A physiologically-based pharmacokinetic/pharmacodynamic modeling approach for drug-drug-gene interaction evaluation of S-warfarin with fluconazole.

Warfarin is a widely used anticoagulant, and its S-enantiomer has higher potency compared to the R-enantiomer. S-warfarin is mainly metabolized by cytochrome P450 (CYP) 2C9, and its pharmacological target is vitamin K epoxide reductase complex subunit 1 (VKORC1). Both CYP2C9 and VKORC1 have genetic polymorphisms, leading to large variations in the pharmacokinetics (PKs) and pharmacodynamics (PDs) of warfarin in the population. This makes dosage management of warfarin difficult, especially in the case of drug-drug interactions (DDIs). This study provides a whole-body physiologically-based pharmacokinetic/PD (PBPK/PD) model of S-warfarin for predicting the effects of drug-drug-gene interactions on S-warfarin PKs and PDs. The PBPK/PD model of S-warfarin was developed in PK-Sim and MoBi. Drug-dependent parameters were obtained from the literature or optimized. Of the 34 S-warfarin plasma concentration-time profiles used, 96% predicted plasma concentrations within twofold range compared to observed data. For S-warfarin plasma concentration-time profiles with CYP2C9 genotype, 364 of 386 predicted plasma concentration values (~94%) fell within the twofold of the observed values. This model was tested in DDI predictions with fluconazole as CYP2C9 perpetrators, with all predicted DDI area under the plasma concentration-time curve to the last measurable timepoint (AUClast) ratio within twofold of the observed values. The anticoagulant effect of S-warfarin was described using an indirect response model, with all predicted international normalized ratio (INR) within twofold of the observed values. This model also incorporates a dose-adjustment method that can be used for dose adjustment and predict INR when warfarin is used in combination with CYP2C9 perpetrators.

Physiologically Based Pharmacokinetic Modeling to Unravel the Drug-gene Interactions of Venlafaxine: Based on Activity Score-dependent Metabolism by CYP2D6 and CYP2C19 Polymorphisms.

BACKGROUND: Venlafaxine (VEN) is a commonly utilized medication for alleviating depression and anxiety disorders. The presence of genetic polymorphisms gives rise to considerable variations in plasma concentrations across different phenotypes. This divergence in phenotypic responses leads to notable differences in both the efficacy and tolerance of the drug. PURPOSE: A physiologically based pharmacokinetic (PBPK) model for VEN and its metabolite O-desmethylvenlafaxine (ODV) to predict the impact of CYP2D6 and CYP2C19 gene polymorphisms on VEN pharmacokinetics (PK). METHODS: The parent-metabolite PBPK models for VEN and ODV were developed using PK-Sim® and MoBi®. Leveraging prior research, derived and implemented CYP2D6 and CYP2C19 activity score (AS)-dependent metabolism to simulate exposure in the drug-gene interactions (DGIs) scenarios. The model's performance was evaluated by comparing predicted and observed values of plasma concentration-time (PCT) curves and PK parameters values. RESULTS: In the base models, 91.1%, 94.8%, and 94.6% of the predicted plasma concentrations for VEN, ODV, and VEN + ODV, respectively, fell within a twofold error range of the corresponding observed concentrations. For DGI scenarios, these values were 81.4% and 85% for VEN and ODV, respectively. Comparing CYP2D6 AS = 2 (normal metabolizers, NM) populations to AS = 0 (poor metabolizers, PM), 0.25, 0.5, 0.75, 1.0 (intermediate metabolizers, IM), 1.25, 1.5 (NM), and 3.0 (ultrarapid metabolizers, UM) populations in CYP2C19 AS = 2.0 group, the predicted DGI AUC0-96 h ratios for VEN were 3.65, 3.09, 2.60, 2.18, 1.84, 1.56, 1.34, 0.61, and for ODV, they were 0.17, 0.35, 0.51, 0.64, 0.75, 0.83, 0.90, 1.11, and the results were similar in other CYP2C19 groups. It should be noted that PK differences in CYP2C19 phenotypes were not similar across different CYP2D6 groups. CONCLUSIONS: In clinical practice, the impact of genotyping on the in vivo disposition process of VEN should be considered to ensure the safety and efficacy of treatment.

