Misuse of the Well-Stirred Model of Hepatic Drug Clearance: Fig. 1

Novel 5-HT7 receptor antagonists modulate intestinal immune responses and reduce severity of colitis

Inflammatory bowel disease (IBD) encompasses several debilitating chronic gastrointestinal (GI) inflammatory disorders, including Crohn's disease and ulcerative colitis. In both conditions, mucosal inflammation is a key clinical presentation associated with altered serotonin (5-hydroxytryptamine or 5-HT) signaling. This altered 5-HT signaling is also found across various animal models of colitis. Of the 14 known receptor subtypes, 5-HT receptor type 7 (5-HT7) is one of the most recently discovered. We previously reported that blocking 5-HT signaling with either a selective 5-HT7 receptor antagonist (SB-269970) or genetic ablation alleviated intestinal inflammation in murine experimental models of colitis. Here, we developed novel antagonists, namely, MC-170073 and MC-230078, which target 5-HT7 receptors with high selectivity. We also investigated the in vivo efficacy of these antagonists in experimental colitis by using dextran sulfate sodium (DSS) and the transfer of CD4+CD45RBhigh T cells to induce intestinal inflammation. Inhibition of 5-HT7 receptor signaling with the antagonists, MC-170073 and MC-230078, ameliorated intestinal inflammation in both acute and chronic colitis models, which was accompanied by lower histopathological damage and diminished levels of proinflammatory cytokines compared with vehicle-treated controls. Together, the data reveal that the pharmacological inhibition of 5-HT7 receptors by these selective antagonists ameliorates the severity of colitis across various experimental models and may, in the future, serve as a potential treatment option for patients with IBD. In addition, these findings support that 5-HT7 is a viable therapeutic target for IBD.NEW & NOTEWORTHY This study demonstrates that the novel highly selective 5-HT7 receptor antagonists, MC-170073 and MC-230078, significantly alleviated the severity of colitis across models of experimental colitis. These findings suggest that inhibition of 5-HT7 receptor signaling by these new antagonists may serve as an alternative mode of treatment to diminish symptomology in those with inflammatory bowel disease.

Using the Dynamic Well-Stirred Model to Extrapolate Hepatic Clearance of Organic Anion-Transporting Polypeptide Transporter Substrates without Assuming Albumin-Mediated Hepatic Drug Uptake

Extrapolating in vivo hepatic clearance from in vitro uptake data is a known challenge, especially for organic anion-transporting polypeptide transporter (OATP) substrates, and the well-stirred model (WSM) commonly yields systematic underpredictions for those anionic drugs, hypothetically due to "albumin-mediated hepatic drug uptake". In the present study, we demonstrate that the WSM incorporating the dynamic free fraction (f D), a measure of drug protein binding affinity, performs reasonably well in predicting hepatic clearance of OATP substrates. For a selection of anionic drugs, including atorvastatin, fluvastatin, pravastatin, rosuvastatin, pitavastatin, cerivastatin, and repaglinide, this dynamic well-stirred model (dWSM) correctly predicts hepatic plasma clearance within 2-fold error for six out of seven OATP substrates examined. The geometric mean of clearance ratios between the predicted and the observed values falls in the range of 1.21-1.38. As expected, the WSM with unbound fraction (f u) systematically underpredicts hepatic clearance with greater than 2-fold error for five out of seven drugs, and the geometric mean of clearance ratios between the predicted and the observed values is in the range of 0.20-0.29. The results suggest that, despite its simplicity, the dWSM operates well for transporter-mediated uptake clearance, and that clearance under-prediction of OATP substrates may not necessarily be associated with the chemical class of the anionic drugs, nor is it a result of albumin-mediated hepatic drug uptake as currently hypothesized. Instead, the superior prediction power of the dWSM confirms the utility of the dynamic free fraction in clearance prediction and the importance of drug plasma binding kinetics in hepatic uptake clearance. SIGNIFICANCE STATEMENT: The traditional well-stirred model (WSM) consistently underpredicts organin anion-transporting polypeptide transporter (OATP)-mediated hepatic uptake clearance, hypothetically due to the albumin-mediated hepatic drug uptake. In this manuscript, we apply the dynamic WSM to extrapolate hepatic clearance of the OATP substrates, and our results show significant improvements in clearance prediction without assuming albumin-mediated hepatic drug uptake.

Uridine 5'-Diphospho-glucuronosyltransferase 1A3 (UGT1A3) Prediction of Hepatic Clearance of Organic Anion Transporting Polypeptide 1B3 (OATP1B3) Substrate Telmisartan by Glucuronidation Using In Vitro-In Vivo Extrapolation (IVIVE)

BACKGROUND AND OBJECTIVE

The prediction of pharmacokinetic parameters for drugs metabolised by cytochrome P450 enzymes has been the subject of active research for many years, while the application of in vitro-in vivo extrapolation (IVIVE) techniques for non-cytochrome P450 enzymes has not been thoroughly evaluated. There is still no established quantitative method for predicting hepatic clearance of drugs metabolised by uridine 5'-diphospho-glucuronosyltransferases (UGTs), not to mention those which undergo hepatic uptake. The objective of the study was to predict the human hepatic clearance for telmisartan based on in vitro metabolic stability and hepatic uptake results.

METHODS

Telmisartan was examined in liver systems, allowing to estimate intrinsic clearance (CLint, in vitro) based on the substrate disappearance rate with the use of liquid chromatography tandem mass spectrometry (LC-MS/MS) technique. Obtained CLint, in vitro values were corrected for corresponding unbound fractions. Prediction of human hepatic clearance was made from scaled unbound CLint, in vitro data with the use of the well-stirred model, and finally referenced to the literature value of observed clearance in humans, allowing determination of the essential scaling factors.

RESULTS

The in vitro scaled CLint, in vitro by UGT1A3 was assessed using three systems, human hepatocytes, liver microsomes, and recombinant enzymes. Obtained values were scaled and hepatic metabolism clearance was predicted, resulting in significant clearance underprediction. Utilization of the extended clearance concept (ECC) and hepatic uptake improved prediction of hepatic metabolism clearance. The scaling factors for hepatocytes, assessing the in vitro-in vivo difference, changed from sixfold difference to only twofold difference with the application of the ECC.

CONCLUSIONS

The study showed that taking into consideration hepatic uptake of a drug allows us to obtain satisfactory scaling factors, hence enabling the prediction of in vivo hepatic glucuronidation from in vitro data.

Introducing the Dynamic Well-Stirred Model for Predicting Hepatic Clearance and Extraction Ratio

The well-stirred model (WSM) incorporating the fraction of unbound drug (fu) to account for the effect of plasma binding on intrinsic clearance has been widely used for predicting hepatic clearance under the assumption that drug protein binding reaches equilibrium instantaneously. Our theoretical analysis reveals that the effect of protein binding on intrinsic clearance is better accounted for with the dynamic free fraction (fD), a measure of drug protein binding affinity, which leads to a putative dynamic well-stirred model (dWSM) without the instantaneous equilibrium assumption. Using recombinant CYP3A4 as the in vitro clearance system, we demonstrate that the binding effect of albumin on the intrinsic clearance of both highly bound midazolam and highly free verapamil is fully corrected by their corresponding fD values, respectively. On the other hand, fu only corrects the binding effect of albumin on the intrinsic clearance of verapamil, and yields severe over-correction of the intrinsic clearance of midazolam. The results suggest that the traditional WSM is suitable for highly free drugs like verapamil but not necessarily for highly bound drugs such as midazolam due to the violation of the instantaneous equilibrium assumption or under-estimating the true free drug concentration. In comparison, the dWSM incorporating fD holds true as long as drug elimination follows steady-state kinetics, and hence, it is more broadly applicable to drugs with different protein binding characteristics. Here we demonstrate with 36 diverse drugs, that the dWSM significantly improves the accuracy of predicting human hepatic clearance and liver extraction ratio from in vitro microsomal clearance data, highlighting the importance of drug plasma protein binding kinetics in addressing the under-prediction of hepatic clearance by the WSM.

Structure-Activity Relationship of a Pyrrole Based Series of PfPKG Inhibitors as Anti-Malarials

Controlling malaria requires new drugs against Plasmodium falciparum. The P. falciparum cGMP-dependent protein kinase (PfPKG) is a validated target whose inhibitors could block multiple steps of the parasite's life cycle. We defined the structure-activity relationship (SAR) of a pyrrole series for PfPKG inhibition. Key pharmacophores were modified to enable full exploration of chemical diversity and to gain knowledge about an ideal core scaffold. In vitro potency against recombinant PfPKG and human PKG were used to determine compound selectivity for the parasite enzyme. P. berghei sporozoites and P. falciparum asexual blood stages were used to assay multistage antiparasitic activity. Cellular specificity of compounds was evaluated using transgenic parasites expressing PfPKG carrying a substituted "gatekeeper" residue. The structure of PfPKG bound to an inhibitor was solved, and modeling using this structure together with computational tools was utilized to understand SAR and establish a rational strategy for subsequent lead optimization.

