparable to or superior to their best mechanistic counterparts. We also show that ML IVIVE models can be used to derive insights into factors for the improvement of mechanistic PK prediction.

Exploring the Boundaries for In Vitro-In Vivo Extrapolation: Use of Isolated Rat Hepatocytes in Co-culture and Impact of Albumin Binding Properties in the Prediction of Clearance of Various Drug Types

Prediction of hepatic clearance of drugs (via uptake or metabolism) from in vitro systems continues to be problematic, particularly when plasma protein binding is high. The following work explores simultaneous assessment of both clearance processes, focusing on a commercial hepatocyte-fibroblast co-culture system (HμREL) over a 24-hour period using six probe drugs (ranging in metabolic and transporter clearance and low-to-high plasma protein binding). A rat hepatocyte co-culture assay was established using drug depletion (measuring both medium and total concentrations) and cell uptake kinetic analysis, both in the presence and absence of plasma protein (1% bovine serum albumin). Secretion of endogenous albumin was monitored as a marker of viability, and this reached 0.004% in incubations (at a rate similar to in vivo synthesis). Binding to stromal cells was substantial and required appropriate correction factors. Drug concentration-time courses were analyzed both by conventional methods and a mechanistic cell model prior to in vivo extrapolation. Clearance assayed by drug depletion in conventional suspended rat hepatocytes provided a benchmark to evaluate co-culture value. Addition of albumin appeared to improve predictions for some compounds (where fraction unbound in the medium is less than 0.1); however, for high-binding drugs, albumin significantly limited quantification and thus predictions. Overall, these results highlight ongoing challenges concerning in vitro hepatocyte system complexity and limitations of practical expediency. Considering this, more reliable measurement of hepatically cleared compounds seems possible through judicious use of available hepatocyte systems, including co-culture systems, as described herein; this would include those compounds with low metabolic turnover but high active uptake clearance. SIGNIFICANCE STATEMENT: Co-culture systems offer a more advanced tool than standard hepatocytes, with the ability to be cultured for longer periods of time, yet their potential as an in vitro tool has not been extensively assessed. We evaluate the strengths and limitations of the HμREL system using six drugs representing various metabolic and transporter-mediated clearance pathways with various degrees of albumin binding. Studies in the presence/absence of albumin allow in vitro-in vivo extrapolation and a framework to maximize their utility.

DeepDelta: predicting ADMET improvements of molecular derivatives with deep learning

Established molecular machine learning models process individual molecules as inputs to predict their biological, chemical, or physical properties. However, such algorithms require large datasets and have not been optimized to predict property differences between molecules, limiting their ability to learn from smaller datasets and to directly compare the anticipated properties of two molecules. Many drug and material development tasks would benefit from an algorithm that can directly compare two molecules to guide molecular optimization and prioritization, especially for tasks with limited available data. Here, we develop DeepDelta, a pairwise deep learning approach that processes two molecules simultaneously and learns to predict property differences between two molecules from small datasets. On 10 ADMET benchmark tasks, our DeepDelta approach significantly outperforms two established molecular machine learning algorithms, the directed message passing neural network (D-MPNN) ChemProp and Random Forest using radial fingerprints, for 70% of benchmarks in terms of Pearson's r, 60% of benchmarks in terms of mean absolute error (MAE), and all external test sets for both Pearson's r and MAE. We further analyze our performance and find that DeepDelta is particularly outperforming established approaches at predicting large differences in molecular properties and can perform scaffold hopping. Furthermore, we derive mathematically fundamental computational tests of our models based on mathematical invariants and show that compliance to these tests correlates with overall model performance - providing an innovative, unsupervised, and easily computable measure of expected model performance and applicability. Taken together, DeepDelta provides an accurate approach to predict molecular property differences by directly training on molecular pairs and their property differences to further support fidelity and transparency in molecular optimization for drug development and the chemical sciences.

Optimization of 3-Cyano-7-cyclopropylamino-pyrazolo[1,5-a]pyrimidines toward the Development of an In Vivo Chemical Probe for CSNK2A

3-Cyano-7-cyclopropylamino-pyrazolo[1,5-a]pyrimidines, including the chemical probe SGC-CK2-1, are potent and selective inhibitors of CSNK2A in cells but have limited utility in animal models due to their poor pharmacokinetic properties. While developing analogues with reduced intrinsic clearance and the potential for sustained exposure in mice, we discovered that phase II conjugation by GST enzymes was a major metabolic transformation in hepatocytes. A protocol for codosing with ethacrynic acid, a covalent reversible GST inhibitor, was developed to improve the exposure of analogue 2h in mice. A double codosing protocol, using a combination of ethacrynic acid and irreversible P450 inhibitor 1-aminobenzotriazole, increased the blood level of 2h by 40-fold at a 5 h time point.

Structure-Property Optimization of a Series of Imidazopyridines for Visceral Leishmaniasis

Leishmaniasis is a collection of diseases caused by more than 20 Leishmania parasite species that manifest as either visceral, cutaneous, or mucocutaneous leishmaniasis. Despite the significant mortality and morbidity associated with leishmaniasis, it remains a neglected tropical disease. Existing treatments have variable efficacy, significant toxicity, rising resistance, and limited oral bioavailability, which necessitates the development of novel and affordable therapeutics. Here, we report on the continued optimization of a series of imidazopyridines for visceral leishmaniasis and a scaffold hop to a series of substituted 2-(pyridin-2-yl)-6,7-dihydro-5H-pyrrolo[1,2-a]imidazoles with improved absorption, distribution, metabolism, and elimination properties.

Optimization of 3-Cyano-7-cyclopropylamino-pyrazolo[1,5-a]pyrimidines Toward the Development of an In Vivo Chemical Probe for CSNK2A

3-cyano-7-cyclopropylamino-pyrazolo[1,5-a]pyrimidines, including the chemical probe SGC-CK2-1, are potent and selective inhibitors of CSNK2A in cells but have limited utility in animal models due to their poor pharmacokinetic properties. While developing analogs with reduced intrinsic clearance and the potential for sustained exposure in mice, we discovered that Phase II conjugation by GST enzymes was a major metabolic transformation in hepatocytes. A protocol for co-dosing with ethacrynic acid, a covalent reversible GST inhibitor, was developed to improve the exposure of analog 2h in mice. A double co-dosing protocol, using a combination of ethacrynic acid and irreversible P450 inhibitor 1-aminobenzotriazole increased the blood level of 2h by 40-fold at a 5 h time point.