Schisandrin protects against ulcerative colitis by inhibiting the SGK1/NLRP3 signaling pathway and reshaping gut microbiota in mice.

BACKGROUND: According to the Chinese Pharmacopoeia, the fruit of Schisandra chinensis (Turcz.) Baill. (SC) is an important traditional Chinese medicine that can be used to treat diarrhea. Despite the increasing research on the anti-inflammatory and anti-oxidant aspects of SC, the studies on the anti-ulcerative colitis of Schisandrin (SCH), the main constituent of SC, are relatively few. METHODS: The mice used in the study were randomly distributed into 6 groups: control, model, 5-ASA, and SCH (20, 40, 80 mg/kg/d). The mice in the model group were administered 3% (w/v) dextran sulfate sodium (DSS) through drinking water for 7 days, and the various parameters of disease activity index (DAI) such as body weight loss, stool consistency, and gross blood were measured. ELISA was used to detect inflammatory factors, and bioinformatics combined with transcriptome analysis was done to screen and verify relevant targets. 16S rDNA high-throughput sequencing was used to analyze the composition of the gut microbiota(GM), while mass spectrometry was done to analyze the changes in the content of bile acids (BAs) in the intestine. RESULTS: Mice treated with SCH experienced significant weight gain, effectively alleviating the severity of colitis, and decreasing the levels of inflammatory factors such as TNF-α, IL-1ß, IL-18, IL-6, and other related proteins (NLRP3, Caspase-1, SGK1) in UC mice. Furthermore, the analysis of GM and BAs in mice revealed that SCH increased the relative abundance of Lactobacilli spp, reduced the relative abundance of Bacteroides, and promoted the conversion of primary BAs to secondary BAs. These effects contributed to a significant improvement in the DSS-induced GM imbalance and the maintenance of intestinal homeostasis. CONCLUSION: It seems that there is a close relationship between the SCH mechanism and the regulation of SGK1/NLRP3 pathway and the restoration of GM balance. Therefore, it can be concluded that SCH could be a potential drug for the treatment of UC.

Physiologically based pharmacokinetic modeling of levetiracetam to predict the exposure in hepatic and renal impairment and elderly populations.

Levetiracetam (LEV) is an anti-epileptic drug approved for use in various populations. The pharmacokinetic (PK) behavior of LEV may be altered in the elderly and patients with renal and hepatic impairment. Thus, dosage adjustment is required. This study was conducted to investigate how the physiologically-based PK (PBPK) model describes the PKs of LEV in adult and elderly populations, as well as to predict the PKs of LEV in patients with renal and hepatic impairment in both populations. The whole-body PBPK models were developed using the reported physicochemical properties of LEV and clinical data. The models were validated using data from clinical studies with different dose ranges and different routes and intervals of administration. The fit performance of the models was assessed by comparing predicted and observed blood concentration data and PK parameters. It is recommended that the doses be reduced to ~70%, 60%, and 45% of the adult dose for the mild, moderate, and severe renal impairment populations and ~95%, 80%, and 57% of the adult dose for the Child Pugh-A (CP-A), Child Pugh-B (CP-B), and Child Pugh-C (CP-C) hepatic impairment populations, respectively. No dose adjustment is required for the healthy elderly population, but dose reduction is required for the elderly with organ dysfunction accordingly, on a scale similar to that of adults. A PBPK model of LEV was successfully developed to optimize dosing regimens for special populations.

Development and Validation of Physiologically Based Pharmacokinetic Model of Levetiracetam to Predict Exposure and Dose Optimization in Pediatrics.

Levetiracetam (Lev) is an antiepileptic drug that has been increasingly used in the epilepsy pediatric population in recent years, but its pharmacokinetic behavior in pediatric population needs to be characterized clearly. Clinical trials for the pediatric drug remain difficult to conduct due to ethical and practical factors. The purpose of this study was to use the physiologically based pharmacokinetic (PBPK) model to predict changes in plasma exposure of Lev in pediatric patients and to provide recommendations for dose adjustment. A PBPK model of Lev in adults was developed using PK-Sim® software and extrapolated to the entire age range of the pediatric population. The model was evaluated using clinical pharmacokinetic data. The results showed the good fit between predictions and observations of the adult and pediatric models. The recommended doses for neonates, infants and children are 0.78, 1.67 and 1.22 times that of adults, respectively. Moreover, at the same dose, plasma exposure in adolescents was similar to that of adults. The PBPK models of Lev for adults and pediatrics were successfully developed and validated to provide a reference for the rational administration of drugs in the pediatric population.