Quantitative prediction of transporter-mediated drug-drug interactions using the mechanistic static pharmacokinetic (MSPK) model

Guidance/guidelines on drug-drug interactions (DDIs) have been issued in Japan, the United States, and Europe. These guidance/guidelines provide decision trees for conducting metabolizing enzyme-mediated clinical DDI studies; however, the decision trees for transporter-mediated DDIs lack quantitative prediction methods. In this study, the accuracy of a net-effect mechanistic static pharmacokinetics (MSPK) model containing the fraction transported (ft) of transporters was examined to predict transporter-mediated DDIs. This study collected information on 25 oral drugs with new active reagents that were used in clinical DDI studies as perpetrators (42 cases) from drugs approved in Japan between April 2016 and June 2020. The AUCRs (AUC ratios with and without perpetrators) of victim drugs were predicted using the net-effect MSPK model. As a result, 83 and 95% of the predicted AUCRs were within 1.5- and 2-fold error in the observed AUCRs, respectively. In cases where the victims were statins in which pharmacokinetics several transporters are involved, 70 and 91% of the predicted AUCRs were within 1.5- and 2-fold errors, respectively. Therefore, the net-effect MSPK model was applicable for predicting the AUCRs of victims, which are substrates for multiple transporters.

Ticagrelor Increases Exposure to the Breast Cancer Resistance Protein Substrate Rosuvastatin

Ticagrelor and rosuvastatin are often used concomitantly after atherothrombotic events. Several cases of rhabdomyolysis during concomitant ticagrelor and rosuvastatin have been reported, suggesting a drug-drug interaction. We showed recently that ticagrelor inhibits breast cancer resistance protein (BCRP) and organic anion transporting polypeptide (OATP) 1B1, 1B3, and 2B1-mediated rosuvastatin transport in vitro. The aim of this study was to investigate the effects of ticagrelor on rosuvastatin pharmacokinetics in humans. In a randomized, crossover study, 9 healthy volunteers ingested a single dose of 90 mg ticagrelor or placebo, followed by a single 10 mg dose of rosuvastatin 1 hour later. Ticagrelor 90 mg or placebo were additionally administered 12, 24, and 36 hours after their first dose. Ticagrelor increased rosuvastatin area under the plasma concentration-time curve (AUC) and peak plasma concentration 2.6-fold (90% confidence intervals: 1.8-3.8 and 1.7-4.0, P = 0.001 and P = 0.003), and prolonged its half-life from 3.1 to 6.6 hours (P = 0.009). Ticagrelor also decreased the renal clearance of rosuvastatin by 11% (3%-19%, P = 0.032). The N-desmethylrosuvastatin:rosuvastatin AUC0-10h ratio remained unaffected by ticagrelor. Ticagrelor had no effect on the plasma concentrations of the endogenous OATP1B substrates glycodeoxycholate 3-O-glucuronide, glycochenodeoxycholate 3-O-glucuronide, glycodeoxycholate 3-O-sulfate, and glycochenodeoxycholate 3-O-sulfate, or the sodium-taurocholate cotransporting polypeptide substrate taurocholic acid. These data indicate that ticagrelor increases rosuvastatin concentrations more than twofold in humans, probably mainly by inhibiting intestinal BCRP. Because the risk for rosuvastatin-induced myotoxicity increases along with rosuvastatin plasma concentrations, using ticagrelor concomitantly with high doses of rosuvastatin should be avoided.

Preclinical Pharmacokinetics and Translational Pharmacokinetic/Pharmacodynamic Modeling of M8891, a Potent and Reversible Inhibitor of Methionine Aminopeptidase 2

INTRODUCTION

M8891 is a selective and reversible inhibitor of methionine aminopeptidase 2 (MetAP2). We describe translational research to define the target pharmacokinetics (PK) of M8891 and associated pharmacodynamic (PD) levels, which were used to support efficacious dose selection in humans.

METHODS

In vitro and in vivo PK characteristics were investigated in animal species, and data integrated using in vitro-in vivo correlation and allometric methods to predict the clearance, volume of distribution, and absorption parameters of M8891 in humans. In parallel, inhibition of MetAP2 activity by M8891 was studied in renal cancer xenografts in mice by measuring accumulation of Met-EF1α, a substrate of MetAP2. The corresponding PD effect was described by a turnover and effect compartment model. This model was used to simulate PD at the M8891 dose showing in vivo efficacy, i.e. significant tumor growth inhibition. Simulations of M8891 PK and associated PD in humans were conducted by integrating predicted human PK parameters into the preclinical PK/PD model.

RESULTS

The target minimum PD level associated with efficacy was determined to be 125 µg Met-EF1α per mg protein. Integrating predicted human PK parameters into the preclinical PK/PD model defined a minimal M8891 concentration at steady-state (Ctrough) of 1500 ng/mL (3.9 µM) in humans as being required to produce the corresponding minimum target Met-EF1a level (125 µg per mg protein).

CONCLUSION

The defined target PK and PD levels supported the design of the clinical Phase Ia dose escalation study of M8891 (NCT03138538) and selection of the recommended Phase II dose.

Using Prior Knowledge on Systems Through PBPK to Gain Further Insight into Routine Clinical Data on Trough Concentrations: The Case of Tacrolimus in Chronic Kidney Disease

BACKGROUND

Routine therapeutic drug monitoring (TDM) relies heavily on measuring trough drug concentrations. Trough concentrations are affected not only by drug bioavailability and clearance, but also by various patient and disease factors and the volume of distribution. This often makes interpreting differences in drug exposure from trough data challenging. This study aimed to combine the advantages of top-down analysis of therapeutic drug monitoring data with bottom-up physiologically-based pharmacokinetic (PBPK) modeling to investigate the effect of declining renal function in chronic kidney disease (CKD) on the nonrenal intrinsic metabolic clearance ( CLint ) of tacrolimus as a case example.

METHODS

Data on biochemistry, demographics, and kidney function, along with 1167 tacrolimus trough concentrations for 40 renal transplant patients, were collected from the Salford Royal Hospital's database. A reduced PBPK model was developed to estimate CLint for each patient. Personalized unbound fractions, blood-to-plasma ratios, and drug affinities for various tissues were used as priors to estimate the apparent volume of distribution. Kidney function based on the estimated glomerular filtration rate ( eGFR ) was assessed as a covariate for CLint using the stochastic approximation of expectation and maximization method.

RESULTS

At baseline, the median (interquartile range) eGFR was 45 (34.5-55.5) mL/min/1.73 m 2 . A significant but weak correlation was observed between tacrolimus CLint and eGFR (r = 0.2, P < 0.001). The CLint declined gradually (up to 36%) with CKD progression. Tacrolimus CLint did not differ significantly between stable and failing transplant patients.

CONCLUSIONS

Kidney function deterioration in CKD can affect nonrenal CLint for drugs that undergo extensive hepatic metabolism, such as tacrolimus, with critical implications in clinical practice. This study demonstrates the advantages of combining prior system information (via PBPK) to investigate covariate effects in sparse real-world datasets.

Dolutegravir pharmacokinetics in Ugandan patients with TB and HIV receiving standard- versus high-dose rifampicin

Higher rifampicin doses may improve tuberculosis treatment outcomes. This could however exacerbate the existing drug interaction with dolutegravir. Moreover, the metabolism of dolutegravir may also be affected by polymorphism of UGT1A1, a gene that codes for uridine diphosphate glucuronosyltransferase. We used population pharmacokinetic modeling to compare the pharmacokinetics of dolutegravir when coadministered with standard- versus high-dose rifampicin in adults with tuberculosis and HIV, and investigated the effect of genetic polymorphisms. Data from the SAEFRIF trial, where participants were randomized to receive first-line tuberculosis treatment with either standard- 10 mg/kg or high-dose 35 mg/kg rifampicin alongside antiretroviral therapy, were used. The dolutegravir model was developed with 211 plasma concentrations from 44 participants. The median (interquartile range) rifampicin area under the curve (AUC) in the standard- and high-dose arms were 32.3 (28.7-36.7) and 153 (138-175) mg·h/L, respectively. A one-compartment model with first-order elimination and absorption through transit compartments best described dolutegravir pharmacokinetics. For a typical 56 kg participant, we estimated a clearance, absorption rate constant, and volume of distribution of 1.87 L/h, 1.42 h-1, and 12.4 L, respectively. Each 10 mg·h/L increase in the AUC of coadministered rifampicin from 32.3 mg·h/L led to a 2.3 (3.1-1.4) % decrease in dolutegravir bioavailability. Genetic polymorphism of UGT1A1 did not significantly affect dolutegravir pharmacokinetics. Simulations of trough dolutegravir concentrations show that the 50 mg twice-daily regimen attains both the primary and secondary therapeutic targets of 0.064 and 0.3 mg/L, respectively, regardless of the dose of coadministered rifampicin, unlike the once-daily regimen.

