Prediction of in vivo drug metabolism in the human liver from in vitro metabolism data

Time-course cross-species transcriptomics reveals conserved hepatotoxicity pathways induced by repeated administration of cyclosporine A

Cyclosporine A (CsA) has shown efficacy against immunity-related diseases despite its toxicity in various organs, including the liver, emphasizing the need to elucidate its underlying hepatotoxicity mechanism. This study aimed to capture the alterations in genome-wide expression over time and the subsequent perturbations of corresponding pathways across species. Six data from humans, mice, and rats, including animal liver tissue, human liver microtissues, and two liver cell lines exposed to CsA toxic dose, were used. The microtissue exposed to CsA for 10 d was analyzed to obtain dynamically differentially expressed genes (DEGs). Single-time points data at 1, 3, 5, 7, and 28 d of different species were used to provide additional evidence. Using liver microtissue-based longitudinal design, DEGs that were consistently up- or down-regulated over time were captured, and the well-known mechanism involved in CsA toxicity was elucidated. Thirty DEGs that consistently changed in longitudinal data were also altered in 28-d rat in-house data with concordant expression. Some genes (e.g. TUBB2A, PLIN2, APOB) showed good concordance with identified DEGs in 1-d and 7-d mouse data. Pathway analysis revealed up-regulations of protein processing, asparagine N-linked glycosylation, and cargo concentration in the endoplasmic reticulum. Furthermore, the down-regulations of pathways related to biological oxidations and metabolite and lipid metabolism were elucidated. These pathways were also enriched in single-time-point data and conserved across species, implying their biological significance and generalizability. Overall, the human organoids-based longitudinal design coupled with cross-species validation provides temporal molecular change tracking, aiding mechanistic elucidation and biologically relevant biomarker discovery.

Rational Exploration of 2,4-Diaminopyrimidines as DHFR Inhibitors Active against Mycobacterium abscessus and Mycobacterium avium, Two Emerging Human Pathogens

Nontuberculous mycobacteria (NTM) are emerging human pathogens linked to severe pulmonary diseases. Current treatments involve the prolonged use of multiple drugs and are often ineffective. Bacterial dihydrofolate reductase (DHFR) is a key enzyme targeted by antibiotics in Gram-negative bacterial infections. However, existing DHFR inhibitors designed for Gram-negative bacteria often fail against mycobacterial DHFRs. Here, we detail the rational design of NTM DHFR inhibitors based on P218, a malarial DHFR inhibitor. We identified compound 8, a 2,4-diaminopyrimidine exhibiting improved pharmacological properties and activity against purified DHFR, and whole cell cultures of two predominant NTM species: Mycobacterium avium and Mycobacterium abscessus. This study underscores the potential of compound 8 as a promising candidate for the in vivo validation of DHFR as an effective treatment against NTM infections.

Rapid Characterization of the Potential Active of Sinomenine in Rats by Ultra-High-Performance Liquid Chromatography-Quadrupole-Exactive Orbitrap Mass Spectrometry and Molecular Docking

Sinomenium acutum (Thunb.) Rehd. et Wils is widely used in the treatment of rheumatoid arthritis, with its alkaloid compound sinomenine (SIN) being renowned for its significant anti-inflammatory properties. However, despite its widespread application, the in vivo anti-inflammatory mechanisms and metabolic pathways of SIN remain incompletely understood. This study established a rapid and reliable method based on an ultra-high-performance liquid chromatography method coupled with Quadrupole-Exactive Orbitrap mass spectrometry and molecular docking to identify and characterize SIN and 69 metabolites in rat plasma, urine, and feces, revealing primary metabolic pathways of hydroxylation, demethylation, sulfation, and glucuronidation. Molecular docking results revealed that phase I reactions, including dedimethylation, demethylation, dehydrogenation, and dihydroxylation, along with their composite reactions, were pivotal in influencing SIN's in vivo anti-inflammatory activity. M28, M36, and M59 are potentially the most anti-inflammatory active metabolites of SIN in vivo. This comprehensive analysis unveils SIN's metabolic pathways, offering insights into its biological processes and suggesting a novel approach for exploring active drug constituents. These findings pave the way for further understanding SIN's anti-inflammatory mechanisms, contributing significantly to the development of new therapeutic strategies.

Pyridinyl 4-(2-oxoalkylimidazolidin-1-yl)benzenesulfonates and their hydrochloride salts as novel water soluble antimitotic prodrugs bioactivated by cytochrome P450 1A1 in breast cancer cells

We developed first-in-class antimitotic prodrugs phenyl 4-(2-oxo-alkylimidazolidin-1-yl)benzenesulfonates (PAIB-SOs) bioactivated by cytochrome P450 (CYP) 1A1 that are highly selective toward several breast cancer cells. However, they show sparingly water solubility. Therefore, we replaced their phenyl ring B with a substituted pyridinyl group preparing novel pyridinyl 4-(2-oxo-3-alkylimidazolidin-1-yl)benzenesulfonates (PYRAIB-SOs) and their hydrochloride salts. Our results evidence that PYRAIB-SO hydrochloride salts show higher water solubility compared to their neutral and PAIB-SO counterparts by up to 625-fold. PYRAIB-SOs with a nitrogen atom at position 3 of the pyridinyl ring exhibited strong antiproliferative activity (IC50: 0.03-3.3 μM) and high selectivity (8->1250) toward sensitive CYP1A1-positive breast cancer cells and cells stably transfected with CYP1A1. They induce cell cycle arrest in the G2/M phase and disrupt microtubule dynamic assembly. Enzymatic assays confirmed that CYP1A1 metabolizes PYRAIB-SOs into their active form with in vitro hepatic half-lives (55-120 min) in rodent and human liver microsomes. Overall, this will allow to increase drug concentration for in vivo studies.

Predicting the in vivo developmental toxicity of fenarimol from in vitro toxicity data using PBTK modelling-facilitated reverse dosimetry approach

In vitro methods are widely used in modern toxicological testing; however, the data cannot be directly employed for risk assessment. In vivo toxicity of chemicals can be predicted from in vitro data using physiologically based toxicokinetic (PBTK) modelling-facilitated reverse dosimetry (PBTK-RD). In this study, a minimal-PBTK model was constructed to predict the in-vivo kinetic profile of fenarimol (FNL) in rats and humans. The model was verified by comparing the observed and predicted pharmacokinetics of FNL for rats (calibrator) and further applied to humans. Using the PBTK-RD approach, the reported in vitro developmental toxicity data for FNL was translated to in vivo dose-response data to predict the assay equivalent oral dose in rats and humans. The predicted assay equivalent rat oral dose (36.46 mg/kg) was comparable to the literature reported in vivo BMD10 value (22.8 mg/kg). The model was also employed to derive the chemical-specific adjustment factor (CSAF) for interspecies toxicokinetics variability of FNL. Further, Monte Carlo simulations were performed to predict the population variability in the plasma concentration of FNL and to derive CSAF for intersubject human kinetic differences. The comparison of CSAF values for interspecies and intersubject toxicokinetic variability with their respective default values revealed that the applied uncertainty factors were adequately protective.