The Disconnect in Intrinsic Clearance Determined in Human Hepatocytes and Liver Microsomes Results from Divergent Cytochrome P450 Activities

Candidate drugs may exhibit higher unbound intrinsic clearances (CLint,u) in human liver microsomes (HLMs) relative to human hepatocytes (HHs), posing a challenge as to which value is more predictive of in vivo clearance (CL). This work was aimed at better understanding the mechanism(s) underlying this 'HLM:HH disconnect' via examination of previous explanations, including passive permeability limited CL or cofactor exhaustion in hepatocytes. A series of structurally related, passively permeable (Papps > 5 × 10-6 cm/s), 5-azaquinazolines were studied in different liver fractions, and metabolic rates and routes were determined. A subset of these compounds demonstrated a significant HLM:HH (CLint,u ratio 2-26) disconnect. Compounds were metabolized via combinations of liver cytosol aldehyde oxidase (AO), microsomal cytochrome P450 (CYP) and flavin monooxygenase (FMO). For this series, the lack of concordance between CLint,u determined in HLM and HH contrasted with an excellent correlation of AO dependent CLint,u determined in human liver cytosol[Formula: see text], r2 = 0.95, P < 0.0001). The HLM:HH disconnect for both 5-azaquinazolines and midazolam was as a result of significantly higher CYP activity in HLM and lysed HH fortified with exogenous NADPH relative to intact HH. Moreover, for the 5-azaquinazolines, the maintenance of cytosolic AO and NADPH-dependent FMO activity in HH, relative to CYP, supports the conclusion that neither substrate permeability nor intracellular NADPH for hepatocytes were limiting CLint,u Further studies are required to identify the underlying cause of the lower CYP activities in HH relative to HLM and lysed hepatocytes in the presence of exogenous NADPH. SIGNIFICANCE STATEMENT: Candidate drugs may exhibit higher intrinsic clearance in human liver microsomes relative to human hepatocytes, posing a challenge as to which value is predictive of in vivo clearance. This work demonstrates that the difference in activity determined in liver fractions results from divergent cytochrome P450 but not aldehyde oxidase or flavin monooxygenase activity. This is inconsistent with explanations including substrate permeability limitations or cofactor exhaustion and should inform the focus of further studies to understand this cytochrome P450 specific disconnect phenomenon.

Assessing Boron-Pleuromutilin AN11251 for the Development of Antibacterial Agents

Pleuromutilins are a group of antibiotics derived from the naturally occurring compound. The recent approval of lefamulin for both intravenous and oral doses in humans to treat community-acquired bacterial pneumonia has prompted investigations in modifying the structure to broaden the antibacterial spectrum, enhance the activity, and improve the pharmacokinetic properties. AN11251 is a C(14)-functionalized pleuromutilin with a boron-containing heterocycle substructure. It was demonstrated to be an anti-Wolbachia agent with therapeutic potential for Onchocerciasis and lymphatic filariasis. Here, the in vitro and in vivo PK parameters of AN11251 were measured including PPB, intrinsic clearance, half-life, systemic clearance, and volume of distribution. The results indicate that the benzoxaborole-modified pleuromutilin possesses good ADME and PK properties. AN11251 has potent activities against the Gram-positive bacterial pathogens tested, including various drug-resistant strains, and against the slow-growing mycobacterial species. Finally, we employed PK/PD modeling to predict the human dose for treatment of disease caused by Wolbachia, Gram-positive bacteria, or Mycobacterium tuberculosis, which might facilitate the further development of AN11251.

Drug Design and Success of Prospective Mouse In Vitro-In Vivo Extrapolation (IVIVE) for Predictions of Plasma Clearance (CLp) from Hepatocyte Intrinsic Clearance (CLint)

Hepatocyte intrinsic clearance (CL_int) and methods of in vitro-in vivo extrapolation (IVIVE) are often used to predict plasma clearance (CL_p) in drug discovery. While the prediction success of this approach is dependent on the chemotype, specific molecular properties and drug design features that govern these outcomes are poorly understood. To address this challenge, we investigated the success of prospective mouse CL_p IVIVE across 2142 chemically diverse compounds. Dilution scaling, which assumes that the free fraction in hepatocyte incubations (f_u,inc) is governed by binding to the 10% of serum in the incubation medium, was used as our default CL_p IVIVE approach. Results show that predictions of CL_p are better for smaller (molecular weight (MW) < 500 Da), less polar (total polar surface area (TPSA) < 100 Ų, hydrogen bond donor (HBD) ≤1, hydrogen bond acceptor (HBA) ≤ 6), lipophilic (log D > 3), and neutral compounds, with low HBD count playing the key role. If compounds are classified according to their chemical space, predictions were good for compounds resembling central nervous system (CNS) drugs [average absolute fold error (AAFE) of 2.05, average fold error (AFE) of 0.90], moderate for classical druglike compounds (according to Lipinski, Veber, and Ghose guidelines; AAFE of 2.55; AFE of 0.68), and poor for nonclassical "beyond the rule of 5" compounds (AAFE of 3.31; AFE of 0.41). From the perspective of measured druglike properties, predictions of CL_p were better for compounds with moderate-to-high hepatocyte CL_int (>10 μL/min/10⁶ cells), high passive cellular permeability (P_app > 100 nm/s), and moderate observed CL_p (5-50 mL/min/kg). Influences of plasma protein binding (f_u,p) and P-glycoprotein (Pgp) apical efflux ratio (AP-ER) were less pronounced. If the extended clearance classification system (ECCS) is applied, predictions were good for class 2 (P_app > 50 nm/s; neutral or basic; AAFE of 2.35; AFE of 0.70) and acceptable for class 1A compounds (AAFE of 2.98; AFE of 0.70). Classes 1B, 3 A/B, and 4 showed poor outcomes (AAFE > 3.80; AFE < 0.60). Functional groups trending toward weaker CL_p IVIVE were esters, carbamates, sulfonamides, carboxylic acids, ketones, primary and secondary amines, primary alcohols, oxetanes, and compounds liable to aldehyde oxidase metabolism, likely due to multifactorial reasons. Multivariate analysis showed that multiple properties are relevant, combining together to define the overall success of CL_p IVIVE. Our results indicate that the current practice of prospective CL_p IVIVE is suitable only for CNS-like compounds and well-behaved classical druglike space (e.g., high permeability or ECCS class 2) without challenging functional groups. Unfortunately, based on existing mouse data, prospective CL_p IVIVE for complex and nonclassical chemotypes is poor and hardly better than random guessing. This is likely due to complexities such as extrahepatic metabolism and transporter-mediated disposition which are poorly captured by this methodology. With small-molecule drug discovery increasingly evolving toward nonclassical and complex chemotypes, existing CL_p IVIVE methodology will require improvement. While empirical correction factors may bridge the gap in the near future, improved and new in vitro assays, data integration models, and machine learning (ML) methods are increasingly needed to address this challenge and reduce the number of nonclinical pharmacokinetic (PK) studies.