Hydroxychloroquine is Metabolized by Cytochrome P450 2D6, 3A4, and 2C8, and Inhibits Cytochrome P450 2D6, while its Metabolites also Inhibit Cytochrome P450 3A in vitro

This study aimed to explore the cytochrome P450 (CYP) metabolic and inhibitory profile of hydroxychloroquine (HCQ). Hydroxychloroquine metabolism was studied using human liver microsomes (HLMs) and recombinant CYP enzymes. The inhibitory effects of HCQ and its metabolites on nine CYPs were also determined in HLMs, using an automated substrate cocktail method. Our metabolism data indicated that CYP3A4, CYP2D6, and CYP2C8 are the key enzymes involved in HCQ metabolism. All three CYPs formed the primary metabolites desethylchloroquine (DCQ) and desethylhydroxychloroquine (DHCQ) to various degrees. Although the intrinsic clearance (CL_int) value of HCQ depletion by recombinant CYP2D6 was > 10-fold higher than that by CYP3A4 (0.87 versus 0.075 µl/min/pmol), scaling of recombinant CYP CL_int to HLM level resulted in almost equal HLM CL_int values for CYP2D6 and CYP3A4 (11 and 14 µl/min/mg, respectively). The scaled HLM CL_int of CYP2C8 was 5.7 µl/min/mg. Data from HLM experiments with CYP-selective inhibitors also suggested relatively equal roles for CYP2D6 and CYP3A4 in HCQ metabolism, with a smaller contribution by CYP2C8. In CYP inhibition experiments, HCQ, DCQ, DHCQ, and the secondary metabolite didesethylchloroquine were direct CYP2D6 inhibitors, with 50% inhibitory concentration (IC₅₀) values between 18 and 135 µM. HCQ did not inhibit other CYPs. Furthermore, all metabolites were time-dependent CYP3A inhibitors (IC₅₀ shift 2.2-3.4). To conclude, HCQ is metabolized by CYP3A4, CYP2D6, and CYP2C8 in vitro. HCQ and its metabolites are reversible CYP2D6 inhibitors, and HCQ metabolites are time-dependent CYP3A inhibitors. These data can be used to improve physiologically-based pharmacokinetic models and update drug-drug interaction risk estimations for HCQ. SIGNIFICANCE STATEMENT: While CYP2D6, CYP3A4, and CYP2C8 have been shown to mediate chloroquine biotransformation, it appears that the role of CYP enzymes in hydroxychloroquine (HCQ) metabolism has not been studied. In addition, little is known about the CYP inhibitory effects of HCQ. Here, we demonstrate that CYP2D6, CYP3A4, and CYP2C8 are the key enzymes involved in HCQ metabolism. Furthermore, our findings show that HCQ and its metabolites are inhibitors of CYP2D6, which likely explains the previously observed interaction between HCQ and metoprolol.

Contribution of UGT Enzymes to Human Drug Metabolism Stereoselectivity: A Case Study of Medetomidine, RO5263397, Propranolol, and Testosterone

The enantiomeric forms of chiral compounds have identical physical properties but may vary greatly in their metabolism by individual enzymes. Enantioselectivity in UDP-glucuronosyl transferase (UGT) metabolism has been reported for a number of compounds and with different UGT isoforms involved. However, the impact of such individual enzyme results on overall clearance stereoselectivity is often not clear. The enantiomers of medetomidine, RO5263397, and propranolol and the epimers testosterone and epitestosterone exhibit more than a 10-fold difference in glucuronidation rates by individual UGT enzymes. In this study, we examined the translation of human UGT stereoselectivity to hepatic drug clearance considering the combination of multiple UGTs to overall glucuronidation, the contribution of other metabolic enzymes such as cytochrome P450s (P450s), and the potential for differences in protein binding and blood/plasma partitioning. For medetomidine and RO5263397, the high individual enzyme (UGT2B10) enantioselectivity translated into ∼3- to >10-fold differences in predicted human hepatic in vivo clearance. For propranolol, the UGT enantioselectivity was irrelevant in the context of high P450 metabolism. For testosterone, a complex picture emerged due to differential epimeric selectivity of various contributing enzymes and potential for extrahepatic metabolism. Quite different patterns of P450- and UGT-mediated metabolism were observed across species, as well as differences in stereoselectivity, indicating that extrapolation from human enzyme and tissue data are essential when predicting human clearance enantioselectivity. SIGNIFICANCE STATEMENT: Individual enzyme stereoselectivity illustrates the importance of three-dimensional drug-metabolizing enzyme-substrate interactions and is essential when considering the clearance of racemic drugs. However, translation from in vitro to in vivo can be challenging as contributions from multiple enzymes and enzyme classes must be combined with protein binding and blood/plasma partitioning data to estimate the net intrinsic clearance for each enantiomer. Preclinical species may be misleading as enzyme involvement and metabolism stereoselectivity can differ substantially.

A Physiological-Based Pharmacokinetic Model Embedded with a Target-Mediated Drug Disposition Mechanism Can Characterize Single-Dose Warfarin Pharmacokinetic Profiles in Subjects with Various CYP2C9 Genotypes under Different Cotreatments

Warfarin, a commonly prescribed oral anticoagulant medication, is highly effective in treating deep vein thrombosis and pulmonary embolism. However, the clinical dosing of warfarin is complicated by high interindividual variability in drug exposure and response and its narrow therapeutic index. CYP2C9 genetic polymorphism and drug-drug interactions (DDIs) are substantial contributors to this high variability of warfarin pharmacokinetics (PK), among numerous factors. Building a physiology-based pharmacokinetic (PBPK) model for warfarin is not only critical for a mechanistic characterization of warfarin PK but also useful for investigating the complicated dose-exposure relationship of warfarin. Thus, the objective of this study was to develop a PBPK model for warfarin that integrates information regarding CYP2C9 genetic polymorphisms and their impact on DDIs. Generic PBPK models for both S- and R-warfarin, the two enantiomers of warfarin, were constructed in R with the mrgsolve package. As expected, a generic PBPK model structure did not adequately characterize the warfarin PK profile collected up to 15 days following the administration of a single oral dose of warfarin, especially for S-warfarin. However, following the integration of an empirical target-mediated drug disposition (TMDD) component, the PBPK-TMDD model well characterized the PK profiles collected for both S- and R-warfarin in subjects with different CYP2C9 genotypes. Following the integration of enzyme inhibition and induction effects, the PBPK-TMDD model also characterized the PK profiles of both S- and R-warfarin in various DDI settings. The developed mathematic framework may be useful in building algorithms to better inform the clinical dosing of warfarin. SIGNIFICANCE STATEMENT: The present study found that a traditional physiology-based pharmacokinetic (PBPK) model cannot sufficiently characterize the pharmacokinetic profiles of warfarin enantiomers when warfarin is administered as a single dose, but a PBPK model with a target-mediated drug disposition mechanism can. After incorporating CYP2C9 genotypes and drug-drug interaction information, the developed model is anticipated to facilitate the understanding of warfarin disposition in subjects with different CYP2C9 genotypes in the absence and presence of both cytochrome P450 inhibitors and cytochrome P450 inducers.

Interspecies evaluation of a physiologically based pharmacokinetic model to predict the biodistribution dynamics of dendritic nanoparticles

The exposure of a dendritic nanoparticle and its conjugated active pharmaceutical ingredient (API) was determined in mouse, rat and dog, with the aim of investigating interspecies differences facilitating clinical translation. Plasma area under the curves (AUCs) were found to be dose proportional across species, while dose normalized concentration time course profiles in plasma, liver and spleen were superimposable in mouse, rat and dog. A physiologically based pharmacokinetic (PBPK) model, previously developed for mouse, was evaluated as a suitable framework to prospectively capture concentration dynamics in rat and dog. The PBPK model, parameterized either by considering species-specific physiology or using alternate scaling methods such as allometry, was shown to capture exposure profiles across species. A sensitivity analysis highlighted API systemic clearance as a key parameter influencing released API levels. The PBPK model was utilized to simulate human exposure profiles, which overlaid dose-normalized data from mouse, rat and dog. The consistency in measured interspecies exposures as well as the capability of the PBPK model to simulate observed dynamics support its use as a powerful translational tool.