In vitro and in vivo studies on a group of chalcones find promising results as potential drugs against fascioliasis

About a third of the world population is infected by helminth parasites implicated in foodborne trematodiasis. Fascioliasis is a worldwide disease caused by trematodes of the genus Fasciola spp. It generates huge economic losses to the agri-food industry and is currently considered an emerging zoonosis by the World Health Organization (WHO). The only available treatment relies on anthelmintic drugs, being triclabendazole (TCBZ) the drug of choice to control human infections. The emergence of TCBZ resistance in several countries and the lack of an effective vaccine to prevent infection highlights the need to develop new drugs to control this parasitosis. We have previously identified a group of benzochalcones as inhibitors of cathepsins, which have fasciolicidal activity in vitro and are potential new drugs for the control of fascioliasis. We selected the four most active compounds of this group to perform further preclinical studies. The compound's stability was determined against a liver microsomal enzyme fraction, obtaining half-lives of 34-169 min and low intrinsic clearance values (<13 μL/min/mg), as desirable for potential new drugs. None of the compounds were mutagenic or genotoxic and no in vitro cytotoxic effects were seen. Compounds C31 and C34 showed the highest selectivity index against liver fluke cathepsins when compared to human cathepsin L. They were selected for in vivo efficacy studies observing a protective effect, similar to TCBZ, in a mouse model of infection. Our findings strongly encourage us to continue the drug development pipeline for these molecules.

A 20-Year Research Overview: Quantitative Prediction of Hepatic Clearance Using the In Vitro-In Vivo Extrapolation Approach Based on Physiologically Based Pharmacokinetic Modeling and Extended Clearance Concept

Understanding the extended clearance concept and establishing a physiologically based pharmacokinetic (PBPK) model are crucial for investigating the impact of changes in transporter and metabolizing enzyme abundance/functions on drug pharmacokinetics in blood and tissues. This mini-review provides an overview of the extended clearance concept and a PBPK model that includes transporter-mediated uptake processes in the liver. In general, complete in vitro and in vivo extrapolation (IVIVE) poses challenges due to missing factors that bridge the gap between in vitro and in vivo systems. By considering key in vitro parameters, we can capture in vivo pharmacokinetics, a strategy known as the top-down or middle-out approach. We present the latest progress, theory, and practice of the Cluster Gauss-Newton method, which is used for middle-out analyses. As examples of poor IVIVE, we discuss "albumin-mediated hepatic uptake" and "time-dependent inhibition" of OATP1Bs. The hepatic uptake of highly plasma-bound drugs is more efficient than what can be accounted for by their unbound concentration alone. This phenomenon is referred to as "albumin-mediated" hepatic uptake. IVIVE was improved by measuring hepatic uptake clearance in vitro in the presence of physiologic albumin concentrations. Lastly, we demonstrate the application of Cluster Gauss-Newton method-based analysis to the target-mediated drug disposition of bosentan. Incorporating saturable target binding and OATP1B-mediated hepatic uptake into the PBPK model enables the consideration of nonlinear kinetics across a wide dose range and the prediction of receptor occupancy over time. SIGNIFICANCE STATEMENT: There have been multiple instances where researchers' endeavors to unravel the underlying mechanism of poor in vitro-in vivo extrapolation have led to the discovery of previously undisclosed truths. These include 1) albumin-mediated hepatic uptake, 2) the target-mediated drug disposition in small molecules, and 3) the existence of a trans-inhibition mechanism by inhibitors for OATP1B-mediated hepatic uptake of drugs. Consequently, poor in vitro-in vivo extrapolation and the subsequent inquisitiveness of scientists may serve as a pivotal gateway to uncover hidden mechanisms.

A physiologically-based pharmacokinetic/pharmacodynamic (PBPK/PD) model for the insecticide dimethoate

1. Dimethoate is an organophosphate insecticide that is converted in vivo to omethoate, the active toxic moiety. Omethoate inhibits acetylcholinesterase (AChE) in the brain and red blood cells (RBCs). This paper describes the development of rat and human physiologically-based pharmacokinetic/pharmacodynamic (PBPK/PD) models for dimethoate.2. The model simulates the absorption and distribution of dimethoate and omethoate, the conversion of dimethoate to omethoate and to other metabolites, the metabolism and excretion of omethoate, and the inhibition of RBC and brain AChE. An extensive data collection program to estimate metabolism and inhibition parameters is described.3. The suite of models includes an adult rat, post-natal rat, and human model. The rat models were evaluated by comparing model predictions of dimethoate and omethoate to measured blood time course data, and with RBC and brain AChE inhibition estimates from an extensive database of in vivo AChE measurements.4. After the demonstration of adequately fitted rat models that were robust to sensitivity analysis, the human model was applied for estimation of points-of-departure (PODs) for risk assessment using the human-specific parameters in the human PBPK/PD model. Thus, the standard interspecies uncertainty factor can be reduced from 10X to 1X.

Beyond the Michaelis-Menten: Accurate Prediction of Drug Interactions through Cytochrome P450 3A4 Induction

The US Food and Drug Administration (FDA) guidance has recommended several model-based predictions to determine potential drug-drug interactions (DDIs) mediated by cytochrome P450 (CYP) induction. In particular, the ratio of substrate area under the plasma concentration-time curve (AUCR) under and not under the effect of inducers is predicted by the Michaelis-Menten (MM) model, where the MM constant ( K m $$ {K}_{\mathrm{m}} $$ ) of a drug is implicitly assumed to be sufficiently higher than the concentration of CYP enzymes that metabolize the drug ( E T $$ {E}_{\mathrm{T}} $$ ) in both the liver and small intestine. Furthermore, the fraction absorbed from gut lumen ( F a $$ {F}_{\mathrm{a}} $$ ) is also assumed to be one because F a $$ {F}_{\mathrm{a}} $$ is usually unknown. Here, we found that such assumptions lead to serious errors in predictions of AUCR. To resolve this, we propose a new framework to predict AUCR. Specifically, F a $$ {F}_{\mathrm{a}} $$ was re-estimated from experimental permeability values rather than assuming it to be one. Importantly, we used the total quasi-steady-state approximation to derive a new equation, which is valid regardless of the relationship between K m $$ {K}_{\mathrm{m}} $$ and E T $$ {E}_{\mathrm{T}} $$ , unlike the MM model. Thus, our framework becomes much more accurate than the original FDA equation, especially for drugs with high affinities, such as midazolam or strong inducers, such as rifampicin, so that the ratio between K m $$ {K}_{\mathrm{m}} $$ and E T $$ {E}_{\mathrm{T}} $$ becomes low (i.e., the MM model is invalid). Our work greatly improves the prediction of clinical DDIs, which is critical to preventing drug toxicity and failure.

Synthesis and Anti-Inflammatory Activity of 2-Amino-4,5,6,7-tetrahydrobenzo[b]thiophene-Derived NRF2 Activators

This is the first study investigating the nuclear factor (erythroid-derived 2)-like 2 (NRF2) activity of compounds containing a new scaffold, tetrahydrobenzo[b]thiophene. Eighteen compounds were synthesised and confirmed their NRF2 activation through NQO1 enzymatic activity and mRNA expression of NQO1 and HO-1 in Hepa-1c1c7 cells. The compounds disrupted the interaction between Kelch-like ECH-associated protein 1 (KEAP1) and NRF2 via interfering with the KEAP1's Kelch domain. The compounds exhibited anti-inflammatory activity in Escherichia coli Lipopolysaccharide (LPSEc )-stimulated RAW 264.7 cells. The anti-inflammatory activity of the compounds was associated with their ability to activate NRF2. The compounds reversed the elevated levels of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α, and IFN-γ) and inflammatory mediators (PGE2, COX-2, and NF-κB). The compounds were metabolically stable in human, rat, and mouse liver microsomes and showed optimum half-life (T1/2 ) and intrinsic clearance (Clint ). The binding mode of the compounds and physicochemical properties were predicted via in silico studies.

