The purpose of this paper is to study the genetic polymorphisms of related gene loci (CYP2C9*3, VKORC1-1639G > A) based on demographic and clinical factors, and use the maximum a posterior Bayesian method to construct a warfarin individualized dose prediction model in line with the Chinese Han population. Finally, the built model is compared and analyzed with the widely used models at home and abroad. In this study, a total of 5467 INR measurements are collected from 646 eligible subjects in our hospital, and the maximum a posterior Bayesian method is used to construct a warfarin dose prediction that conforms to the Chinese Han population on the basis of the Hamberg model. The model is verified and compared with foreign models. This study finds that body weight and concomitant use of amiodarone have a significant effect on the anticoagulant effect of warfarin. The model can provide an effective basis for individualized and rational dosing of warfarin in Han population more accurately. In the performance of comparison with different warfarin dose prediction models, the new model has the highest prediction accuracy, and the prediction percentage is as high as 72.56%. The dose predicted by the Huang model is the closest to the actual dose of warfarin. The population pharmacokinetics and pharmacodynamics model established in this study can better reflect the distribution characteristics of INR values after warfarin administration in the Han population, and performs better than the models reported in the literature.

BACKGROUND: Noscapine is a commonly used cough suppressant, with ongoing research on its anti-inflammatory and anti-tumor properties. The drug has a pronounced pharmacokinetic variability.
OBJECTIVE: This evaluation aims to describe the pharmacokinetics of noscapine using a semi-mechanistic population pharmacokinetic model and to identify covariates that could explain inter-individual pharmacokinetic variability.
METHODS: Forty-eight healthy volunteers (30 men and 18 women, mean age 33 years) were enrolled in a randomized, two-period, two-stage, crossover bioequivalence study of noscapine in two different liquid formulations. Noscapine plasma concentrations following oral administration of noscapine 50 mg were evaluated by a non-compartmental analysis and by a population pharmacokinetic model separately.
RESULTS: Compared to the reference formulation, the test formulation exhibited ratios (with 94.12% confidence intervals) of 0.784 (0.662-0.929) and 0.827 (0.762-0.925) for peak plasma concentrations and area under the plasma concentration-time curve, respectively. Significant differences in p values (< 0.01) were both observed when comparing peak plasma concentrations and area under the plasma concentration-time curve between CYP2C9 genotype-predicted phenotypes. A three-compartmental model with zero-order absorption and first-order elimination process best described the plasma data. The introduction of a liver compartment was able to describe the profound first-pass effect of noscapine. Total body weight and the CYP2C9 genotype-predicted phenotype were both identified as significant covariates on apparent clearance, which was estimated as 958 ± 548 L/h for extensive metabolizers (CYP2C9*1/*1 and *1/*9), 531 ± 304 L/h for intermediate metabolizers with an activity score of 1.5 (CYP2C9*1/*2), and 343 ± 197 L/h for poor metabolizers and intermediate metabolizers with an activity score of 1.0 (CYP2C9*1/*3, *2/*3, and*3/*3).
CONCLUSIONS: The current work is expected to facilitate the future pharmacokinetic/pharmacodynamic development of noscapine. This study was registered prior to starting at \"Deutsches Register Klinischer Studien\" under registration no. DRKS00017760.