Development, testing, parameterisation, and calibration of a human PBPK model for the plasticiser, di-(2-ethylhexyl) terephthalate (DEHTP) using in silico, in vitro and human biomonitoring data

A physiologically based pharmacokinetic model for di-(2-ethylhexyl) terephthalate (DEHTP) based on a refined model for di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the metabolism and biokinetics of DEHTP following a single oral dose of 50 mg to three male volunteers. In vitro and in silico methods were used to generate parameters for the model. For example, measured intrinsic hepatic clearance scaled from in vitro to in vivo and plasma unbound fraction and tissue:blood partition coefficients (PCs) were predicted algorithmically. Whereas the development and calibration of the DPHP model was based upon two data streams, blood concentrations of parent chemical and first metabolite and the urinary excretion of metabolites, the model for DEHTP was calibrated against a single data stream, the urinary excretion of metabolites. Despite the model form and structure being identical significant quantitative differences in lymphatic uptake between the models were observed. In contrast to DPHP the fraction of ingested DEHTP entering lymphatic circulation was much greater and of a similar magnitude to that entering the liver with evidence for the dual uptake mechanisms discernible in the urinary excretion data. Further, the absolute amounts absorbed by the study participants, were much higher for DEHTP relative to DPHP. The in silico algorithm for predicting protein binding performed poorly with an error of more than two orders of magnitude. The extent of plasma protein binding has important implications for the persistence of parent chemical in venous blood-inferences on the behaviour of this class of highly lipophilic chemicals, based on calculations of chemical properties, should be made with extreme caution. Attempting read across for this class of highly lipophilic chemicals should be undertaken with caution since basic adjustments to PCs and metabolism parameters would be insufficient, even when the structure of the model itself is appropriate. Therefore, validation of a model parameterized entirely with in vitro and in silico derived parameters would need to be calibrated against several human biomonitoring data streams to constitute a data rich source chemical to afford confidence for future evaluations of other similar chemicals using the read-across approach.

Can We Predict Clinical Pharmacokinetics of Highly Lipophilic Compounds by Integration of Machine Learning or In Vitro Data into Physiologically Based Models? A Feasibility Study Based on 12 Development Compounds

While high lipophilicity tends to improve potency, its effects on pharmacokinetics (PK) are complex and often unfavorable. To predict clinical PK in early drug discovery, we built human physiologically based PK (PBPK) models integrating either (i) machine learning (ML)-predicted properties or (ii) discovery stage in vitro data. Our test set was composed of 12 challenging development compounds with high lipophilicity (mean calculated log P 4.2), low plasma-free fraction (50% of compounds with fu,p < 1%), and low aqueous solubility. Predictions focused on key human PK parameters, including plasma clearance (CL), volume of distribution at steady state (V_ss), and oral bioavailability (%F). For predictions of CL, the ML inputs showed acceptable accuracy and slight underprediction bias [an average absolute fold error (AAFE) of 3.55; an average fold error (AFE) of 0.95]. Surprisingly, use of measured data only slightly improved accuracy but introduced an overprediction bias (AAFE = 3.35; AFE = 2.63). Predictions of V_ss were more successful, with both ML (AAFE = 2.21; AFE = 0.90) and in vitro (AAFE = 2.24; AFE = 1.72) inputs showing good accuracy and moderate bias. The %F was poorly predicted using ML inputs [average absolute prediction error (AAPE) of 45%], and use of measured data for solubility and permeability improved this to 34%. Sensitivity analysis showed that predictions of CL limited the overall accuracy of human PK predictions, partly due to high nonspecific binding of lipophilic compounds, leading to uncertainty of unbound clearance. For accurate predictions of %F, solubility was the key factor. Despite current limitations, this work encourages further development of ML models and integration of their results within PBPK models to enable human PK prediction at the drug design stage, even before compounds are synthesized. Further evaluation of this approach with more diverse chemical types is warranted.

SimRFlow: An R-based workflow for automated high-throughput PBPK simulation with the Simcyp® simulator

SimRFlow is a high-throughput physiologically based pharmacokinetic (PBPK) modelling tool which uses Certara’s Simcyp® simulator. The workflow is comprised of three main modules: 1) a Data Collection module for automated curation of physicochemical (from ChEMBL and the Norman Suspect List databases) and experimental data (i.e.: clearance, plasma-protein binding, and blood-to-plasma ratio, from httk-R package databases), 2) a Simulation module which activates the Simcyp® simulator and runs Monte Carlo simulations on virtual subjects using the curated data, and 3) a Data Visualisation module for understanding the simulated compound-specific profiles and predictions. SimRFlow has three administration routes (oral, intravenous, dermal) and allows users to change some simulation parameters including the number of subjects, simulation duration, and dosing. Users are only expected to provide a file of the compounds they wish to simulate, and in return the workflow provides summary statistics, concentration-time profiles of various tissue types, and a database file (containing in-depth results) for each simulated compound. This is presented within a guided and easy-to-use R Shiny interface which provides many plotting options for the visualisation of concentration-time profiles, parameter distributions, trends between the different parameters, as well as comparison of predicted parameters across all batch-simulated compounds. The in-built R functions can be assembled in user-customised scripts which allows for the modification of the workflow for different purposes. SimRFlow proves to be a time-efficient tool for simulating a large number of compounds without any manual curation of physicochemical or experimental data necessary to run Simcyp® simulations.

Pharmacokinetics of standard versus high-dose isoniazid for treatment of multidrug-resistant tuberculosis

BACKGROUND

The WHO-endorsed shorter-course regimen for MDR-TB includes high-dose isoniazid. The pharmacokinetics of high-dose isoniazid within MDR-TB regimens has not been well described.

OBJECTIVES

To characterize isoniazid pharmacokinetics at 5-15 mg/kg as monotherapy or as part of the MDR-TB treatment regimen.

METHODS

We used non-linear mixed-effects modelling to evaluate the combined data from INHindsight, a 7 day early bactericidal activity study with isoniazid monotherapy, and PODRtb, an observational study of patients on MDR-TB treatment including terizidone, pyrazinamide, moxifloxacin, kanamycin, ethionamide and/or isoniazid.

RESULTS

A total of 58 and 103 participants from the INHindsight and PODRtb studies, respectively, were included in the analysis. A two-compartment model with hepatic elimination best described the data. N-acetyltransferase 2 (NAT2) genotype caused multi-modal clearance, and saturable first-pass was observed beyond 10 mg/kg dosing. Saturable isoniazid kinetics predicted an increased exposure of approximately 50% beyond linearity at 20 mg/kg dosing. Participants treated with the MDR-TB regimen had a 65.6% lower AUC compared with participants on monotherapy. Ethionamide co-administration was associated with a 29% increase in isoniazid AUC.

CONCLUSIONS

Markedly lower isoniazid exposures were observed in participants on combination MDR-TB treatment compared with monotherapy. Isoniazid displays saturable kinetics at doses >10 mg/kg. The safety implications of these phenomena remain unclear.

Drug clearance by aldehyde oxidase: can we avoid clinical failure?

Despite increased awareness of aldehyde oxidase (AO) as a major drug-metabolising enzyme, predicting the pharmacokinetics of its substrates remains challenging. Several drug candidates have been terminated due to high clearance, which were subsequently discovered to be AO substrates. Even retrospective extrapolation of human clearance, from models more sensitive to AO activity, often resulted in underprediction.The questions of the current work thus were: Is there an acceptable degree of in vitro AO metabolism that does not result in high in vivo human clearance? And, if so, how can this be predicted?We built an in vitro/in vivo correlation using known AO substrates, combining multiple in vitro parameters to calculate the blood metabolic clearance mediated by AO (CLb_AO). This value was compared with observed blood clearance (CLb_-obs), establishing cut-off CLb_AO values, to discriminate between low and high CLb_-obs. The model was validated using additional literature compounds, and CLb_-obs was predicted in the correct category.This simple, categorical, semi-quantitative yet multi-factorial model is readily applicable in drug discovery. Further, it is valuable for high-clearance compounds, as it predicts the CLb group, rather than an exact CLb value, for the substrates of this poorly-characterised enzyme.