Anti-Inflammatory Effects of Auranamide and Patriscabratine-Mechanisms and In Silico Studies

Auranamide and patriscabratine are amides from Melastoma malabathricum (L.) Smith. Their anti-inflammatory activity and nuclear factor erythroid 2-related factor 2 (NRF2) activation ability were evaluated using Escherichia coli lipopolysaccharide (LPSEc)-stimulated murine macrophages (RAW264.7) and murine hepatoma (Hepa-1c1c7) cells, respectively. The cytotoxicity of the compounds was assessed using a 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assay. The anti-inflammatory activity was determined by measuring the nitric oxide (NO) production and pro-inflammatory cytokines (Interleukin (IL)-1β, Interferon (IFN)-γ, tumour necrosis factor (TNF)-α, and IL-6) and mediators (NF-κB and COX-2). NRF2 activation was determined by measuring the nicotinamide adenine dinucleotide phosphate hydrogen (NADPH) quinone oxidoreductase 1 (NQO1), nuclear NRF2 and hemeoxygenase (HO)-1. In vitro metabolic stability was assessed using the mouse, rat, and human liver microsomes. The compounds were non-toxic to the cells at 10 μM. Both compounds showed dose-dependent effects in downregulating NO production and pro-inflammatory cytokines and mediators. The compounds also showed upregulation of NQO1 activity and nuclear NRF2 and HO-1 levels. The compounds were metabolically stable in mouse, rat and human liver microsomes. The possible molecular targets of NRF2 activation by these two compounds were predicted using molecular docking studies and it was found that the compounds might inhibit the Kelch domain of KEAP1 and GSK-3β activity. The physicochemical and drug-like properties of the test compounds were predicted using Schrodinger small molecule drug discovery suite (v.2022-2).

Application of Physiologically Based Pharmacokinetic Modeling in Preclinical Studies: A Feasible Strategy to Practice the Principles of 3Rs

Pharmacokinetic characterization plays a vital role in drug discovery and development. Although involving numerous laboratory animals with error-prone, labor-intensive, and time-consuming procedures, pharmacokinetic profiling is still irreplaceable in preclinical studies. With physiologically based pharmacokinetic (PBPK) modeling, the in vivo profiles of drug absorption, distribution, metabolism, and excretion can be predicted. To evaluate the application of such an approach in preclinical investigations, the plasma pharmacokinetic profiles of seven commonly used probe substrates of microsomal enzymes, including phenacetin, tolbutamide, omeprazole, metoprolol, chlorzoxazone, nifedipine, and baicalein, were predicted in rats using bottom-up PBPK models built with in vitro data alone. The prediction's reliability was assessed by comparison with in vivo pharmacokinetic data reported in the literature. The overall predicted accuracy of PBPK models was good with most fold errors within 2, and the coefficient of determination (R2) between the predicted concentration data and the observed ones was more than 0.8. Moreover, most of the observation dots were within the prediction span of the sensitivity analysis. We conclude that PBPK modeling with acceptable accuracy may be incorporated into preclinical studies to refine in vivo investigations, and PBPK modeling is a feasible strategy to practice the principles of 3Rs.

Assessment of Digestion, Absorption, and Metabolism of Nanoencapsulated Phytochemicals Using In Vitro and In Vivo Models: A Perspective Paper

Nanoencapsulation delivery systems have been used to enhance the absorption and bioefficacy of phytochemicals. With modified physical and chemical properties, nanoencapsulated phytochemicals differ from their free forms in digestion, absorption, and metabolism. These pharmacokinetic processes can be assessed using a combination of various in vitro/in vivo models and analytical strategies, but each approach has its limitations. The correlation between current models and physiological conditions and their feasibility for nanoencapsulation systems require further validation. More detailed studies are still needed to clarify how nanoencapsulation affects the phytochemical and host interaction. Future investigations must take extra caution in model selection and result interpretation.

Cytochrome P450 isoforms contribution, plasma protein binding, toxicokinetics of enniatin A in rats and in vivo clearance prediction in humans

Emerging mycotoxins, such as enniatin A (ENNA), are becoming a worldwide concern owing to their presence in different types of food and feed. However, comprehensive toxicokinetic data that links intake, exposure and toxicological effects of ENNA has not been elucidated yet. Therefore, the present study investigated the in vitro (rat and human) and in vivo (rat) toxicokinetic properties of ENNA. Towards this, an easily applicable and sensitive bioanalytical method was developed and validated for the estimation of ENNA in rat plasma. ENNA exhibited high plasma protein binding (99%), high hepatic clearance and mainly underwent metabolism via CYP3A4 (74%). The in-house predicted hepatic clearance (54 mL/min/kg) and observed in vivo rat clearance (55 mL/min/kg) were comparable. The predicted in vivo human hepatic clearance was 18 mL/min/kg. ENNA underwent slow absorption (T_max = 4 h) and rapid elimination following oral administration to rats. The absolute oral bioavailability was 47%. The toxicokinetic findings for ENNA from this study will help in designing and interpreting toxicological studies in rats. Besides, these findings could be used in physiologically based toxicokinetic (PBTK) model development for exposure predictions and risk assessment for ENNA in humans.

Design and synthesis of multifunctional microtubule targeting agents endowed with dual pro-apoptotic and anti-autophagic efficacy

Autophagy is a lysosome dependent cell survival mechanism and is central to the maintenance of organismal homeostasis in both physiological and pathological situations. Targeting autophagy in cancer therapy attracted considerable attention in the past as stress-induced autophagy has been demonstrated to contribute to both drug resistance and malignant progression and recently interest in this area has re-emerged. Unlocking the therapeutic potential of autophagy modulation could be a valuable strategy for designing innovative tools for cancer treatment. Microtubule-targeting agents (MTAs) are some of the most successful anti-cancer drugs used in the clinic to date. Scaling up our efforts to develop new anti-cancer agents, we rationally designed multifunctional agents 5a-l with improved potency and safety that combine tubulin depolymerising efficacy with autophagic flux inhibitory activity. Through a combination of computational, biological, biochemical, pharmacokinetic-safety, metabolic studies and SAR analyses we identified the hits 5i,k. These MTAs were characterised as potent pro-apoptotic agents and also demonstrated autophagy inhibition efficacy. To measure their efficacy at inhibiting autophagy, we investigated their effects on basal and starvation-mediated autophagic flux by quantifying the expression of LC3II/LC3I and p62 proteins in oral squamous cell carcinoma and human leukaemia through western blotting and by immunofluorescence study of LC3 and LAMP1 in a cervical carcinoma cell line. Analogues 5i and 5k, endowed with pro-apoptotic activity on a range of hematological cancer cells (including ex-vivo chronic lymphocytic leukaemia (CLL) cells) and several solid tumor cell lines, also behaved as late-stage autophagy inhibitors by impairing autophagosome-lysosome fusion.