Study of the Metabolic Profiles of "Indazole-3-Carboxamide" and "Isatin Acyl Hydrazone" (OXIZID) Synthetic Cannabinoids in a Human Liver Microsome Model Using UHPLC-QE Orbitrap MS

Unregulated core structures, "isatin acyl hydrazones" (OXIZIDs), have quietly appeared on the market since China legislated to ban seven general core scaffolds of synthetic cannabinoids (SCs). The fast evolution of SCs presents clinical and forensic toxicologists with challenges. Due to extensive metabolism, the parent compounds are barely detectable in urine. Therefore, studies on the metabolism of SCs are essential to facilitate their detection in biological matrices. The aim of the present study was to elucidate the metabolism of two cores, "indazole-3-carboxamide" (e.g., ADB-BUTINACA) and "isatin acyl hydrazone" (e.g., BZO-HEXOXIZID). The in vitro phase I and phase II metabolism of these six SCs was investigated by incubating 10 mg/mL pooled human liver microsomes with co-substrates for 3 h at 37 °C, and then analyzing the reaction mixture using ultrahigh-performance liquid chromatography-quadrupole/electrostatic field orbitrap mass spectrometry. In total, 9 to 34 metabolites were detected for each SC, and the major biotransformations were hydroxylation, dihydrodiol formation (MDMB-4en-PINACA and BZO-4en-POXIZID), oxidative defluorination (5-fluoro BZO-POXIZID), hydrogenation, hydrolysis, dehydrogenation, oxidate transformation to ketone and carboxylate, N-dealkylation, and glucuronidation. Comparing our results with previous studies, the parent drugs and SC metabolites formed via hydrogenation, carboxylation, ketone formation, and oxidative defluorination were identified as suitable biomarkers.

In Vitro-In Vivo Extrapolation and Scaling Factors for Clearance of Human and Preclinical Species with Liver Microsomes and Hepatocytes

In vitro-in vivo extrapolation ((IVIVE) and empirical scaling factors (SF) of human intrinsic clearance (CL_int) were developed using one of the largest dataset of 455 compounds with data from human liver microsomes (HLM) and human hepatocytes (HHEP). For extended clearance classification system (ECCS) class 2/4 compounds, linear SFs (SF_lin) are approximately 1, suggesting enzyme activities in HLM and HHEP are similar to those in vivo under physiological conditions. For ECCS class 1A/1B compounds, a unified set of SFs was developed for CL_int. These SFs contain both SF_lin and an exponential SF (SF_β) of fraction unbound in plasma (f_u,p). The unified SFs for class 1A/1B eliminate the need to identify the transporters involved prior to clearance prediction. The underlying mechanisms of these SFs are not entirely clear at this point, but they serve practical purposes to reduce biases and increase prediction accuracy. Similar SFs have also been developed for preclinical species. For HLM-HHEP disconnect (HLM > HHEP) ECCS class 2/4 compounds that are mainly metabolized by cytochrome P450s/FMO, HLM significantly overpredicted in vivo CL_int, while HHEP slightly underpredicted and geometric mean of HLM and HHEP slightly overpredicted in vivo CL_int. This observation is different than in rats, where rat liver microsomal CL_int correlates well with in vivo CL_int for compounds demonstrating permeability-limited metabolism. The good CL_int IVIVE developed using HLM and HHEP helps build confidence for prospective predictions of human clearance and supports the continued utilization of these assays to guide structure-activity relationships to improve metabolic stability.

New Dual Inhibitors of Bacterial Topoisomerases with Broad-Spectrum Antibacterial Activity and In Vivo Efficacy against Vancomycin-Intermediate Staphylococcus aureus

A new series of dual low nanomolar benzothiazole inhibitors of bacterial DNA gyrase and topoisomerase IV were developed. The resulting compounds show excellent broad-spectrum antibacterial activities against Gram-positive Enterococcus faecalis, Enterococcus faecium and multidrug resistant (MDR) Staphylococcus aureus strains [best compound minimal inhibitory concentrations (MICs): range, <0.03125-0.25 μg/mL] and against the Gram-negatives Acinetobacter baumannii and Klebsiella pneumoniae (best compound MICs: range, 1-4 μg/mL). Lead compound 7a was identified with favorable solubility and plasma protein binding, good metabolic stability, selectivity for bacterial topoisomerases, and no toxicity issues. The crystal structure of 7a in complex with Pseudomonas aeruginosa GyrB24 revealed its binding mode at the ATP-binding site. Expanded profiling of 7a and 7h showed potent antibacterial activity against over 100 MDR and non-MDR strains of A. baumannii and several other Gram-positive and Gram-negative strains. Ultimately, in vivo efficacy of 7a in a mouse model of vancomycin-intermediate S. aureus thigh infection was also demonstrated.

Simplifying the Extended Clearance Concept Classification System (EC3S) to Guide Clearance Prediction in Drug Discovery

PURPOSE

The Extended Clearance Concept Classification System was established as a development-stage tool to provide a framework for identifying fundamental mechanism(s) governing drug disposition in humans. In the present study, the applicability of the EC3S in drug discovery has been investigated. In its current format, the EC3S relies on low-throughput hepatocyte uptake data, which are not frequently generated in a discovery setting.

METHODS

A relationship between hepatocyte uptake clearance and MDCK permeability was first established along with intrinsic clearance from human liver microsomes. The performance of this approach was examined by categorizing 64 drugs into EC3S classes and comparing the predicted major elimination pathway(s) to that observed in humans. As an extension of the work, the ability of the simplified EC3S to predict human systemic clearance based on intrinsic clearance generated using in-vitro metabolic systems was evaluated.

RESULTS

The assessment enabled the use of MDCK permeability and unscaled unbound intrinsic clearance to generate cut-off criteria to categorize compounds into four EC3S classes: Class 12ab, 2cd, 34ab, and 34cd, with major elimination mechanism(s) assigned to each class. The predictivity analysis suggested that systemic clearance could generally be predicted within threefold for EC3S class 12ab and 34ab compounds. For classes 2cd and 34cd, systemic clearance was poorly predicted using in-vitro systems explored in this study.