SAR Probing of KX2-391 Provided Analogues With Juxtaposed Activity Profile Against Major Oncogenic Kinases

Tirbanibulin (KX2-391, KX-01), a dual non-ATP (substrate site) Src kinase and tubulin-polymerization inhibitor, demonstrated a universal anti-cancer activity for variety of cancer types. The notion that KX2-391 is a highly selective Src kinase inhibitor have been challenged by recent reports on the activities of this drug against FLT3-ITD mutations in some leukemic cell lines. Therefore, we hypothesized that analogues of KX2-391 may inhibit oncogenic kinases other than Src. A set of 4-aroylaminophenyl-N-benzylacetamides were synthesized and found to be more active against leukemia cell lines compared to solid tumor cell lines. N-(4-(2-(benzylamino)-2-oxoethyl)phenyl)-4-chlorobenzamide (4e) exhibited activities at IC₅₀ 0.96 µM, 1.62 µM, 1.90 µM and 4.23 µM against NB4, HL60, MV4-11 and K562 leukemia cell lines, respectively. We found that underlying mechanisms of 4e did not include tubulin polymerization or Src inhibition. Such results interestingly suggested that scaffold-hopping of KX2-391 may change the two main underlying cytotoxic mechanisms (Src and tubulin). Kinase profiling using two methods revealed that 4e significantly reduces the activities of some other potent oncogenic kinases like the MAPK member ERK1/2 (>99%) and it also greatly upregulates the pro-apoptotic c-Jun kinase (84%). This research also underscores the importance of thorough investigation of total kinase activities as part of the structure-activity relationship studies.

Prediction of Pharmacokinetics of IDP-73152 in Humans Using Physiologically-Based Pharmacokinetics

IDP-73152, a novel peptide deformylase inhibitor with an antibacterial effect against Gram-positive bacteria, is in phase I development. The objective of this study was to develop a physiologically-based pharmacokinetic model (PBPK) for IDP-73152 in animals, and to extend the model to humans. Biopharmaceutical properties of IDP-73152 are determined using in vitro/in vivo experimentations for the PBPK model. A transit model consisting of gastrointestinal segments is applied for an estimation of the intestinal absorption kinetics. The PBPK model of IDP-73152 in rats is able to appropriately predict the plasma concentration–time profiles after the administration of IDP-73152 at different doses and by different routes (combined absolute average fold error (cAAFE), 1.77). The model is also found to be adequate in predicting the plasma concentration–time profiles of IDP-73152 in mice (cAAFE 1.59) and dogs (cAAFE 1.42). Assuming the oral administration of IDP-73152 to humans at doses of 640 and 1280 mg, the model is able to reproduce the concentration–time profiles obtained in humans (cAAFE 1.38); therefore, these observations indicate that the PBPK model used for IDP-73152 is applicable to animal species and humans. This model may be useful in predicting efficacious doses of IDP-73152 for the management of infectious disease in humans.

Identification and Strategies to Mitigate High Total Clearance of Benzylamine-Substituted Biphenyl Ring Systems

For most oral small-molecule projects within drug discovery, the extent and duration of the effect are influenced by the total clearance of the compound; hence, designing compounds with low clearance remains a key focus to help enable sufficient protein target engagement. Comprehensive understanding and accurate prediction of animal clearance and pharmacokinetics provides confidence that the same can be observed for human. During a MERTK inhibitor lead optimization project, a series containing a biphenyl ring system with benzylamine meta-substitution on one phenyl and nitrogen inclusion as the meta atom on the other ring demonstrated multiple routes of compound elimination in rats. Here, we describe the identification of a structural pharmacophore involving two key interactions observed for both the MERTK program and an additional internal project. Four strategies to mitigate these clearance liabilities were identified and systematically investigated. We provide evidence that disruption of at least one of the interactions led to a significant reduction in CL that was subsequently predicted from rat hepatocytes using in vitro/in vivo extrapolation and the well-stirred scaling method. These tactics will likely be of general utility to the medicinal chemistry and DMPK community during compound optimization when similar issues are encountered for biphenyl benzylamines.

Exploration of the Plausible Mechanism of Ethambutol Induced Ocular Toxicity by Using Proteomics Informed Physiologically Based Pharmacokinetic (PBPK) Modeling

PURPOSE

Ethambutol (EMB) is a first-line anti-tubercular drug that is known to cause optic neuropathy. The exact mechanism of its eye toxicity is unknown; however, proposition is metal chelating effect of both EMB and its metabolite 2,2'-(ethylenediamino)-dibutyric acid (EDBA). The latter is formed by sequential metabolism of EMB by alcohol dehydrogenases (ADHs) and aldehyde dehydrogenases (ALDHs). The purpose of this study was to predict the levels of drug and EDBA in the eye using physiologically based pharmacokinetic (PBPK) modeling.

METHODS

The PBPK model of EMB was developed using GastroPlus. The intrinsic hepatic clearance of ALDH, calculated by the model, was scaled down using proteomics data to estimate the rate of formation of EDBA in the eye. Additionally, the comparative permeability of EMB and EDBA was assessed by employing in silico and in vitro approaches. The rate of formation of EDBA in the eye and permeability data were then incorporated in a compartmental model to predict the ocular levels of EMB and EDBA.

RESULTS

The simulation results of compartmental model highlighted that there was an on-site formation of EDBA upon metabolism of EMB. Furthermore, in silico and in vitro studies revealed that EDBA possessed much lower permeability than EMB. These observations meant that once EDBA was formed in the eye, it was not permeated out and hence achieved higher ocular concentration.

CONCLUSION

The on-site formation of EDBA in the eye, its higher local concentration due to lower ocular clearance and its pre-known characteristic to chelate metal species better explains the ocular toxicity shown by EMB.

Clinical Pharmacokinetic Assessment of Kratom (Mitragyna speciosa), a Botanical Product with Opioid-like Effects, in Healthy Adult Participants

Increasing use of the botanical kratom to self-manage opioid withdrawal and pain has led to increased kratom-linked overdose deaths. Despite these serious safety concerns, rigorous fundamental pharmacokinetic knowledge of kratom in humans remains lacking. We assessed the pharmacokinetics of a single low dose (2 g) of a well-characterized kratom product administered orally to six healthy participants. Median concentration-time profiles for the kratom alkaloids examined were best described by a two-compartment model with central elimination. Pronounced pharmacokinetic differences between alkaloids with the 3S configuration (mitragynine, speciogynine, paynantheine) and alkaloids with the 3R configuration (mitraciliatine, speciociliatine, isopaynantheine) were attributed to differences in apparent intercompartmental distribution clearance, volumes of distribution, and clearance. Based on noncompartmental analysis of individual concentration-time profiles, the 3S alkaloids exhibited a shorter median time to maximum concentration (1–2 vs. 2.5–4.5 h), lower area under the plasma concentration-time curve (430–490 vs. 794–5120 nM × h), longer terminal half-life (24–45 vs. ~12–18 h), and higher apparent volume of distribution during the terminal phase (960–12,700 vs. ~46–130 L) compared to the 3R alkaloids. Follow-up mechanistic in vitro studies suggested differential hepatic/intestinal metabolism, plasma protein binding, blood-to-plasma partitioning, and/or distribution coefficients may explain the pharmacokinetic differences between the two alkaloid types. This first comprehensive pharmacokinetic characterization of kratom alkaloids in humans provides the foundation for further research to establish safety and effectiveness of this emerging botanical product.

Towards the Elucidation of the Pharmacokinetics of Voriconazole: A Quantitative Characterization of Its Metabolism

The small-molecule drug voriconazole (VRC) shows a complex and not yet fully understood metabolism. Consequently, its in vivo pharmacokinetics are challenging to predict, leading to therapy failures or adverse events. Thus, a quantitative in vitro characterization of the metabolism and inhibition properties of VRC for human CYP enzymes was aimed for. The Michaelis-Menten kinetics of voriconazole N-oxide (NO) formation, the major circulating metabolite, by CYP2C19, CYP2C9 and CYP3A4, was determined in incubations of human recombinant CYP enzymes and liver and intestine microsomes. The contribution of the individual enzymes to NO formation was 63.1% CYP2C19, 13.4% CYP2C9 and 29.5% CYP3A4 as determined by specific CYP inhibition in microsomes and intersystem extrapolation factors. The type of inhibition and inhibitory potential of VRC, NO and hydroxyvoriconazole (OH-VRC), emerging to be formed independently of CYP enzymes, were evaluated by their effects on CYP marker reactions. Time-independent inhibition by VRC, NO and OH-VRC was observed on all three enzymes with NO being the weakest and VRC and OH-VRC being comparably strong inhibitors of CYP2C9 and CYP3A4. CYP2C19 was significantly inhibited by VRC only. Overall, the quantitative in vitro evaluations of the metabolism contributed to the elucidation of the pharmacokinetics of VRC and provided a basis for physiologically-based pharmacokinetic modeling and thus VRC treatment optimization.