Application of liquid chromatography coupled to data-independent acquisition mass spectrometry for the metabolic profiling of N-ethyl heptedrone

We have investigated the metabolic profile of N-ethyl heptedrone, a new designer synthetic stimulant drug, by using data independent acquisition mass spectrometry. Phase I and phase II metabolism was studied by in vitro models, followed by liquid-chromatography coupled to mass spectrometry, to characterize and pre-select the most diagnostic markers of intake. N-ethyl heptedrone was incubated in the presence of pooled human liver microsomes. The contribution of individual enzymatic isoforms in the formation of the phase I and phase II metabolites was further investigated by using human recombinant cDNA-expressed cytochrome P450 enzymesand uridine 5'-diphospho glucuronosyltransferases. The analytical workflow consisted of liquid-liquid extraction with tert-butyl-methyl-ether at alkaline pH, performed before (to investigate the phase I metabolic profile) and after (to investigate the glucuronidation profile) enzymatic hydrolysis. The separation, identification, and determination of the compounds formed in the in vitro experiments were carried out by using liquid chromatography coupled to either high- or low-resolution mass spectrometry. Data independent acquisition method, namely sequential window acquisition of all theoretical fragment-ion spectra (SWATH®) and product ion scan were selected for high-resolution mass spectrometry, whereas multiple reaction monitoring was used for low-resolution mass spectrometry. Thirteen phase-I metabolites were isolated, formed from reactions being catalyzed mainly by CYP1A2, CYP2C9, CYP2C19 and CYP2D6 and, to a lesser degree, by CYP3A4 and CYP3A5. The phase I biotransformation pathways included hydroxylation in different positions, reduction of the ketone group, carbonylation, N-dealkylation, and combinations of the above. Most of the hydroxylated metabolites underwent conjugation reactions to form the corresponding glucurono-conjugated metabolites. Based on our in vitro observation, the metabolic products resulting from reduction of the keto group, N-dealkylation and hydroxylation of the aliphatic chain appear to be the most diagnostic target analytes to be selected as markers of exposure to N-ethyl heptedrone.

Prospective prediction of plasma pharmacokinetics of a novel immune-modulating agent in cancer patients after intra-tumoral administration: translation from non-clinical species to humans

Intra-tumoral (I-TUMOUR) delivery is being widely explored for novel anti-cancer agents. This route is anticipated to result in high tumour concentrations leading to better efficacy and safety. Prediction of human systemic pharmacokinetics (PK) from non-clinical species facilitates understanding of pharmacokinetic-pharmacodynamic relationships, efficient dose selection, and risk assessment of novel drugs. However, there is limited knowledge on the predictability of human pharmacokinetics following I-TUMOUR delivery.In this publication, we present a case study wherein human systemic PK of a novel agent administered intra-tumourally was prospectively predicted and compared with observed human PK.Simple allometry was used to project the human clearance (10.5 mL/min/kg) and steady-state volume of distribution (1.4 L/kg) after intravenous (IV) dosing. Using these IV PK parameters and assuming rapid absorption and complete I-TUMOUR bioavailability, human plasma PK profile was simulated. The projected 30 min concentrations and AUC_(0-6h) were within 1.9 to 2.5-fold and 1 to 1.4-fold of the observed PK indicating a reasonable concordance between predicted and observed PK.To our knowledge, this is the first article that prospectively projected human pharmacokinetics after I-TUMOUR dosing. The results from this study indicate that similar approaches can be used to project the human PK of other I-TUMOUR agents.

Drug metabolic stability in early drug discovery to develop potential lead compounds

Knowledge of the metabolic stability of a new drug substance eliminated by biotransformation is essential for envisaging the pharmacokinetic parameters required for deciding drug dosing and frequency. Strategies aimed at modifying lead compounds may improve metabolic stability, thereby reducing the drug dosing frequency. Replacement of selective hydrogens with deuterium can effectively enhance the drug's metabolic stability by increasing the biological half-life. Further, cyclization, change in ring size, and chirality can substantially improve the metabolic stability of drugs. The microsomal t_1/2 approach for measuring drug in vitro intrinsic clearance by automated LC-MS/MS offers sensitive high-throughput screens with reliable data. The obtained in vitro intrinsic clearance from metabolic stability data helps predict the drug's in vivo total clearance using different scaling factors and hepatic clearance models. This review summarizes all the recent approaches and technological advancements in metabolic stability studies for narrowing down the potential lead compounds in drug discovery. Further, we summarized the potential pitfalls and assumptions made during the in vivo intrinsic clearance estimation from in vitro intrinsic clearance.

Comparison between lab variability and in silico prediction errors for the unbound fraction of drugs in human plasma

Variability of the unbound fraction in plasma (f_u) between labs, methods and conditions is known to exist. Variability and uncertainty of this parameter influence predictions of the overall pharmacokinetics of drug candidates and might jeopardise safety in early clinical trials. Objectives of this study were to evaluate the variability of human in vitro f_u-estimates between labs for a range of different drugs, and to develop and validate an in silico f_u-prediction method and compare the results to the lab variability.A new in silico method with prediction accuracy (Q²) of 0.69 for log f_u was developed. The median and maximum prediction errors were 1.9- and 92-fold, respectively. Corresponding estimates for lab variability (ratio between max and min f_u for each compound) were 2.0- and 185-fold, respectively. Greater than 10-fold lab variability was found for 14 of 117 selected compounds.Comparisons demonstrate that in silico predictions were about as reliable as lab estimates when these have been generated during different conditions. Results propose that the new validated in silico prediction method is valuable not only for predictions at the drug design stage, but also for reducing uncertainties of f_u-estimations and improving safety of drug candidates entering the clinical phase.

Evaluation and comparison of in vitro intrinsic clearance rates measured using cryopreserved hepatocytes from humans, rats, and rainbow trout

In vitro and in silico methods that can reduce the need for animal testing are being used with increasing frequency to assess chemical risks to human health and the environment. The rate of hepatic biotransformation is an important species-specific parameter for determining bioaccumulation potential and extrapolating in vitro bioactivity to in vivo effects. One approach to estimating hepatic biotransformation is to employ in vitro systems derived from liver tissue to measure chemical (substrate) depletion over time which can then be translated to a rate of intrinsic clearance (CL_int). In the present study, cryopreserved hepatocytes from humans, rats, and rainbow trout were used to measure CL_int values for 54 industrial and pesticidal chemicals at starting test concentrations of 0.1 and 1 μM. A data evaluation framework that emphasizes the behavior of Heat-Treated Controls (HTC) was developed to identify datasets suitable for rate reporting. Measured or estimated ("greater than" or "less than") CL_int values were determined for 124 of 226 (55 %) species-chemical-substrate concentration datasets with acceptable analytical chemistry. A large percentage of tested chemicals exhibited low HTC recovery values, indicating a substantial abiotic loss of test chemical over time. An evaluation of K_OW values for individual chemicals suggested that in vitro test performance declined with increasing chemical hydrophobicity, although differences in testing devices for mammals and fish also likely played a role. The current findings emphasize the value of negative controls as part of a rigorous approach to data quality assessment for in vitro substrate depletion studies. Changes in current testing protocols can be expected to result in the collection of higher quality data. However, poorly soluble chemicals are likely to remain a challenge for CL_int determination.

A Novel Experimental and Theoretical Method for Estimating Albumin-Mediated Hepatic Uptake Based on the Albumin Binding Fraction in Plasma and Human PK Prediction Using a Physiologically-Based Pharmacokinetic Approach

Recently, protein-facilitated uptake has been suggested to be an important factor in the precise prediction of the pharmacokinetic (PK) profiles of drugs. In our previous study, a physiologically-based pharmacokinetic (PBPK) approach considering the mechanism of albumin-mediated hepatic uptake was developed for predicting human PK profiles. It was assumed that drugs affected by albumin-mediated hepatic uptake would bind only to albumin, which means that there would be over-estimation of the contribution of protein-facilitated uptake for a drug that could bind to multiple proteins. In this study, we developed a method that can evaluate the albumin binding fraction in plasma considering the affinity for other proteins. Based on the albumin binding fraction, the contribution of albumin-mediated hepatic uptake was theoretically estimated, and then the human PK profiles were predicted by our proposed PBPK approach incorporating this mechanism. As a result, the predicted human PK profiles agreed well with the observed ones, and the absolute average fold error of PK parameters was almost within a 1.5-fold error on average. These findings show the importance of considering protein-facilitated uptake and also suggest that our proposed PBPK approach can be useful in scientific discussions with regulatory authorities.