CONCLUSION

Collectively, our simplified classification approach is expected to facilitate the identification of mechanism(s) involved in drug elimination, faster resolution of in-vitro to in-vivo disconnects, and better design of mechanistic pharmacokinetic studies in drug discovery.

An Insight into the Metabolism of 2,5-Disubstituted Monotetrazole Bearing Bisphenol Structures: Emerging Bisphenol A Structural Congeners

The non-estrogenic 2,5-disubstituted tetrazole core-bearing bisphenol structures (TbB) are being researched as emerging structural congeners of Bisphenol A, an established industrial endocrine disruptor. However, there is no understanding of TbB's adverse effects elicited via metabolic activation. Therefore, the current study aimed to investigate the metabolism of TbB ligands, with in silico results serving as a guide for in vitro studies. The Cytochrome P450 enzymes (CYP) inhibitory assay of TbB ligands on the seven human liver CYP isoforms (i.e., 1A2, 2A6, 2D6, 2C9, 2C8, 2C19, and 3A4) using human liver microsomes (HLM) revealed TbB ligand 223-3 to have a 50% inhibitory effect on all the CYP isoforms at a 10 μM concentration, except 1A2. The TbB ligand 223-10 inhibited 2B6 and 2C8, whereas the TbB ligand 223-2 inhibited only 2C9. The first-order inactivity rate constant (Kobs) studies indicated TbB ligands 223-3, 223-10 to be time-dependent (TD) inhibitors, whereas the TbB 223-2 ligand did not show such a significant effect. The 223-3 exhibited a TD inhibition for 2C9, 2C19, and 1A2 with Kobs values of 0.0748, 0.0306, and 0.0333 min-1, respectively. On the other hand, the TbB ligand 223-10 inhibited 2C9 in a TD inhibition manner with Kobs value 0.0748 min-1. However, the TbB ligand 223-2 showed no significant TD inhibition effect on the CYPs. The 223-2 ligand biotransformation pathway by in vitro studies in cryopreserved human hepatocytes suggested the clearance via glucuronidation with the predominant detection of only 223-2 derived mono glucuronide as a potential inactive metabolite. The present study demonstrated that the 223-2 ligand did not elicit any significant adverse effect via metabolic activation, thus paving the way for its in vivo drug-drug interactions (DDI) studies.

Antiviral effects and tissue exposure of tetrandrine against SARS-CoV-2 infection and COVID-19

Tetrandrine (TET) has been used to treat silicosis in China for decades. The aim of this study was to facilitate rational repurposing of TET against SARS-CoV-2 infection. In this study, we confirmed that TET exhibited antiviral potency against SARS-CoV-2 in the African green monkey kidney (Vero E6), human hepatocarcinoma (Huh7), and human lung adenocarcinoma epithelial (Calu-3) cell lines. TET functioned during the early-entry stage of SARS-CoV-2 and impeded intracellular trafficking of the virus from early endosomes to endolysosomes. An in vivo study that used adenovirus (AdV) 5-human angiotensin-converting enzyme 2 (hACE2)-transduced mice showed that although TET did not reduce pulmonary viral load, it significantly alleviated pathological damage in SARS-CoV-2-infected murine lungs. The systemic preclinical pharmacokinetics were investigated based on in vivo and in vitro models, and the route-dependent biodistribution of TET was explored. TET had a large volume of distribution, which contributed to its high tissue accumulation. Inhaled administration helped TET target the lung and reduced its exposure to other tissues, which mitigated its off-target toxicity. Based on the available human pharmacokinetic data, it appeared feasible to achieve an unbound TET 90% maximal effective concentration (EC90) in human lungs. This study provides insights into the route-dependent pulmonary biodistribution of TET associated with its efficacy.

Impact of chemical structure on the in vitro hydrolysis of fatty esters of 2-ethylhexanoic acid or 2-ethylhexanol and extrapolation to the in vivo situation

Fatty esters of 2-ethylhexanoic acid (EHA) and 2-ethylhexanol (EH) are commonly used in cosmetics. Human liver and skin S9 and human plasma were used to determine the in vitro rates of clearance (CL_int) of a series of compounds, with a range of 2-11 carbons on the acid or alcohol moiety and branching at the C2 position. The impact of carbon chain length on in vitro CL_int was most prominent for the liver metabolism of esters of EH, while for in vitro skin metabolism it was greater for esters of EHA. The position of the branching also impacted the liver hydrolysis rates, especially for the C3, C4, and C5 esters with lower CL_{int in vitro} rates for esters of EHA relative to those of EH. When the in vitro intrinsic clearance rates were scaled to in vivo rates of hepatic clearance, all compounds approximated the rate for hepatic blood flow, mitigating this dependence of metabolism on structure. This work shows how structural changes to the molecule can affect in vitro metabolism and, furthermore, allows for an estimation of the in vivo metabolism.

Metabolic clearance of select opioids and opioid antagonists using hepatic spheroids and recombinant cytochrome P450 enzymes

The opioid crisis is a pressing public health issue, exacerbated by the emergence of more potent synthetic opioids, particularly fentanyl and its analogs. While competitive antagonists exist, their efficacy against synthetic opioids is largely unknown. Furthermore, due to the short durations of action of current antagonists, renarcotization remains a concern. In this study, metabolic activity was characterized for fentanyl-class opioids and common opioid antagonists using multiple in vitro systems, namely, cytochrome P450 (CYP) enzymes and hepatic spheroids, after which an in vitro-in vivo correlation was applied to convert in vitro metabolic activity to predictive in vivo intrinsic clearance. For all substrates, intrinsic hepatic metabolism was higher than the composite of CYP activities, due to fundamental differences between whole cells and single enzymatic reactions. Of the CYP isozymes investigated, 3A4 yielded the highest absolute and relative metabolism across all substrates, with largely negligible contributions from 2D6 and 2C19. Comparative analysis highlighted elevated lipophilicity and diminished CYP3A4 activity as potential considerations for the development of more efficacious opioid antagonists. Finally, antagonists with a high degree of molecular similarity exhibited comparable clearance, providing a basis for structure-metabolism relationships. Together, these results provide multiple screening criteria for early stage drug discovery involving opioid countermeasures.