Insights on Cancer Cell Inhibition, Subcellular Activities, and Kinase Profile of Phenylacetamides Pending 1H-Imidazol-5-One Variants

Structural changes of small-molecule drugs may bring interesting biological properties, especially in the field of kinase inhibitors. We sought to study tirbanibulin, a first-in-class dual Src kinase (non-ATP competitive)/tubulin inhibitor because there was not enough reporting about its structure–activity relationships (SARs). In particular, the present research is based on the replacement of the outer ring of the biphenyl system of 2-[(1,1′-biphenyl)-4-yl]-N-benzylacetamide, the identified pharmacophore of KX chemotype, with a heterocyclic ring. The newly synthesized compounds showed a range of activities in cell-based anticancer assays, agreeing with a clear SAR profile. The most potent compound, (Z)-N-benzyl-4-[4-(4-methoxybenzylidene)-2-methyl-5-oxo-4,5-dihydro-1H-imidazol-1-yl]phenylacetamide (KIM-161), demonstrated cytotoxic IC₅₀ values at 294 and 362 nM against HCT116 colon cancer and HL60 leukemia cell lines, respectively. Profiling of this compound (aqueous solubility, liver microsomal stability, cytochrome P450 inhibition, reactivity with reduced glutathione, and plasma protein binding) confirmed its adequate drug-like properties. Mechanistic studies revealed that this compound does not depend on tubulin or Src kinase inhibition as a factor in forcing HL60 to exit its cell cycle and undergo apoptosis. Instead, KIM-161 downregulated several other kinases such as members of BRK, FLT, and JAK families. It also strongly suppresses signals of ERK1/2, GSK-3α/β, HSP27, and STAT2, while it downregulated AMPKα1 phosphorylation within the HL60 cells. Collectively, these results suggest that phenylacetamide-1H-imidazol-5-one (KIM-161) could be a promising lead compound for further clinical anticancer drug development.

The blood-to-plasma ratio and predicted GABAA-binding affinity of designer benzodiazepines

PURPOSE

The number of benzodiazepines appearing as new psychoactive substances (NPS) is continually increasing. Information about the pharmacological parameters of these compounds is required to fully understand their potential effects and harms. One parameter that has yet to be described is the blood-to-plasma ratio. Knowledge of the pharmacodynamics of designer benzodiazepines is also important, and the use of quantitative structure-activity relationship (QSAR) modelling provides a fast and inexpensive method of predicting binding affinity to the GABA_A receptor.

METHODS

In this work, the blood-to-plasma ratios for six designer benzodiazepines (deschloroetizolam, diclazepam, etizolam, meclonazepam, phenazepam, and pyrazolam) were determined. A previously developed QSAR model was used to predict the binding affinity of nine designer benzodiazepines that have recently appeared.

RESULTS

Blood-to-plasma values ranged from 0.57 for phenazepam to 1.18 to pyrazolam. Four designer benzodiazepines appearing since 2017 (fluclotizolam, difludiazepam, flualprazolam, and clobromazolam) had predicted binding affinities to the GABA_A receptor that were greater than previously predicted binding affinities for other designer benzodiazepines.

CONCLUSIONS

This work highlights the diverse nature of the designer benzodiazepines and adds to our understanding of their pharmacology. The greater predicted binding affinities are a potential indication of the increasing potency of designer benzodiazepines appearing on the illicit drugs market.

Physiologically-based pharmacokinetic modeling to predict CYP3A4-mediated drug-drug interactions of finerenone

Finerenone is a nonsteroidal, selective mineralocorticoid receptor antagonist that recently demonstrated its efficacy to delay chronic kidney disease (CKD) progression and reduce cardiovascular events in patients with CKD and type 2 diabetes. Here, we report the development of a physiologically‐based pharmacokinetic (PBPK) model for finerenone and its application as a victim drug of cytochrome P450 3A4 (CYP3A4)‐mediated drug‐drug interactions (DDIs) using the open‐source PBPK platform PK‐Sim, which has recently been qualified for this application purpose. First, the PBPK model for finerenone was developed using physicochemical, in vitro, and clinical (including mass balance) data. Subsequently, the finerenone model was validated regarding the contribution of CYP3A4 metabolism to total clearance by comparing to observed data from dedicated clinical interaction studies with erythromycin (simulated geometric mean ratios of the area under the plasma concentration‐time curve [AUCR] of 3.46 and geometric mean peak plasma concentration ratios [C_maxRs] of 2.00 vs. observed of 3.48 and 1.88, respectively) and verapamil (simulated AUCR of 2.91 and C_maxR of 1.86 vs. observed of 2.70 and 2.22, respectively). Finally, the finerenone model was applied to predict clinically untested DDI studies with various CYP3A4 modulators. An AUCR of 6.31 and a C_maxR of 2.37 was predicted with itraconazole, of 5.28 and 2.25 with clarithromycin, 1.59 and 1.40 with cimetidine, 1.57 and 1.38 with fluvoxamine, 0.19 and 0.32 with efavirenz, and 0.07 and 0.14 with rifampicin. This PBPK analysis provides a quantitative basis to guide the label and clinical use of finerenone with concomitant CYP3A4 modulators.

Discovery and Optimization of Orally Bioavailable Phthalazone and Cinnolone Carboxylic Acid Derivatives as S1P2 Antagonists against Fibrotic Diseases

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung disease. Current treatments only slow down disease progression, making new therapeutic strategies compelling. Increasing evidence suggests that S1P2 antagonists could be effective agents against fibrotic diseases. Our compound collection was mined for molecules possessing substructure features associated with S1P2 activity. The weakly potent indole hit 6 evolved into a potent phthalazone series, bearing a carboxylic acid, with the aid of a homology model. Suboptimal pharmacokinetics of a benzimidazole subseries were improved by modifications targeting potential interactions with transporters, based on concepts deriving from the extended clearance classification system (ECCS). Scaffold hopping, as a part of a chemical enablement strategy, permitted the rapid exploration of the position adjacent to the carboxylic acid. Compound 38, with good pharmacokinetics and in vitro potency, was efficacious at 10 mg/kg BID in three different in vivo mouse models of fibrotic diseases in a therapeutic setting.

PBK Model-Based Prediction of Intestinal Microbial and Host Metabolism of Zearalenone and Consequences for its Estrogenicity

Scope

The aim of the present study is to develop physiologically‐based kinetic (PBK) models for rat and human that include intestinal microbial and hepatic metabolism of zearalenone (ZEN) in order to predict systemic concentrations of ZEN and to obtain insight in the contribution of metabolism by the intestinal microbiota to the overall metabolism of ZEN.

Methods and Results

In vitro derived kinetic parameters, apparent maximum velocities (V_max) and Michaelis–Menten constants (K_m) for liver and intestinal microbial metabolism of ZEN are included in the PBK models. The models include a sub‐model for the metabolite, α‐zearalenol (α‐ZEL), a metabolite known to be 60‐times more potent as an estrogen than ZEN. Integrating intestinal microbial ZEN metabolism into the PBK models revealed that hepatic metabolism drives the formation of α‐ZEL. Furthermore, the models predicted that at the tolerable daily intake (TDI) of 0.25 µg kg⁻¹ bw the internal concentration of ZEN and α‐ZEL are three‐orders of magnitude below concentrations reported to induce estrogenicity in vitro.

Conclusion

It is concluded that combining kinetic data on liver and intestinal microbial metabolism in a PBK model facilitates a holistic view on the role of the intestinal microbiota in the overall metabolism of the foodborne xenobiotic ZEN and its bioactivation to α‐ZEL.