Pharmacodynamics-based approach for efficacious human dose projection of BMS-986260, a small molecule transforming growth factor beta receptor 1 inhibitor

Transforming growth factor beta (TGF-β) is a pleiotropic cytokine that has a wide array of biological effects. For decades, tumor biology implicated TGF-β as an attractive therapeutic target due to its immunosuppressive effects. Toward this end, multiple pharmaceutical companies developed a number of drug modalities that specifically target the TGF-β pathway. BMS-986260 is a small molecule, selective TGF-βR1 kinase inhibitor that was under preclinical development for oncology. In vivo studies across mouse, rat, dog, and monkey and cryopreserved hepatocytes predicted human pharmacokinetics (PK) and distribution of BMS-986260. Efficacy studies of BMS-986260 were undertaken in the MC38 murine colon cancer model, and target engagement, as measured by phosphorylation of SMAD2/3, was assessed in whole blood to predict the clinical efficacious dose. The human clearance is predicted to be low, 4.25 ml/min/kg. BMS-986260 provided a durable and robust antitumor response at 3.75 mg/kg daily and 1.88 mg/kg twice-daily dosing regimens. Phosphorylation of SMAD2/3 was 3.5-fold less potent in human monocytes than other preclinical species. Taken together, the projected clinical efficacious dose was 600 mg QD or 210 mg BID for 3 days followed by a 4-day drug holiday. Mechanism-based cardiovascular findings in the rat ultimately led to the termination of BMS-986260. This study describes the preclinical PK characterization and pharmacodynamics-based efficacious dose projection of a novel small molecule TGF-βR1 inhibitor.

A Simple Decision Tree Suited for Identification of Early Oral Drug Candidates With Likely Pharmacokinetic Nonlinearity by Intestinal CYP3A Saturation

To identify oral drugs that likely display nonlinear pharmacokinetics due to saturable metabolism by intestinal CYP3A, our previous report using CYP3A substrate drugs proposed an approach using thresholds for the linear index number (LIN3A = dose/K_m; K_m, Michaelis-Menten constant for CYP3A) and the intestinal availability (F_aF_g). Here, we aimed to extend the validity of the previous approach using both CYP3A substrate and non-substrate drugs and to devise a decision tree suited for early drug candidates using in vitro metabolic intrinsic clearance (CL_{int, vitro}) instead of F_aF_g. Out of 152 oral drugs (including 136 drugs approved in Japan, US or both), type I nonlinearity (in which systemic drug exposure increases in a more than dose-proportional manner) was noted with 82 drugs (54%), among which 58 drugs were identified as CYP3A substrates based on public information. Based on practical feasibility, 41 drugs were selected from CYP3A substrates and subjected to in-house metabolic assessment. The results were used to determine the thresholds for CL_{int, vitro} (0.45 μL/min/pmol CYP3A4) and LIN3A (1.0 L). For four drugs incorrectly predicted, potential mechanisms were looked up. Overall, our proposed decision tree may aid in the identification of early drug candidates with intestinal CYP3A-derived type I nonlinearity.

Evidence-based strategies for the characterisation of human drug and chemical glucuronidation in vitro and UDP-glucuronosyltransferase reaction phenotyping

Enzymes of the UDP-glucuronosyltransferase (UGT) superfamily contribute to the elimination of drugs from almost all therapeutic classes. Awareness of the importance of glucuronidation as a drug clearance mechanism along with increased knowledge of the enzymology of drug and chemical metabolism has stimulated interest in the development and application of approaches for the characterisation of human drug glucuronidation in vitro, in particular reaction phenotyping (the fractional contribution of the individual UGT enzymes responsible for the glucuronidation of a given drug), assessment of metabolic stability, and UGT enzyme inhibition by drugs and other xenobiotics. In turn, this has permitted the implementation of in vitro - in vivo extrapolation approaches for the prediction of drug metabolic clearance, intestinal availability, and drug-drug interaction liability, all of which are of considerable importance in pre-clinical drug development. Indeed, regulatory agencies (FDA and EMA) require UGT reaction phenotyping for new chemical entities if glucuronidation accounts for ≥25% of total metabolism. In vitro studies are most commonly performed with recombinant UGT enzymes and human liver microsomes (HLM) as the enzyme sources. Despite the widespread use of in vitro approaches for the characterisation of drug and chemical glucuronidation by HLM and recombinant enzymes, evidence-based guidelines relating to experimental approaches are lacking. Here we present evidence-based strategies for the characterisation of drug and chemical glucuronidation in vitro, and for UGT reaction phenotyping. We anticipate that the strategies will inform practice, encourage development of standardised experimental procedures where feasible, and guide ongoing research in the field.

Investigating the Theoretical Basis for In Vitro-In Vivo Extrapolation (IVIVE) in Predicting Drug Metabolic Clearance and Proposing Future Experimental Pathways

Extensive studies have been conducted to predict in vivo metabolic clearance from in vitro human liver metabolism parameters (i.e., in vitro-in vivo extrapolation (IVIVE)) with little success. Here, deriving IVIVE from first principles, we show that the product of fraction unbound in the blood and the predicted in vivo intrinsic clearance determined from hepatocyte or microsomal incubations is the lower boundary condition for in vivo hepatic clearance and the prerequisite for IVIVE predictions to be valid, regardless of extraction ratio. For 60-80% of drugs evaluated here, this product is markedly less than the in vivo measured clearance, a result that violates the lower boundary of the predictive relationship. This can only be explained by (a) suboptimal in vitro metabolic stability assay conditions, (b) significant error in the assumption that in vitro intrinsic clearance determinations will predict in vivo intrinsic clearance simply by scaling-up the amount of enzyme (in vitro incubation to in vivo liver), and/or (c) the methods of determining fraction unbound are incorrect. We further suggest that widely employed organ blood flow values underpredict the effective blood flow within the organ by approximately 2.5-fold, thus impacting IVIVE of high clearance compounds. We propose future pathways that should be investigated in terms of the relationship to experimentally measured clearance values, rather than model-dependent intrinsic clearance. IVIVE outcome can be improved by estimating the ratio of unbound drug concentration in the liver tissue to the liver plasma, examining the assumption of the free drug theory (i.e., there are no transporter effects at the blood cell membrane) and the finding that the upper limit of organ clearance may be greater than blood flow entering the organ.

Application of the Extended Clearance Classification System (ECCS) in Drug Discovery and Development: Selection of Appropriate In Vitro Tools and Clearance Prediction

In vitro to in vivo extrapolation (IVIVE) to predict human hepatic clearance, including metabolism and transport, requires extensive experimental resources. In addition, there may be technical challenges to measure low clearance values. Therefore, prospective identification of rate-determining step(s) in hepatic clearance through application of the Extended Clearance Classification System (ECCS) could be beneficial for optimal compound characterization. IVIVE for hepatic intrinsic clearance (CLint,h) prediction is conducted for a set of 36 marketed drugs with low-to-high in vivo clearance, which are substrates of metabolic enzymes and active uptake transporters in the liver. The compounds were assigned to the ECCS classes, and CLint,h, estimated with HepatoPac (a micropatterned hepatocyte coculture system), was compared with values calculated based on suspended hepatocyte incubates. An apparent permeability threshold (apical to basal) of 50 nm/s in LLC-PK1 cells proved optimal for ECCS classification. A reasonable performance of the IVIVE for compounds across multiple classes using HepatoPac was achieved (with 2-3-fold error), except for substrates of uptake transporters (class 3b), for which scaling of uptake clearance using plated hepatocytes is more appropriate. Irrespective of the ECCS assignment, metabolic clearance can be estimated well using HepatoPac. The validation and approach elaborated in the present study can result in proposed decision trees for the selection of the optimal in vitro assays guided by ECCS class assignment, to support compound optimization and candidate selection. SIGNIFICANCE STATEMENT: Characterization of the rate-determining step(s) in hepatic elimination could be on the critical path of compound optimization during drug discovery. This study demonstrated that HepatoPac and plated hepatocytes are suitable tools for the estimation of metabolic and active uptake clearance, respectively, for a larger set of marketed drugs, supporting a comprehensive strategy to select optimal in vitro tools and to achieve Extended Clearance Classification System-dependent in vitro to in vivo extrapolation for human clearance prediction.