Integrating Bioinformatics and Network Pharmacology to Explore the Therapeutic Target and Molecular Mechanisms of Schisandrin on Hypertrophic Cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease and is currently the leading cause of sudden death in adolescent athletes. Schisandrin is a quality marker of the traditional Chinese medicine Schisandra chinensis, which has an excellent therapeutic effect on HCM, but its pharmacological mechanism remains unclear. OBJECTIVE: This study aimed to explore the potential and provide scientific evidence for schisandrin as a lead compound against hypertrophic cardiomyopathy. METHODS: The drug-like properties of schisandrin were predicted using the SwissADME website. Then, the PharmMapper database was used to predict potential drug targets and match gene names in the Uniprot database. HCM targets were collected from NCBI, OMIM, and Genecards databases and intersected with drug targets. The intersection targets were imported into the STRING database for PPI analysis, and core targets were identified. KEGG and GO enrichment analysis was performed on the core targets through the DAVID database, and all network maps were imported into Cytoscape software for visualization optimization. HCM-related datasets were downloaded from the GEO database to analyze core targets and screen differentially expressed target genes for molecular docking. RESULTS: After the PPI network analysis of the intersection targets of drugs and diseases, 12 core targets were screened out. The KEGG analysis results showed that they were mainly involved in Rap1, TNF, FoxO, PI3K-Akt, and other signaling pathways. After differential analysis, PPARG, EGFR, and MMP3 targets were also screened. The molecular docking results showed that schisandrin was well bound to the protein backbone of each target. CONCLUSION: This study used network pharmacology combined with differential expression and molecular docking to predict that schisandrin may treat HCM by acting on PPARG, EGFR, and MMP3 targets, and the regulatory process may involve signaling pathways, such as Rap1, TNF, FoxO, and PI3K-Akt, which may provide a valuable reference for subsequent studies.

Predictive performance and verification of physiologically based pharmacokinetic model of propylthiouracil.

Background: Propylthiouracil (PTU) treats hyperthyroidism and thyroid crisis in all age groups. A variety of serious adverse effects can occur during clinical use and require attention to its pharmacokinetic and pharmacodynamic characteristics in various populations. Objective: To provide information for individualized dosing and clinical evaluation of PTU in the clinical setting by developing a physiologically based pharmacokinetic (PBPK) model, predicting ADME characteristics, and extrapolating to elderly and pediatric populations. Methods: Relevant databases and literature were retrieved to collect PTU's pharmacochemical properties and ADME parameters, etc. A PBPK model for adults was developed using PK-Sim® software to predict tissue distribution and extrapolated to elderly and pediatric populations. The mean fold error (MFE) method was used to compare the differences between predicted and observed values to assess the accuracy of the PBPK model. The model was validated using PTU pharmacokinetic data in healthy adult populations. Result: The MFE ratios of predicted to observed values of AUC0-t, Cmax, and Tmax were mainly within 0.5 and 2. PTU concentrations in various tissues are lower than venous plasma concentrations. Compared to healthy adults, the pediatric population requires quantitative adjustment to the appropriate dose to achieve the same plasma exposure levels, while the elderly do not require dose adjustments. Conclusion: The PBPK model of PTU was successfully developed, externally validated, and applied to tissue distribution prediction and special population extrapolation, which provides a reference for clinical individualized drug administration and evaluation.

DYF-5/MAK-dependent phosphorylation promotes ciliary tubulin unloading.

Cilia are microtubule-based organelles that power cell motility and regulate sensation and signaling, and abnormal ciliary structure and function cause various ciliopathies. Cilium formation and maintenance requires intraflagellar transport (IFT), during which the kinesin-2 family motor proteins ferry IFT particles carrying axonemal precursors such as tubulins into cilia. Tubulin dimers are loaded to IFT machinery through an interaction between tubulin and the IFT-74/81 module; however, little is known of how tubulins are unloaded when arriving at the ciliary tip. Here, we show that the ciliary kinase DYF-5/MAK phosphorylates multiple sites within the tubulin-binding module of IFT-74, reducing the tubulin-binding affinity of IFT-74/81 approximately sixfold. Ablation or constitutive activation of IFT-74 phosphorylation abnormally elongates or shortens sensory cilia in Caenorhabditis elegans neurons. We propose that DYF-5/MAK-dependent phosphorylation plays a fundamental role in ciliogenesis by regulating tubulin unloading.