Development, Testing, Parameterisation and Calibration of a Human PBPK Model for the Plasticiser, Di-(2-propylheptyl) Phthalate (DPHP) Using in Silico, in vitro and Human Biomonitoring Data

A physiologically based pharmacokinetic model for Di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the biokinetics in humans after single oral doses. The model was parameterized with in vitro and in silico derived parameters and uncertainty and sensitivity analysis was used during the model development process to assess structure, biological plausibility and behaviour prior to simulation and analysis of human biological monitoring data. To provide possible explanations for some of the counter-intuitive behaviour of the biological monitoring data the model included a simple lymphatic uptake process for DPHP and enterohepatic recirculation (EHR) for DPHP and the mono ester metabolite mono-(2-propylheptyl) phthalate (MPHP). The model was used to simultaneously simulate the concentration-time profiles of blood DPHP, MPHP and the urinary excretion of two metabolites, mono-(2-propyl-6-hydroxyheptyl) phthalate (OH-MPHP) and mono-(2-propyl-6-carboxyhexyl) phthalate (cx-MPHP). The availability of blood and urine measurements permitted a more robust qualitative and quantitative investigation of the importance of EHR and lymphatic uptake. Satisfactory prediction of blood DPHP and urinary metabolites was obtained whereas blood MPHP was less satisfactory. However, the delayed peak of DPHP concentration relative to MPHP in blood and second order metabolites in urine could be explained as a result of three processes: 1) DPHP entering the systemic circulation from the lymph, 2) rapid and very high protein binding and 3) the efficiency of the liver in removing DPHP absorbed via the hepatic route. The use of sensitivity analysis is considered important in the evaluation of uncertainty around in vitro and in silico derived parameters. By quantifying their impact on model output sufficient confidence in the use of a model should be afforded. This approach could expand the use of PBPK models since parameterization with in silico techniques allows for rapid model development. This in turn could assist in reducing the use of animals in toxicological evaluations by enhancing the utility of “read across” techniques.

PBPK Analysis to Study the Impact of Genetic Polymorphism of NAT2 on Drug-Drug Interaction Potential of Isoniazid

PURPOSE

Isoniazid (INH) is prescribed both for the prophylaxis as well as the treatment of tuberculosis. It is primarily metabolized through acetylation by a highly polymorphic enzyme, N-acetyl transferase 2 (NAT2), owing to which significant variable systemic drug levels have been reported among slow and rapid acetylators. Furthermore, many drugs, like phenytoin, diazepam, triazolam, etc., are known to show toxic manifestation when co-administered with INH and it happens prominently among slow acetylators. Additionally, it is revealed in in vitro inhibition studies that INH carries noteworthy potential to inhibit CYP2C19 and CYP3A4 enzymes. However, CYP inhibitory effect of INH gets masked by opposite enzyme-inducing effect of rifampicin, when used in combination. Thus, distinct objective of this study was to fill the knowledge gaps related to gene-drug-drug interactions (DDI) potential of INH when given alone for prophylactic purpose.

METHODS

Whole body-PBPK models of INH were developed and verified for both slow and fast acetylators. The same were then utilized to carry out prospective DDI studies with CYP2C19 and CYP3A4 substrates in both acetylator types.

RESULTS

The results highlighted likelihood of significant higher blood levels of CYP2C19 and CYP3A4 substrate drugs in subjects receiving INH pre-treatment. It was also re-established that interaction was more likely in slow acetylators, as compared to rapid acetylators.

CONCLUSION

The novel outcome of the present study is the indication that prescribers should give careful consideration while advising CYP2C19 and CYP3A4 substrate drugs to subjects who are on prophylaxis INH therapy, and are slow to metabolic acetylation.

MC-100093, a Novel β-Lactam Glutamate Transporter-1 Enhancer Devoid of Antimicrobial Properties, Attenuates Cocaine Relapse in Rats

Cocaine use disorder currently lacks Food and Drug Administration-approved treatments. In rodents, the glutamate transporter-1 (GLT-1) is downregulated in the nucleus accumbens after cocaine self-administration, and increasing the expression and function of GLT-1 reduces the reinstatement of cocaine seeking. The β-lactam antibiotic ceftriaxone upregulates GLT-1 and attenuates cue- and cocaine-induced cocaine seeking without affecting motivation for natural rewards. Although ceftriaxone shows promise for treating cocaine use disorder, it possesses characteristics that limit successful translation from bench to bedside, including poor brain penetration, a lack of oral bioavailability, and a risk of bacterial resistance when used chronically. Thus, we aimed to develop novel molecules that retained the GLT-1-enhancing effects of ceftriaxone but displayed superior drug-like properties. Here, we describe a new monocyclic β-lactam, MC-100093, as a potent upregulator of GLT-1 that is orally bioavailable and devoid of antimicrobial properties. MC-100093 was synthesized and tested in vitro and in vivo to determine physiochemical, pharmacokinetic, and pharmacodynamic properties. Next, adult male rats underwent cocaine self-administration and extinction training. During extinction training, rats received one of four doses of MC-100093 for 6-8 days prior to a single cue-primed reinstatement test. Separate cohorts of rats were used to assess nucleus accumbens GLT-1 expression and MC-100093 effects on sucrose self-administration. We found that 50 mg/kg MC-100093 attenuated cue-primed reinstatement of cocaine seeking while upregulating GLT-1 expression in the nucleus accumbens core. This dose did not produce sedation, nor did it decrease sucrose consumption or body weight. Thus, MC-100093 represents a potential treatment to reduce cocaine relapse. SIGNIFICANCE STATEMENT: Increasing GLT-1 activity reliably reduces drug-seeking across classes of drugs; however, existing GLT1-enhancers have side effects and lack oral bioavailability. To address this issue, novel GLT-1 enhancers were synthesized, and the compound with the most favorable pharmacokinetic and pharmacodynamic properties, MC-100093, was selected for further testing. MC-100093 attenuated cued cocaine seeking without reducing food seeking or locomotion and upregulated GLT-1 expression in the nucleus accumbens.

Prediction of a clinically effective dose of THY1773, a novel V1B receptor antagonist, based on preclinical data

THY1773 is a novel arginine vasopressin 1B (V1B ) receptor antagonist that is under development as an oral drug for the treatment of major depressive disorder (MDD). Here we report our strategy to predict a clinically effective dose of THY1773 for MDD in the preclinical stage, and discuss the important insights gained by retrospective analysis of prediction accuracy. To predict human pharmacokinetic (PK) parameters, several extrapolation methods from animal or in vitro data to humans were investigated. The fu correction intercept method and two-species-based allometry were used to extrapolate clearance from rats and dogs to humans. The physiologically based pharmacokinetics (PBPK)/receptor occupancy (RO) model was developed by linking free plasma concentration with pituitary V1B RO by the Emax model. As a result, the predicted clinically effective dose of THY1773 associated with 50% V1B RO was low enough (10 mg/day, or at maximum 110 mg/day) to warrant entering phase 1 clinical trials. In the phase 1 single ascending dose study, TS-121 capsule (active ingredient: THY1773) showed favorable PKs for THY1773 as expected, and in the separately conducted phase 1 RO study using positron emission tomography, the observed pituitary V1B RO was comparable to our prediction. Retrospective analysis of the prediction accuracy suggested that the prediction methods considering plasma protein binding, and avoiding having to apply unknown scaling factors obtained in animals to humans, would lead to better prediction. Selecting mechanism-based methods with reasonable assumptions would be critical for the successful prediction of a clinically effective dose in the preclinical stage of drug development.

Pharmacokinetics and Drug-Drug Interactions of Isoniazid and Efavirenz in Pregnant Women Living With HIV in High TB Incidence Settings: Importance of Genotyping

The World Health Organization guidelines recommend that individuals living with HIV receive ≥ 6 months of isoniazid preventive therapy, including pregnant women. Yet, plasma isoniazid exposure during pregnancy, in the antiretroviral therapy era, has not been well-described. We investigated pregnancy-induced and pharmacogenetic-associated pharmacokinetic changes and drug-drug interactions between isoniazid and efavirenz in pregnant women. Eight hundred forty-seven women received isoniazid for 28 weeks, either during pregnancy or at 12 weeks postpartum, and 786 women received efavirenz. After adjusting for NAT2 and CYP2B6 genotype and weight, pregnancy increased isoniazid and efavirenz clearance by 26% and 15%, respectively. Isoniazid decreased efavirenz clearance by 7% in CYP2B6 normal metabolizers and 13% in slow and intermediate metabolizers. Overall, both isoniazid and efavirenz exposures were reduced during pregnancy, but the main determinants of drug concentration were NAT2 and CYP2B6 genotypes, which resulted in a five-fold difference for both drugs between rapid and slow metabolizers.