Current Approaches and Techniques in Physiologically Based Pharmacokinetic (PBPK) Modelling of Nanomaterials

There have been efforts to develop physiologically based pharmacokinetic (PBPK) models for nanomaterials (NMs). Since NMs have quite different kinetic behaviors, the applicability of the approaches and techniques that are utilized in current PBPK models for NMs is warranted. Most PBPK models simulate a size-independent endocytosis from tissues or blood. In the lungs, dosimetry and the air-liquid interface (ALI) models have sometimes been used to estimate NM deposition and translocation into the circulatory system. In the gastrointestinal (GI) tract, kinetics data are needed for mechanistic understanding of NM behavior as well as their absorption through GI mucus and their subsequent hepatobiliary excretion into feces. Following absorption, permeability (P_t) and partition coefficients (PCs) are needed to simulate partitioning from the circulatory system into various organs. Furthermore, mechanistic modelling of organ- and species-specific NM corona formation is in its infancy. More recently, some PBPK models have included the mononuclear phagocyte system (MPS). Most notably, dissolution, a key elimination process for NMs, is only empirically added in some PBPK models. Nevertheless, despite the many challenges still present, there have been great advances in the development and application of PBPK models for hazard assessment and risk assessment of NMs.

In-Silico Modeling in Drug Metabolism and Interaction: Current Strategies of Lead Discovery

BACKGROUND

Drug metabolism is a complex mechanism of human body systems to detoxify foreign particles, chemicals, and drugs through bio alterations. It involves many biochemical reactions carried out by invivo enzyme systems present in the liver, kidney, intestine, lungs, and plasma. After drug administration, it crosses several biological membranes to reach into the target site for binding and produces the therapeutic response. After that, it may undergo detoxification and excretion to get rid of the biological systems. Most of the drugs and its metabolites are excreted through kidney via urination. Some drugs and their metabolites enter into intestinal mucosa and excrete through feces. Few of the drugs enter into hepatic circulation where they go into the intestinal tract. The drug leaves the liver via the bile duct and is excreted through feces. Therefore, the study of total methodology of drug biotransformation and interactions with various targets is costly.

METHODS

To minimize time and cost, in-silico algorithms have been utilized for lead-like drug discovery. Insilico modeling is the process where a computer model with a suitable algorithm is developed to perform a controlled experiment. It involves the combination of both in-vivo and in-vitro experimentation with virtual trials, eliminating the non-significant variables from a large number of variable parameters. Whereas, the major challenge for the experimenter is the selection and validation of the preferred model, as well as precise simulation in real physiological status.

RESULTS

The present review discussed the application of in-silico models to predict absorption, distribution, metabolism, and excretion (ADME) properties of drug molecules and also access the net rate of metabolism of a compound.

CONCLUSION

It helps with the identification of enzyme isoforms; which are likely to metabolize a compound, as well as the concentration dependence of metabolism and the identification of expected metabolites. In terms of drug-drug interactions (DDIs), models have been described for the inhibition of metabolism of one compound by another, and for the compound-dependent induction of drug-metabolizing enzymes.

Direct Comparison of Total Clearance Prediction: Computational Machine Learning Model versus Bottom-Up Approach Using In Vitro Assay

The in vitro-in vivo extrapolation (IVIVE) approach for predicting total plasma clearance (CL_tot) has been widely used to rank order compounds early in discovery. More recently, a computational machine learning approach utilizing physicochemical descriptors and fingerprints calculated from chemical structure information has emerged, enabling virtual predictions even earlier in discovery. Previously, this approach focused more on in vitro intrinsic clearance (CL_int) prediction. Herein, we directly compare these two approaches for predicting CL_tot in rats. A structurally diverse set of 1114 compounds with known in vivo CL_tot, in vitro CL_int, and plasma protein binding was used as the basis for this evaluation. The machine learning models were assessed by validation approaches using the time- and cluster-split training and test sets, and five-fold cross validation. Assessed by five-fold validation, the random forest regression (RF) and radial basis function (RBF) models demonstrated better prediction performance in eight attempted machine learning models. The CL_tot values predicted by the RF and RBF models were within two-fold of the observed values for 67.7 and 71.9% of cluster-split test set compounds, respectively, while the predictivity was worse in the time-split dataset. The predictivity of both models tended to be improved by incorporating in vitro parameters, unbound fraction in plasma (f_u,p), and CL_int. CL_tot prediction utilizing in vitro CL_int and the well-stirred model, correcting for the fraction unbound in blood, was substantially worse compared to machine learning approaches for the same cluster-split test set. The reason that CL_tot is underestimated by IVIVE is not fully explained by considering the calculated microsomal unbound fraction (cf_u,mic), extended clearance classification system (ECCS), and omitting high clearance compounds in excess of hepatic blood flow. The analysis suggests that in silico machine learning models may have the power to reduce reliance on or replace in vitro and in vivo studies for chemical structure optimization in early drug discovery.

Beyond the Michaelis-Menten: Accurate Prediction of In Vivo Hepatic Clearance for Drugs With Low KM

Clearance (CL) is the major pharmacokinetic parameter for evaluating systemic exposure of drugs in the body and, thus, for developing new drugs. To predict in vivo CL, the ratio between the maximal rate of metabolism and Michaelis‐Menten constant (V_max/K_M estimated from in vitro metabolism study has been widely used. This canonical approach is based on the Michaelis‐Menten equation, which is valid only when the K_M value of a drug is much higher than the hepatic concentration of the enzymes, especially cytochrome P450, involved in its metabolism. Here, we find that such a condition does not hold for many drugs with low K_M, and, thus, the canonical approach leads to considerable error. Importantly, we propose an alternative approach, which incorporates the saturation of drug metabolism when concentration of the enzymes is not sufficiently lower than K_M. This new approach dramatically improves the accuracy of prediction for in vivo CL of high‐affinity drugs with low K_M. This indicates that the proposed approach in this study, rather than the canonical approach, should be used to predict in vivo hepatic CL for high‐affinity drugs, such as midazolam and propafenone.