Structure-based discovery of nonopioid analgesics acting through the α2A-adrenergic receptor

Because nonopioid analgesics are much sought after, we computationally docked more than 301 million virtual molecules against a validated pain target, the α2A-adrenergic receptor (α2AAR), seeking new α2AAR agonists chemotypes that lack the sedation conferred by known α2AAR drugs, such as dexmedetomidine. We identified 17 ligands with potencies as low as 12 nanomolar, many with partial agonism and preferential Gi and Go signaling. Experimental structures of α2AAR complexed with two of these agonists confirmed the docking predictions and templated further optimization. Several compounds, including the initial docking hit '9087 [mean effective concentration (EC50) of 52 nanomolar] and two analogs, '7075 and PS75 (EC50 4.1 and 4.8 nanomolar), exerted on-target analgesic activity in multiple in vivo pain models without sedation. These newly discovered agonists are interesting as therapeutic leads that lack the liabilities of opioids and the sedation of dexmedetomidine.

In Silico Prediction of Human and Rat Liver Microsomal Stability via Machine Learning Methods

Liver microsomal stability is an important property considered for the screening of drug candidates in the early stage of drug development. Determination of hepatic metabolic stability can be performed by an in vitro assay, but it requires quite a few resources and time. In recent years, machine learning methods have made much progress. Therefore, development of computational models to predict liver microsomal stability is highly desirable in the drug discovery process. In this study, the in silico classification models for the prediction of the metabolic stability of compounds in rat and human liver microsomes were constructed by the conventional machine learning and deep learning methods. The performance of the models was evaluated using the test and external sets. For the rat liver microsomes (RLM) stability, the best model yielded the AUC values of 0.84 and 0.71 on the test and external validation sets, respectively. For the human liver microsome (HLM) stability, the best model exhibited the AUC values of 0.86 and 0.77 on the test and external validation sets, respectively. In addition, several important substructure fragments were detected using information gain and frequency substructure analysis methods. The applicability domain of the models was defined using the Euclidean distance-based method. We anticipate that our results would be helpful for the prediction of liver microsomal stability of compounds in the early stage of drug discovery.

On modeling and utilizing chemical compound information with deep learning technologies: A task-oriented approach

A large number of chemical compounds are available in databases such as PubChem and ZINC. However, currently known compounds, though large, represent only a fraction of possible compounds, which is known as chemical space. Many of these compounds in the databases are annotated with properties and assay data that can be used for drug discovery efforts. For this goal, a number of machine learning algorithms have been developed and recent deep learning technologies can be effectively used to navigate chemical space, especially for unknown chemical compounds, in terms of drug-related tasks. In this article, we survey how deep learning technologies can model and utilize chemical compound information in a task-oriented way by exploiting annotated properties and assay data in the chemical compounds databases. We first compile what kind of tasks are trying to be accomplished by machine learning methods. Then, we survey deep learning technologies to show their modeling power and current applications for accomplishing drug related tasks. Next, we survey deep learning techniques to address the insufficiency issue of annotated data for more effective navigation of chemical space. Chemical compound information alone may not be powerful enough for drug related tasks, thus we survey what kind of information, such as assay and gene expression data, can be used to improve the prediction power of deep learning models. Finally, we conclude this survey with four important newly developed technologies that are yet to be fully incorporated into computational analysis of chemical information.

Study on In Vitro Metabolism and In Vivo Pharmacokinetics of Beauvericin

Beauvericin (BEA) is a well-known mycotoxin produced by many fungi, including Beaveria bassiana. The purpose of this study was to evaluate the in vitro distribution and metabolism characteristics as well as the in vivo pharmacokinetic (PK) profile of BEA. The in vitro metabolism studies of BEA were performed using rat, dog, mouse, monkey and human liver microsomes, cryopreserved hepatocytes and plasma under conditions of linear kinetics to estimate the respective elimination rates. Additionally, LC-UV-MSn (n = 1~2) was used to identify metabolites in human, rat, mouse, dog and monkey liver microsomes. Furthermore, cytochrome P450 (CYP) reaction phenotyping was carried out. Finally, the absolute bioavailability of BEA was evaluated by intravenous and oral administration in rats. BEA was metabolically stable in the liver microsomes and hepatocytes of humans and rats; however, it was a strong inhibitor of midazolam 1′-hydroxylase (CYP3A4) and mephenytoin 4′-hydroxylase (CYP2C19) activities in human liver microsomes. The protein binding fraction values of BEA were >90% and the half-life (T1/2) values of BEA were approximately 5 h in the plasma of the five species. The absolute bioavailability was calculated to be 29.5%. Altogether, these data indicate that BEA has great potential for further development as a drug candidate. Metabolic studies of different species can provide important reference values for further safety evaluation.

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.

In Vitro - in Vivo Extrapolation of Hepatic Clearance in Preclinical Species

Accurate prediction of human clearance is of critical importance in drug discovery. In this study, in vitro - in vivo extrapolation (IVIVE) of hepatic clearance was established using large sets of compounds for four preclinical species (mouse, rat, dog, and non-human primate) to enable better understanding of clearance mechanisms and human translation. In vitro intrinsic clearances were obtained using pooled liver microsomes (LMs) or hepatocytes (HEPs) and scaled to hepatic clearance using the parallel-tube and well-stirred models. Subsequently, IVIVE scaling factors (SFs) were derived to best predict in vivo clearance. The SFs for extended clearance classification system (ECCS) class 2/4 compounds, involving metabolic clearance, were generally small (≤ 2.6) using both LMs and HEPs with parallel-tube model, with the exception of the rodents (~ 2.4-4.6), suggesting in vitro reagents represent in vivo reasonably well. SFs for ECCS class 1A and 1B are generally higher than class 2/4 across the species, likely due to the contribution of transporter-mediated clearance that is under-represented with in vitro reagents. The parallel-tube model offered lower variability in clearance predictions over the well-stirred model. For compounds that likely demonstrate passive permeability-limited clearance in vitro, rat LM predicted in vivo clearance more accurately than HEP. This comprehensive analysis demonstrated reliable IVIVE can be achieved using LMs and HEPs. Evaluation of clearance IVIVE in preclinical species helps to better understand clearance mechanisms, establish more reliable IVIVE in human, and enhance our confidence in human clearance and PK prediction, while considering species differences in drug metabolizing enzymes and transporters.