Evaluation of Tissue Binding in Three Tissues across Five Species and Prediction of Volume of Distribution from Plasma Protein and Tissue Binding with an Existing Model

Volume of distribution (V_d) is a primary pharmacokinetic parameter used to calculate the half-life and plasma concentration-time profile of drugs. Numerous models have been relatively successful in predicting V_d, but the model developed by Korzekwa and Nagar is of particular interest because it utilizes plasma protein binding and microsomal binding data, both of which are readily available in vitro parameters. Here, Korzekwa and Nagar's model was validated and expanded upon using external and internal data sets. Tissue binding, plasma protein binding, V_d, physiochemical, and physiologic data sets were procured from literature and Genentech's internal data base. First, we investigated the hypothesis that tissue binding is primarily governed by passive processes that depend on the lipid composition of the tissue type. The fraction unbound in tissues (fu_tissue) was very similar across human, rat, and mouse. In addition, we showed that dilution factors could be generated from nonlinear regression so that one fu_tissue value could be used to estimate another one regardless of species. More importantly, results suggested that microsomes could serve as a surrogate for tissue binding. We applied the parameters from Korzekwa and Nagar's V_d model to two distinct liver microsomal data sets and found remarkably close statistical results. Brain and lung data sets also accurately predicted V_d, further validating the model. V_d prediction accuracy for compounds with log D_7.4 > 1 significantly outperformed that of more hydrophilic compounds. Finally, human V_d predictions from Korzekwa and Nagar's model appear to be as accurate as rat allometry and slightly less accurate than dog and cynomolgus allometry. SIGNIFICANCE STATEMENT: This study shows that tissue binding is comparable across five species and can be interconverted with a dilution factor. In addition, we applied internal and external data sets to the volume of distribution model developed by Korzekwa and Nagar and found comparable V_d prediction accuracy between the V_d model and single-species allometry. These findings could potentially accelerate the drug research and development process by reducing the amount of resources associated with in vitro binding and animal experiments.

Pharmacokinetic Estimation Models-based Approach to Predict Clinical Implications for CYP Induction by Calcitriol in Human Cryopreserved Hepatocytes and HepaRG Cells

Calcitriol, a vitamin D₃ metabolite, is approved for various indications because it is the bioactive form of vitamin D in the body. The purpose of this study was to predict the clinical significance of cytochrome P450 (CYP) induction by calcitriol using in vitro human cryopreserved hepatocytes, HepaRG experimental systems, and various pharmacokinetic estimation models. CYP2B6, 3A4, 2C8, and 2C9 mRNA levels increased in a concentration-dependent manner in the presence of calcitriol in human cryopreserved hepatocytes and HepaRG cells. Using the half maximal effective concentration (EC₅₀) and maximum induction effect (E_max) obtained from the in vitro study, a basic kinetic model was applied, suggesting clinical relevance. In addition, a static mechanistic model showed the improbability of a clinically significant effect; however, the calculated area under the plasma concentration-time curve ratio (AUCR) was marginal for CYP3A4 in HepaRG cells. To clarify the effect of CYP3A4 in vivo, physiologically based pharmacokinetic (PBPK) modeling was applied as a dynamic mechanistic model, revealing a low clinically significant effect of CYP3A4 induction by calcitriol. Therefore, we conclude that CYP induction by calcitriol treatment would not be clinically significant under typical clinical conditions.

Drug-drug interaction of atazanavir on UGT1A1-mediated glucuronidation of molidustat in human

Molidustat is an oral inhibitor of hypoxia‐inducible factor (HIF) prolyl‐hydroxylase enhancing the erythropoietin (EPO) response to HIF; it is in clinical development for the treatment of anaemia related to chronic kidney disease. The predominant role of glucuronidation for molidustat clearance (formation of N‐glucuronide metabolite M1) and subsequent renal excretion was confirmed in a human mass balance study, with about 85% of the drug being excreted as M1 in urine. The inhibitory effects of 176 drugs and xenobiotics from various compound classes on the UGT‐mediated glucuronidation of molidustat in human liver microsomes (HLMs) were investigated. Based on preclinical findings, glucuronidation of molidustat was predominantly mediated by the 5'‐diphospho‐glucuronosyltransferase (UGT) isoform UGT1A1. Therefore, atazanavir, which is a potent inhibitor of UGT1A1, was chosen for the evaluation of pharmacokinetics and EPO release following a single oral dose of 25 mg molidustat. Molidustat exposure increased about twofold upon coadministration with atazanavir when considering area under plasma concentration‐time curve from zero to infinity (AUC) and maximum plasma concentration (C_max). Baseline‐corrected increase of EPO was 14% and 34% for C_max and AUC (calculated over 24 hours), respectively. Coadministration of molidustat and atazanavir was well tolerated.

Comparative Pharmacokinetics of Meloxicam Between Healthy Post-partum vs. Mid-lactation Dairy Cattle

Lactating dairy cattle are at risk for various painful conditions throughout their life, such as lameness, parturition, mastitis, and metabolic disorders. These conditions necessitate adequate methods of analgesia to address welfare concerns through efficacious pain mitigation. As no method of analgesia has been approved for lactating dairy cattle, to date, research is necessary to determine effective pain management strategies for dairy cattle. In both the European Union and Canada, meloxicam has been approved for use in lactating dairy cattle as a methodology for pain control. The objective of this study was to characterize the pharmacokinetics of meloxicam administered orally and intravenously to lactating dairy cattle in the post-partum vs. mid-lactation period. In this parallel study design, 12 healthy, lactating Holsteins were enrolled within 24 h of freshening and randomly allocated to intravenous (0.2 mg/kg) or oral (1.0 mg/kg) meloxicam administration treatment groups. They were matched based on parity to 12, healthy cows that were considered mid-lactation [>150 days-in-milk (DIM)] to receive the same treatment. Based on meloxicam formulation, sampling times varied and plasma was collection via jugular venipuncture for 6 days. Plasma drug concentrations were evaluated using liquid chromatography coupled with mass spectroscopy and pharmacokinetic properties were evaluated using non-compartmental (i.e., statistical moments) analysis. Results indicated a decreased systemic clearance of meloxicam in post-partum relative to mid-lactation cows, which resulted in a longer half-life and increased total exposure independent of mode of administration. These results suggest a need for dose adjustments based on stage in lactation and further assessment of the impact of days-in-milk on milk withholding period.

Precision Dosing Management with Intelligent Computing in Digital Health

Pediatric dosing is not only critical for successful pediatric trials in drug development but also paramount to safety and effective treatment at bedside. Due to the complex pharmacokinetic of children compared to adults, several challenges are posed in managing dosing precisely during drug development and after drug approval to clinicians. In particular, given the real-world practice, understanding the impact of development on the dose-exposure-response relationship is essential in optimizing the dosing to children of different ages. In this paper we propose a novel intelligent computing framework to examine how the growth and maturation create size- and age-dependent variability in pharmacokinetics and pharmacodynamics, and summarize the use of modeling-based approaches for dose finding in pediatric drug development, allowing clinicians to anticipate probable treatment effects and to have a higher likelihood of achieving optimal dose regimens early, as well as reducing the drug development cycling time and cost.

Drug-Drug Interaction Risk Assessment of Esaxerenone as a Perpetrator by In Vitro Studies and Static and Physiologically Based Pharmacokinetic Models

Esaxerenone (CS-3150) is a novel, oral, nonsteroidal, selective mineralocorticoid receptor blocker approved for the treatment of hypertension in Japan. Here, the drug-drug interaction (DDI) potential of esaxerenone was evaluated in vitro, and its impact in clinical practice was estimated. Esaxerenone exhibited time-dependent inhibition and induction of CYP3A. When the clinical impacts of esaxerenone on the inhibition and induction of CYP3A were estimated separately by using a mechanistic static model, the predicted area under the curve ratios (AUCRs) of midazolam, a typical CYP3A substrate, were 1.80 and 0.31, respectively, suggesting that the DDI potential of esaxerenone cannot be neglected. Because it was suggested that DDIs mainly occur in the intestine, predictions using concentration-time profiles in each segment of the gastrointestinal tract were performed with GastroPlus, a physiologically based pharmacokinetic (PBPK) modeling software. The predicted AUCR of midazolam was approximately 1.2, which is close to that in a clinical study, despite the difficulty of predicting DDIs for compounds with both inhibition and induction effects. When only inhibition or induction was incorporated into a model, the AUCR of midazolam changed depending on the dosing period and dose level of esaxerenone and the timing of midazolam administration. However, the AUCR calculated by incorporating both effects remained almost constant. This study shows the ability of PBPK models to simulate weak DDIs via intestinal CYP3A and that esaxerenone has low DDI potential as a perpetrator because of the offset of inhibition and induction. SIGNIFICANCE STATEMENT: Weak CYP3A inhibition and/or induction sometimes cause DDIs in the intestine but not the liver. Because strong inhibitors maximally inhibit intestinal CYP3A, the predictability of weak DDIs in the intestine should be evaluated further. Here, we simulate the DDIs of esaxerenone as a perpetrator by using physiologically based pharmacokinetic modeling focusing on the intestine and offset of inhibition and induction.