In Vitro Toxicokinetics and Phase I Biotransformation of the Mycotoxin Penitrem A in Dogs

The tremorgenic mycotoxin penitrem A is produced by Penicillium species as a secondary metabolite on moldy food and feed. Dogs are sometimes exposed to penitrem A by consumption of spoiled food waste or fallen fruit. The lipophilic toxin crosses the blood-brain barrier and targets neuroreceptors and neurotransmitter release mechanisms in the central and peripheral nervous systems. Typical symptoms of penitrem A intoxication are periodical or continuous tremors, which can be passing, persistent or lethal, depending on the absorbed dose. There is presently no information on the biotransformation and toxicokinetics of penitrem A in dogs. The aim of the present study was therefore to identify potential metabolites of the toxin by performing in vitro biotransformation assays in dog liver microsomes. Analyses by liquid chromatography coupled to high-resolution mass spectrometry led to the provisional identification of eleven penitrem A phase I metabolites, which were tentatively characterized as various oxidation products. Furthermore, elimination parameters determined in in vitro assays run under linear kinetics were used for in vitro-to-in vivo extrapolation of the toxicokinetic data, predicting a maximal bioavailability of more than 50%. The metabolite profile detected in the in vitro assays was similar to that observed in the plasma of an intoxicated dog, confirming the predictive capability of the in vitro approach.

In vitro hepatic biotransformation of the algal toxin pectenotoxin-2

We have investigated the in vitro metabolism of pectenotoxin-2 (PTX-2) using primary hepatocytes from Wistar rats in suspension. Purified PTX-2 was rapidly metabolized. Two major and several minor oxidized PTX-2 metabolites were formed, none of which had retention times corresponding to PTX-1, -11, or −13. Hydrolysis products, such as PTX-2 seco acid, were not observed. Preliminary multi-stage LC-MS analyses indicated that the major hepatic PTX-2 metabolites resulted from the insertion of an oxygen atom at the positions C-19 to C-24, or at C-44. The rapid oxidative metabolism may explain the low oral toxicity of PTXs observed in vivo studies.

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PTX-2 is rapidly metabolized in rat hepatocytes.

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Two major and several minor oxidized PTX-2 metabolites were formed.

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The results may explain the low oral toxicity of PTXs observed in vivo studies.

In vitro-in vivo extrapolation of metabolic clearance using human liver microsomes: factors showing variability and their normalization

In vitro-in vivo extrapolation (IVIVE) using human liver microsomes has been widely used to predict metabolic clearance, but some of the factors used in the process of prediction show variability for the same compound: notably, microsomal intrinsic clearance values corrected by the unbound fraction (CL_{int, u}), physiological parameters used for scale-up, and the source of in vivo clearance data.The purpose of this study was to assess the correlation between in vitro and in vivo CL_int with a focus on factors showing variability using four cytochrome P450 (CYP)3A substrates.We surveyed in vivo clearance values in literature and also determined the microsomal CL_{int, u} values. A scaling factor (SF_direct) was defined as in vivo CL_int divided by the microsomal CL_{int, u}, which ranged from 1190 to 2310 (mg protein per kg body weight). The application of a mean SF_direct of 1600 (mg protein per kg body weight) and further normalization by the microsomal CL_{int, u} values of midazolam, the most commonly used substrate, resulted in improved prediction accuracy for CL_{int, u} values from various microsomal batches.The results suggest the normalization of variability might be useful for predicting the in vivo CL_int.

Narrowing the Gap Between In Vitro and In Vivo Genetic Profiles by Deconvoluting Toxicogenomic Data In Silico

Toxicogenomics (TGx) is a powerful method to evaluate toxicity and is widely used in both in vivo and in vitro assays. For in vivo TGx, reduction, refinement, and replacement represent the unremitting pursuit of live-animal tests, but in vitro assays, as alternatives, usually demonstrate poor correlation with real in vivo assays. In living subjects, in addition to drug effects, inner-environmental reactions also affect genetic variation, and these two factors are further jointly reflected in gene abundance. Thus, finding a strategy to factorize inner-environmental factor from in vivo assays based on gene expression levels and to further utilize in vitro data to better simulate in vivo data is needed. We proposed a strategy based on post-modified non-negative matrix factorization, which can estimate the gene expression profiles and contents of major factors in samples. The applicability of the strategy was first verified, and the strategy was then utilized to simulate in vivo data by correcting in vitro data. The similarities between real in vivo data and simulated data (single-dose 0.72, repeat-doses 0.75) were higher than those observed when directly comparing real in vivo data with in vitro data (single-dose 0.56, repeat-doses 0.70). Moreover, by keeping environment-related factor, a simulation can always be generated by using in vitro data to provide potential substitutions for in vivo TGx and to reduce the launch of live-animal tests.

Effect of Gender on the Pharmacokinetics of ON 123300, A Dual Inhibitor of ARK5 and CDK4/6 for the Treatment of Cancer, in Rats

BACKGROUND AND OBJECTIVES

ON 123300, a small molecule dual inhibitor of the c-MYC activated kinases ARK5 and CDK4/6, is being developed as a novel drug candidate for the treatment of cancer. The objective of this research was to evaluate gender differences in the in vitro metabolism and in vivo systemic exposure of ON 123300 in rats.

METHODS

In vitro metabolism experiments (n = 2/group) were performed in rat liver microsomes from male and female donors. ON 123300 bislactate (final concentration 10 µM) was incubated with 0.5 mg/mL microsomes, and samples (100 µL) were withdrawn at specified incubation times over a period of 60 min, and immediately quenched and centrifuged. The supernatant was analyzed for ON 123300 and its metabolites by HPLC. ON 123300 (bislactate salt) pharmacokinetics were evaluated following intravenous (i.v.) (30 s infusion, 5 and 10 mg/kg) or oral administration (25 and 100 mg/kg) to male and female Sprague-Dawley rats (250-300 g). Following dosing, blood samples were collected over a time period up to 24 h. ON 123300 plasma concentrations were measured by LC-MS/MS. Pharmacokinetic parameters were estimated by non-compartmental analysis. Plasma and microsomal binding of ON 123300 and blood:plasma ratio were also determined.

RESULTS

ON 123300 displayed more rapid microsomal degradation in vitro in males compared to females, as reflected in intrinsic clearance (181 vs 53.1 µL/min/mg). This translated into a significantly higher exposure of ON 123300 following oral administration to female rats, with the area under the curve (AUC) increasing nearly 3-fold (5617 ± 1914 ng·h/mL) compared to males (AUC = 1965 ± 749 ng·h/mL). This gender effect was less pronounced following i.v. dosing, where the AUC was ~ 2-fold higher in females. Based on these results, the higher plasma exposure observed in females can be primarily attributed to reductions in both hepatic clearance and presystemic metabolism compared to males.

CONCLUSIONS

This investigation demonstrated a significantly lower metabolism of ON 123300 in female rats, which resulted in high systemic exposure. Additional testing is warranted to assess the potential clinical implications of these findings.

Biotransformation of Polycyclic Aromatic Hydrocarbons by Trout Liver S9 Fractions: Evaluation of Competitive Inhibition Using a Substrate Depletion Approach

Environmental contaminants frequently occur as part of a chemical mixture, potentially resulting in competitive inhibition among multiple substrates metabolized by the same enzyme. Trout liver S9 fractions were used to evaluate the biotransformation of 3 polycyclic aromatic hydrocarbons (PAHs): phenanthrene, pyrene, and benzo[a]pyrene, tested as binary mixtures. Initial rates of biotransformation were determined using a substrate-depletion approach. The resulting data were then fitted by simultaneous nonlinear regression to a competitive inhibition model. In each case, the PAH possessing the lower Michaelis-Menten affinity constant (K_M ) competitively inhibited biotransformation of the other compound. Inhibition constants determined for the lower-K_M compound were generally close to previously determined K_M values, consistent with the suggestion that phase I biotransformation of PAHs is largely catalyzed by one or a small number of cytochrome P450 enzymes. The use of a substrate-depletion approach to perform enzyme-inhibition studies imposes practical limitations on experimental design and complicates the interpretation of derived kinetic constants. Nevertheless, the resulting information may have utility for chemical hazard assessments as well as the design and interpretation of controlled laboratory studies. Depletion experiments informed by measured chemical concentrations in tissues may also provide a means of determining whether enzyme inhibition occurs under relevant environmental conditions. Environ Toxicol Chem 2019;38:2729-2739. Published 2019 Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work, and as such, is in the public domain in the United States of America.