Future of Biotransformation Science in the Pharmaceutical Industry

Over the past decades, the number of scientists trained in departments dedicated to traditional medicinal chemistry, biotransformation and/or chemical toxicology have seemingly declined. Yet, there remains a strong demand for such specialized skills in the pharmaceutical industry, particularly within drug metabolism/pharmacokinetics (DMPK) departments. In this position paper, the members of the Biotransformation, Mechanisms, and Pathways Focus Group (BMPFG) steering committee reflect on the diverse roles and responsibilities of scientists trained in the biotransformation field in pharmaceutical companies and contract research organizations. The BMPFG is affiliated with the International Society for the Study of Xenobiotics (ISSX) and was specifically created to promote the exchange of ideas pertaining to topics of current and future interest involving the metabolism of xenobiotics (including drugs). The authors also delve into the relevant education and diverse training skills required to successfully nurture the future cohort of industry biotransformation scientists and guide them toward a rewarding career path. The ability of scientists with a background in biotransformation and organic chemistry to creatively solve complex drug metabolism problems encountered during research and development efforts on both small and large molecular modalities is exemplified in five relevant case studies. Finally, the authors stress the importance and continued commitment to training the next generation of biotransformation scientists who are not only experienced in the metabolism of conventional small molecule therapeutics, but are also equipped to tackle emerging challenges associated with new drug discovery modalities including peptides, protein degraders, and antibodies. SIGNIFICANCE STATEMENT: Biotransformation and mechanistic drug metabolism scientists are critical to advancing chemical entities through discovery and development, yet the number of scientists academically trained for this role is on the decline. This position paper highlights the continuing demand for biotransformation scientists and the necessity of nurturing creative ways to train them and guarantee the future growth of this field.

An update on the importance of plasma protein binding in drug discovery and development

Introduction: Plasma protein binding (PPB) remains a controversial topic in drug discovery and development. Fraction unbound (f_u) is a critical parameter that needs to be measured accurately, because it has significant impacts on the predictions of drug-drug interactions (DDI), estimations of therapeutic indices (TI), and developments of PK/PD relationships.  However, it is generally not advisable to change PPB through structural modifications, because PPB on its own has little relevance for in vivo efficacy.Areas covered: PPB fundamentals are discussed including the three main classes of drug binding proteins (i.e., albumin, alpha1-acid glycoprotein, and lipoproteins) and their physicochemical properties, in vivo half-life, and synthesis rate.  State-of-the-art methodologies for PPB are highlighted. Applications of PPB in drug discovery and development are presented.Expert opinion: PPB is an old topic in pharmacokinetics, but there are still many misconceptions. Improving the accuracy of PPB for highly bound compounds is an ongoing effort in the field with high priority. As the field continues to generate high quality data, the regulatory agencies will increase their confidence in our ability to accurately measure PPB of highly bound compounds, and experimental fu values below 0.01 will more likely be used for DDI predictions in the future.

Evolving approaches on measurements and applications of intracellular free drug concentration and Kpuu in drug discovery

Introduction: Intracellular-free drug concentration (C_u,cell) and unbound partition coefficient (Kp_uu) are two important parameters to develop pharmacokinetic and pharmacodynamic relationships, predict drug-drug interaction potentials and estimate therapeutic indices.Area covered: Methods on measurements of C_u,cell, Kp_uu, partition coefficient (Kp) and fraction unbound of cells (f_uc) are discussed. Advantages and limitations of several f_uc methods are reviewed. Applications highlighted here are bridging the potency gaps between biochemical and cell-based assays, in vitro hepatocyte assay to predict in vivo liver-to-plasma Kp_uu, the role of Kp_uu in prediction of hepatic clearance for enzyme- and transporter-mediated mechanisms using extended clearance equation, and structural attributes governing tissue Kp_uu.Expert opinion: C_u,cell and Kp_uu are of growing applications in drug discovery. Methods for measurements of these properties continue to evolve in order to achieve higher precision/accuracy and obtain more detailed information at the subcellular levels. Future directions of the field include the development of in vitro and in silico models to predict tissue Kp_uu, direct measurement of free drug concentration in subcellular organelles, and further investigations into the critical elements governing cell and tissue Kp_uu. Significant innovation is needed to advance this complex, but highly impactful and exciting area of science.

Development and Application of a Life-Stage Physiologically Based Pharmacokinetic (PBPK) Model to the Assessment of Internal Dose of Pyrethroids in Humans

To address concerns around age-related sensitivity to pyrethroids, a life-stage physiologically based pharmacokinetic (PBPK) model, supported by in vitro to in vivo extrapolation (IVIVE) was developed. The model was used to predict age-dependent changes in target tissue exposure of 8 pyrethroids; deltamethrin (DLM), cis-permethrin (CPM), trans-permethrin, esfenvalerate, cyphenothrin, cyhalothrin, cyfluthrin, and bifenthrin. A single model structure was used based on previous work in the rat. Intrinsic clearance (CLint) of each individual cytochrome P450 or carboxylesterase (CES) enzyme that are active for a given pyrethroid were measured in vitro, then biologically scaled to obtain in vivo age-specific total hepatic CLint. These IVIVE results indicate that, except for bifenthrin, CES enzymes are largely responsible for human hepatic metabolism (>50% contribution). Given the high efficiency and rapid maturation of CESs, clearance of the pyrethroids is very efficient across ages, leading to a blood flow-limited metabolism. Together with age-specific physiological parameters, in particular liver blood flow, the efficient metabolic clearance of pyrethroids across ages results in comparable to or even lower internal exposure in the target tissue (brain) in children than that in adults in response to the same level of exposure to a given pyrethroid (Cmax ratio in brain between 1- and 25-year old = 0.69, 0.93, and 0.94 for DLM, bifenthrin, and CPM, respectively). Our study demonstrated that a life-stage PBPK modeling approach, coupled with IVIVE, provides a robust framework for evaluating age-related differences in pharmacokinetics and internal target tissue exposure in humans for the pyrethroid class of chemicals.

Influence of Proteome Profiles and Intracellular Drug Exposure on Differences in CYP Activity in Donor-Matched Human Liver Microsomes and Hepatocytes

Human liver microsomes (HLM) and human hepatocytes (HH) are important in vitro systems for studies of intrinsic drug clearance (CLint) in the liver. However, the CLint values are often in disagreement for these two systems. Here, we investigated these differences in a side-by-side comparison of drug metabolism in HLM and HH prepared from 15 matched donors. Protein expression and intracellular unbound drug concentration (Kpuu) effects on the CLint were investigated for five prototypical probe substrates (bupropion-CYP2B6, diclofenac-CYP2C9, omeprazole-CYP2C19, bufuralol-CYP2D6, and midazolam-CYP3A4). The samples were donor-matched to compensate for inter-individual variability but still showed systematic differences in CLint. Global proteomics analysis outlined differences in HLM from HH and homogenates of human liver (HL), indicating variable enrichment of ER-localized cytochrome P450 (CYP) enzymes in the HLM preparation. This suggests that the HLM may not equally and accurately capture metabolic capacity for all CYPs. Scaling CLint with CYP amounts and Kpuu could only partly explain the discordance in absolute values of CLint for the five substrates. Nevertheless, scaling with CYP amounts improved the agreement in rank order for the majority of the substrates. Other factors, such as contribution of additional enzymes and variability in the proportions of active and inactive CYP enzymes in HLM and HH, may have to be considered to avoid the use of empirical scaling factors for prediction of drug metabolism.