Optimal sidestepping of intraflagellar transport kinesins regulates structure and function of sensory cilia.

Cytoskeletal-based molecular motors produce force perpendicular to their direction of movement. However, it remains unknown whether and why motor proteins generate sidesteps movement along their filamentous tracks in vivo. Using Hessian structured illumination microscopy, we located green fluorescent protein (GFP)-labeled intraflagellar transport (IFT) particles inside sensory cilia of live Caenorhabditis elegans with 3-6-nanometer accuracy and 3.4-ms resolution. We found that IFT particles took sidesteps along axoneme microtubules, demonstrating that IFT motors generate torque in a living animal. Kinesin-II and OSM-3-kinesin collaboratively drive anterograde IFT. We showed that the deletion of kinesin-II, a torque-generating motor protein, reduced sidesteps, whereas the increase of neck flexibility of OSM-3-kinesin upregulated sidesteps. Either increase or decrease of sidesteps of IFT kinesins allowed ciliogenesis to the regular length, but changed IFT speeds, disrupted axonemal ninefold symmetry, and inhibited sensory cilia-dependent animal behaviors. Thus, an optimum level of IFT kinesin sidestepping is associated with the structural and functional fidelity of cilia.

Spectrin-based membrane skeleton supports ciliogenesis.

Cilia are remarkable cellular devices that power cell motility and transduce extracellular signals. To assemble a cilium, a cylindrical array of 9 doublet microtubules push out an extension of the plasma membrane. Membrane tension regulates cilium formation; however, molecular pathways that link mechanical stimuli to ciliogenesis are unclear. Using genome editing, we introduced hereditary elliptocytosis (HE)- and spinocerebellar ataxia (SCA)-associated mutations into the Caenorhabditis elegans membrane skeletal protein spectrin. We show that these mutations impair mechanical support for the plasma membrane and change cell shape. RNA sequencing (RNA-seq) analyses of spectrin-mutant animals uncovered a global down-regulation of ciliary gene expression, prompting us to investigate whether spectrin participates in ciliogenesis. Spectrin mutations affect intraflagellar transport (IFT), disrupt axonemal microtubules, and inhibit cilium formation, and the endogenous spectrin periodically distributes along cilia. Mammalian spectrin also localizes in cilia and regulates ciliogenesis. These results define a previously unrecognized yet conserved role of spectrin-based mechanical support for cilium biogenesis.

Diaqua-bis-[4-(4H-1,2,4-triazol-4-yl)benzoato-κO,O']nickel(II).

In the title compound, [Ni(C(9)H(6)N(3)O(2))(2)(H(2)O)(2)], the Ni(II) atom lies on a twofold rotation axis and is six-coordinated by two bidentate chelating 4-(1,2,4-triazol-4-yl)benzoate ligands and two water mol-ecules in a distorted octa-hedral geometry. Inter-molecular O-H⋯N hydrogen bonds link the complex mol-ecules into a two-dimensional network parallel to (010).

Tetra-aqua-bis-[4-(4H-1,2,4-triazol-4-yl)benzoato-κN]copper(II) dihydrate.

In the title compound, [Cu(C(9)H(6)N(3)O(2))(2)(H(2)O)(4)]·2H(2)O, the Cu(II) atom lies on an inversion center and is six-coordinated by two N atoms from two 4-(1,2,4-triazol-4-yl)benzoate ligands and four water mol-ecules in a distorted octa-hedral geometry. In the crystal, inter-molecular O-H⋯O hydrogen bonds lead to a three-dimensional supra-molecular network. Intra-molecular O-H⋯N hydrogen bonds and π-π inter-actions between the benzene rings and between the benzene and triazole rings [centroid-centroid distances = 3.657 (1) and 3.752 (1) Å] are observed.