Comparative Proteomics Analysis of Human Liver Microsomes and S9 Fractions

Human liver microsomes (HLM) and human liver S9 fractions (HLS9) are commonly used to study drug metabolism in vitro. However, a quantitative comparison of HLM and HLS9 proteomes is lacking, resulting in the arbitrary selection of one hepatic preparation over another and in difficulties with data interpretation. In this study, we applied a label-free global absolute quantitative proteomics method to the analysis of HLS9 and the corresponding HLM prepared from 102 individual human livers. A total of 3137 proteins were absolutely quantified, and 3087 of those were determined in both HLM and HLS9. Protein concentrations were highly correlated between the two hepatic preparations (R = 0.87, P < 0.0001). We reported the concentrations of 98 drug-metabolizing enzymes (DMEs) and 51 transporters, and demonstrated significant differences between their abundances in HLM and HLS9. We also revealed the protein-protein correlations among these DMEs and transporters and the sex effect on the HLM and HLS9 proteomes. Additionally, HLM and HLS9 displayed distinct expression patterns for protein markers of cytosol and various cellular organelles. Moreover, we evaluated the interindividual variability of three housekeeping proteins, and identified five proteins with low variation across individuals that have the potential to serve as new internal controls for western blot experiments. In summary, these results will lead to better understanding of data obtained from HLM and HLS9 and assist in in vitro-in vivo extrapolations. Knowing the differences between HLM and HLS9 also allows us to make better-informed decisions when choosing between these two hepatic preparations for in vitro drug metabolism studies. SIGNIFICANCE STATEMENT: This investigation revealed significant differences in protein concentrations of drug-metabolizing enzymes and transporters between human liver microsomes and S9 fractions. We also determined the protein-protein correlations among the drug-metabolizing enzymes and transporters and the sex effect on the proteomes of these two hepatic preparations. The results will help interpret data obtained from these two preparations and allow us to make more informed decisions when choosing between human liver microsomes and S9 fractions for in vitro drug metabolism studies.

Metabolic stability and its role in the discovery of new chemical entities

Determination of metabolic profiles of new chemical entities is a key step in the process of drug discovery, since it influences pharmacokinetic characteristics of therapeutic compounds. One of the main challenges of medicinal chemistry is not only to design compounds demonstrating beneficial activity, but also molecules exhibiting favourable pharmacokinetic parameters. Chemical compounds can be divided into those which are metabolized relatively fast and those which undergo slow biotransformation. Rapid biotransformation reduces exposure to the maternal compound and may lead to the generation of active, non-active or toxic metabolites. In contrast, high metabolic stability may promote interactions between drugs and lead to parent compound toxicity. In the present paper, issues of compound metabolic stability will be discussed, with special emphasis on its significance, in vitro metabolic stability testing, dilemmas regarding in vitro-in vivo extrapolation of the results and some aspects relating to different preclinical species used in in vitro metabolic stability assessment of compounds.

Defining the Contribution of CYP1A1 and CYP1A2 to Drug Metabolism Using Humanized CYP1A1/1A2 and Cyp1a1/Cyp1a2 Knockout Mice

Cytochrome P450s CYP1A1 and CYP1A2 can metabolize a broad range of foreign compounds and drugs. However, these enzymes have significantly overlapping substrate specificities. To establish their relative contribution to drug metabolism in vivo, we used a combination of mice humanized for CYP1A1 and CYP1A2 together with mice nulled at the Cyp1a1 and Cyp1a2 gene loci. CYP1A2 was constitutively expressed in the liver, and both proteins were highly inducible by 2,3,7,8-tetrachlorodibenzodioxin (TCDD) in a number of tissues, including the liver, lung, kidney, and small intestine. Using the differential inhibition of the human enzymes by quinidine, we developed a method to distinguish the relative contribution of CYP1A1 or CYP1A2 in the metabolism of drugs and foreign compounds. Both enzymes made a significant contribution to the hepatic metabolism of the probe compounds 7-methoxy and 7-ehthoxyresorufin in microsomal fractions from animals treated with TCDD. This enzyme kinetic approach allows modeling of the CYP1A1, CYP1A2, and non-CYP1A contribution to the metabolism of any substrate at any substrate, inhibitor, or enzyme concentration and, as a consequence, can be integrated into a physiologically based pharmacokinetics model. The validity of the model can then be tested in humanized mice in vivo. SIGNIFICANCE STATEMENT: Human CYP1A1 and CYP1A2 are important in defining the efficacy and toxicity/carcinogenicity of drugs and foreign compounds. In light of differences in substrate specificity and sensitivity to inhibitors, it is of central importance to understand their relative role in foreign compound metabolism. To address this issue, we have generated mice humanized or nulled at the Cyp1a gene locus and, through the use of these mouse lines and selective inhibitors, developed an enzyme kinetic-based model to enable more accurate prediction of the fate of new chemicals in humans and which can be validated in vivo using mice humanized for cytochrome P450-mediated metabolism.

Determination of the in vitro metabolic stability and metabolites of the anticancer derivative riccardin D-N in human and mouse hepatic S9 fractions using HPLC-Q-LIT-MS

Riccardin D-N (RD-N) is an aminomethylated derivative of the macrocyclic bisbibenzyl compound riccardin D (RD), which has shown stronger activity against cancer cells than RD. However, there has been no research on the metabolism of RD-N. The present study aimed to characterize the in vitro metabolism and metabolic stability of RD-N after incubation with mouse and human hepatic S9 fractions using high performance liquid chromatography-hybrid triple quadrupole/linear ion trap mass spectrometry (HPLC-Q-LIT-MS). Multiple ion monitoring (MIM) and multiple reaction monitoring (MRM)-information dependent acquisition-enhanced product ion (MIM/MRM-IDA-EPI) scans were used to identify the metabolites formed. MRM scans were also used to quantify the changes in the amount of RD-N and to semi-quantify the main metabolites. Twenty-eight metabolic products were detected and 25 structures were predicted. Hydroxylation, dehydrogenation, glucuronidation, and methylation were proposed to be the principle metabolic pathways in the in vitro incubation with human and mouse hepatic S9 fractions. There were differences in the number and abundance of RD-N metabolites between the human and mouse hepatic S9 fractions. RD-N was shown to have good metabolic stability. After 2 h of incubation, 44% of the original RD-N remained in the human hepatic S9 fraction compared with 22% in the mouse. The major metabolites of RD-N, M4, M8, M20 and M21, were monitored semi-quantitatively using the typical transitions. Finally, HPLC-Q-LIT-MS was used for the identification and quantitation of the metabolites of R D-N, which is a simple and efficient method to rapidly screen potential drug candidates.

Bioformulative concepts on intracellular organ specific bioavailability

Bioavailability is an ancient but effective terminology by which the entire therapeutic efficacy of a drug directly or indirectly relays. Despite considering general plasma bioavailability, specific organ/tissue bioavailability will pave the path to broad spectrum dose calculation. Clear knowledge and calculative vision on bioavailability can improve the research and organ-targeting phenomenon. This article comprises a detailed introduction on bioavailability along with regulatory aspects, kinetic data and novel bioformulative approaches to achieve improved organ specific bioavailability, which may not be readily related to blood plasma bioavailability.