Species Differences in Microsomal Metabolism of Xanthine-Derived A1 Adenosine Receptor Ligands

Tracer development for positron emission tomography (PET) requires thorough evaluation of pharmacokinetics, metabolism, and dosimetry of candidate radioligands in preclinical animal studies. Since variations in pharmacokinetics and metabolism of a compound occur in different species, careful selection of a suitable model species is mandatory to obtain valid data. This study focuses on species differences in the in vitro metabolism of three xanthine-derived ligands for the A₁ adenosine receptor (A₁AR), which, in their ¹⁸F-labeled form, can be used to image A₁AR via PET. In vitro intrinsic clearance and metabolite profiles of 8-cyclopentyl-3-(3-fluoropropyl)-1-propylxanthine (CPFPX), an established A₁AR-ligand, and two novel analogs, 8-cyclobutyl-3-(3-fluoropropyl)-1-propylxanthine (CBX) and 3-(3-fluoropropyl)-8-(1-methylcyclobutyl)-1-propylxanthine (MCBX), were determined in liver microsomes from humans and preclinical animal species. Molecular mechanisms leading to significant differences between human and animal metabolite profiles were also examined. The results revealed significant species differences regarding qualitative and quantitative aspects of microsomal metabolism. None of the tested animal species fully matched human microsomal metabolism of the three A₁AR ligands. In conclusion, preclinical evaluation of xanthine-derived A₁AR ligands should employ at least two animal species, preferably rodent and dog, to predict in vivo behavior in humans. Surprisingly, rhesus macaques appear unsuitable due to large differences in metabolic activity towards the test compounds.

A Systematic Study of the In Vitro Pharmacokinetics and Estimated Human In Vivo Clearance of Indole and Indazole-3-Carboxamide Synthetic Cannabinoid Receptor Agonists Detected on the Illicit Drug Market

In vitro pharmacokinetic studies were conducted on enantiomer pairs of twelve valinate or tert-leucinate indole and indazole-3-carboxamide synthetic cannabinoid receptor agonists (SCRAs) detected on the illicit drug market to investigate their physicochemical parameters and structure-metabolism relationships (SMRs). Experimentally derived Log D_7.4 ranged from 2.81 (AB-FUBINACA) to 4.95 (MDMB-4en-PINACA) and all SCRAs tested were highly protein bound, ranging from 88.9 ± 0.49% ((R)-4F-MDMB-BINACA) to 99.5 ± 0.08% ((S)-MDMB-FUBINACA). Most tested SCRAs were cleared rapidly in vitro in pooled human liver microsomes (pHLM) and pooled cryopreserved human hepatocytes (pHHeps). Intrinsic clearance (CL_int) ranged from 13.7 ± 4.06 ((R)-AB-FUBINACA) to 2944 ± 95.9 mL min⁻¹ kg⁻¹ ((S)-AMB-FUBINACA) in pHLM, and from 110 ± 34.5 ((S)-AB-FUBINACA) to 3216 ± 607 mL min⁻¹ kg⁻¹ ((S)-AMB-FUBINACA) in pHHeps. Predicted Human in vivo hepatic clearance (CL_H) ranged from 0.34 ± 0.09 ((S)-AB-FUBINACA) to 17.79 ± 0.20 mL min⁻¹ kg⁻¹ ((S)-5F-AMB-PINACA) in pHLM and 1.39 ± 0.27 ((S)-MDMB-FUBINACA) to 18.25 ± 0.12 mL min⁻¹ kg⁻¹ ((S)-5F-AMB-PINACA) in pHHeps. Valinate and tert-leucinate indole and indazole-3-carboxamide SCRAs are often rapidly metabolised in vitro but are highly protein bound in vivo and therefore predicted in vivo CL_H is much slower than CL_int. This is likely to give rise to longer detection windows of these substances and their metabolites in urine, possibly as a result of accumulation of parent drug in lipid-rich tissues, with redistribution into the circulatory system and subsequent metabolism.

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 K_m or K_i, 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.

Characterization of application scenario-dependent pharmacokinetics and pharmacodynamic properties of permethrin and hyperforin in a dynamic skin and liver multi-organ-chip model

Microphysiological systems (MPS) aim to mimic the dynamic microenvironment and the interaction between tissues. While MPS exist for investigating pharmaceuticals, the applicability of MPS for cosmetics ingredients is yet to be evaluated. The HUMIMIC Chip2 ("Chip2″), is the first multi-organ chip technology to incorporate skin models, allowing for the topical route to be tested. Therefore, we have used this model to analyze the impact of different exposure scenarios on the pharmacokinetics and pharmacodynamics of two topically exposed chemicals, hyperforin and permethrin. The Chip2 incorporated reconstructed human epidermis models (EpiDerm™) and HepaRG-stellate spheroids. Initial experiments using static incubations of single organoids helped determine the optimal dose. In the Chip2 studies, parent and metabolites were analyzed in the circuit over 5 days after application of single and repeated topical or systemic doses. The gene expression of relevant xenobiotic metabolizing enzymes in liver spheroids was measured to reflect toxicodynamics effects of the compounds in liver. The results show that 1) metabolic capacities of EpiDerm™ and liver spheroids were maintained over five days; 2) EpiDerm™ model barrier function remained intact; 3) repeated application of compounds resulted in higher concentrations of parent chemicals and most metabolites compared to single application; 4) compound-specific gene induction e.g. induction of CYP3A4 by hyperforin depended on the application route and frequency; 5) different routes of application influenced the systemic concentrations of both parents and metabolites in the chip over the course of the experiment; 6) there was excellent intra- and inter-lab reproducibility. For permethrin, a process similar to the excretion in a human in vivo study could be simulated which was remarkably comparable to the in vivo situation. These results support the use of the Chip2 model to provide information on parent and metabolite disposition that may be relevant to risk assessment of topically applied cosmetics ingredients.

Evaluation of the Disconnect between Hepatocyte and Microsome Intrinsic Clearance and In Vitro In Vivo Extrapolation Performance

The use of in vitro in vivo extrapolation (IVIVE) from human hepatocyte (HH) and human liver microsome (HLM) stability assays is a widely accepted predictive methodology for human metabolic clearance (CLmet). However, a systematic underprediction of CLmet from both matrices appears to be universally apparent, which can be corrected for via an empirical regression offset. After physiological scaling, intrinsic clearance (CLint) for compounds metabolized via the same enzymatic pathway should be equivalent for both matrices. Compounds demonstrating significantly higher HLM CLint relative to HH CLint have been encountered, raising questions regarding how to predict CLmet for such compounds. Here, we determined the HLM:HH CLint ratio for 140 marketed drugs/compounds, compared this ratio as a function of physiochemical properties and drug metabolism enzyme dependence, and examined methodologies to predict CLmet from both matrices. The majority (78%) of compounds displaying a high HLM:HH CLint ratio were CYP3A substrates. Using HH CLint for CYP3A substrates, the current IVIVE regression offset approach remains an appropriate strategy to predict CLmet (% compounds overpredicted/correctly predicted/underpredicted 27/62/11, respectively). However, using the same approach for HLM significantly overpredicts CLmet for CYP3A substrates (% compounds overpredicted/correctly predicted/underpredicted 56/33/11, respectively), highlighting that a different IVIVE offset is required for CYP3A substrates using HLM. This work furthers the understanding of compound properties associated with a disproportionately high HLM:HH CLint ratio and outlines a successful IVIVE approach for such compounds. SIGNIFICANCE STATEMENT: Oral drug discovery programs typically strive for low clearance compounds to ensure sufficient target engagement. Human liver microsomes and isolated human hepatocytes are used to optimize and predict human hepatic metabolic clearance. After physiological scaling, intrinsic clearance for compounds of the same metabolic pathway should be equivalent between matrices. However, a disconnect in intrinsic clearance is sometimes apparent. The work described attempts to further understand this phenomenon, and by achieving a mechanistic understanding, improvements in clearance predictions may be realized.

Predicting the Human Hepatic Clearance of Acidic and Zwitterionic Drugs

Prospective predictions of human hepatic clearance for anionic/zwitterionic compounds, which are oftentimes subjected to transporter-mediated uptake, are challenging in drug discovery. We evaluated the utility of preclinical species, rats and cynomolgus monkeys [nonhuman primates (NHPs)], to predict the human hepatic clearance using a diverse set of acidic/zwitterionic drugs. Preclinical clearance data were generated following intravenous dosing in rats/NHPs and compared to the human clearance data (n = 18/27). Single-species scaling of NHP clearance with an allometric exponent of 0.50 allowed for good prediction of human clearance (fold error ∼2.1, bias ∼1.0), with ∼86% predictions within 3-fold. In comparison, rats underpredicted the clearance of lipophilic acids, while overprediction was noted for hydrophilic acids. Finally, an in vitro clearance assay based on human hepatocytes, which is routinely used in discovery setting, markedly underpredicted human clearance (bias ∼0.12). Collectively, this study provides insights into the usefulness of the preclinical models in enabling pharmacokinetic optimization for acid/zwitterionic drug candidates.

Comparison of In Vitro to In Vivo Extrapolation Approaches for Predicting Transporter-Mediated Hepatic Uptake Clearance Using Suspended Rat Hepatocytes

Clearance (CL) prediction remains a significant challenge in drug discovery, especially when complex processes such as drug transporters are involved. The present work explores various in vitro to in vivo extrapolation (IVIVE) approaches to predict hepatic CL driven by uptake transporters in rat. Broadly, two different IVIVE methods using suspended rat hepatocytes were compared: initial uptake CL (PSu,inf) and intrinsic metabolic CL (CLint,met) corrected by unbound hepatocytes to medium partition coefficient (Kpuu). Kpuu was determined by temperature method (Temp Kpuu,ss), homogenization method (Hom Kpuu,ss), and initial rate method (Kpuu,V0). In addition, the impact of bovine serum albumin (BSA) on each of these methods was investigated. Twelve compounds, which are known substrates of organic anion-transporting polypeptides representing diverse chemical matter, were selected for these studies. As expected, CLint,met alone significantly underestimated hepatic CL for all the test compounds. Overall, predicted hepatic CL using PSu,inf with BSA, Hom Kpuu,ss with BSA, and Temp Kpuu,ss showed the most robust correlation with in vivo rat hepatic CL. Adding BSA improved hepatic CL prediction for selected compounds when using the PSu,inf and Hom Kpuu,ss methods, with minimal impact on the Temp Kpuu,ss and Kpuu,V0 methods. None of the IVIVE approaches required an empirical scaling factor. These results suggest that supplementing rat hepatocyte suspension with BSA may be essential in drug discovery research for novel chemical matters to improve CL prediction. SIGNIFICANCE STATEMENT: The current investigation demonstrates that hepatocyte uptake assay supplemented with 4% bovine serum albumin is a valuable tool for estimating unbound hepatic uptake clearance (CL) and Kpuu. Based upon the extended clearance concept, direct extrapolation from these in vitro parameters significantly improved the overall hepatic CL prediction for organic anion-transporting polypeptide substrates in rat. This study provides a practical in vitro to in vivo extrapolation strategy for predicting transporter-mediated hepatic CL in early drug discovery.

Optimizing the Benefit/Risk of Acetyl-CoA Carboxylase Inhibitors through Liver Targeting

Preclinical and clinical data suggest that acetyl-CoA carboxylase (ACC) inhibitors have the potential to rebalance disordered lipid metabolism, leading to improvements in nonalcoholic steatohepatitis (NASH). Consistent with these observations, first-in-human clinical trials with our ACC inhibitor PF-05175157 led to robust reduction of de novo lipogenesis (DNL), albeit with concomitant reductions in platelet count, which were attributed to the inhibition of fatty acid synthesis within bone marrow. Herein, we describe the design, synthesis, and evaluation of carboxylic acid-based ACC inhibitors with organic anion transporting polypeptide (OATP) substrate properties, which facilitated selective distribution of the compounds at the therapeutic site of action (liver) relative to the periphery. These efforts led to the discovery of clinical candidate PF-05221304 (12), which selectively inhibits liver DNL in animals, while demonstrating considerable safety margins against platelet reduction in a nonhuman primate model.