Voriconazole is the first-line treatment for invasive aspergillosis. Its pharmacokinetics exhibit considerable inter- and intra-individual variability. The purpose of this study was to investigate the effects of CYP2C19, CYP2C9, CYP3A4, and FMO3 genetic polymorphisms and sex on the pharmacokinetics of voriconazole in healthy Chinese adults receiving single-dose and multiple-dose voriconazole, to provide a reference for its clinical individualized treatment. A total of 123 healthy adults were enrolled in the study, with 108 individuals and 15 individuals in the single-dose and multiple-dose doses, respectively. Plasma voriconazole concentrations were measured using a validated LC-MS/MS method, and pharmacokinetics parameters were calculated using the non-compartmental method with WinNonlin 8.2. CYP2C19, CYP2C9, CYP3A4, and FMO3 single-nucleotide polymorphisms were sequenced using the Illumina Hiseq X-Ten platform. The results suggested that CYP2C19 genetic polymorphisms significantly affected the pharmacokinetics of voriconazole at single doses of 4, 6, and 8 mg/kg and multiple doses of voriconazole. CYP3A4 rs2242480 had a significant effect on AUC0-∞ (area under the plasma concentration-time curve from time 0 to infinity) and MRT (mean residence time) of voriconazole at a single dose of 4 mg/kg in CYP2C19 extensive metabolizer. Regardless of the CYP2C19 genotype, CYP2C9 rs1057910 and FMO3 rs2266780 were not associated with the pharmacokinetics of voriconazole at three single-dose levels or multiple doses. No significant differences in most voriconazole pharmacokinetics parameters were noted between male and female participants after single and multiple dosing. For patients receiving voriconazole treatment, CYP2C19 genetic polymorphisms should be genotyped for its precision administration. In contrast, based on our study of healthy Chinese adults, it seems unnecessary to consider the effects of CYP2C9, CYP3A4, and FMO3 genetic polymorphisms on voriconazole pharmacokinetics.

The clinical effectiveness of nux-vomica in treating rheumatism and arthralgia is noteworthy; however, its nephrotoxicity has sparked global concerns. Hence, there is value in conducting studies on detoxification methods based on traditional Chinese medicine compatibility theory. Blood biochemistry, enzyme-linked immunosorbent assay, and pathological sections were used to evaluate both the nephrotoxicity of nux-vomica and the efficacy of the Jian Pi Tong Luo (JPTL) compound in mitigating this toxicity. Kidney metabolomics, using ultra-high-performance liquid chromatography-quadrupole-time-of-flight-MS (UPLC-Q-TOF-MS), was applied to elucidate the alterations in small-molecule metabolites in vivo. In addition, network pharmacology analysis was used to verify the mechanism and pathways underlying the nephrotoxicity associated with nux-vomica. Finally, essential targets were validated through molecular docking and western blotting. The findings indicated significant nephrotoxicity associated with nux-vomica, while the JPTL compound demonstrated the ability to alleviate this toxicity. The mechanism potentially involves nux-vomica activating the \"PTGS2/CYP2C9-phosphatidylcholine-arachidonic acid metabolic pathway.\" This study establishes a scientific foundation for the clinical use of nux-vomica and lays groundwork for further research and safety assessment of toxic Chinese herbal medicines.

To uncover the effect of danshensu on irbesartan pharmacokinetics and its underlying mechanisms.To investigate the effect of danshensu on the pharmacokinetics of irbesartan, Sprague-Dawley rats (n = 6) were orally administered 30 mg/kg irbesartan alone (control group) or pre-treated with 160 mg/kg danshensu (experimental group). The effect of danshensu on the metabolic stability of irbesartan in RLMs was examined by LC-MS/MS method. The effect of danshensu on CYP2C9 activity was also determined.Danshensu markedly increased the AUC(0-t) (9573 ± 441 vs. 16157 ± 559 μg/L*h) and Cmax (821 ± 24 vs. 1231 ± 44 μg/L) of irbesartan. Danshensu prolonged the t1/2 (13.39 ± 0.98 vs. 16.04 ± 1.21 h) and decreased the clearance rate (2.27 ± 0.14 vs. 1.19 ± 0.10 L/h/kg) of irbesartan. Danshensu enhanced the metabolic stability of irbesartan in vitro with prolonged t1/2 (36.34 ± 11.68 vs. 48.62 ± 12.03 min) and reduced intrinsic clearance (38.14 ± 10.24 vs. 28.51 ± 9.06 μL/min/mg protein). Additionally, the IC50 value for CYP2C9 inhibition by danshensu was 35.74 μM.Danshensu enhanced systemic exposure of irbesartan by suppressing CYP2C9. The finding can also serve as a guidance for further investigation of danshensu-irbesartan interaction in clinical practice.

Warfarin is an irreplaceable oral anticoagulant for patients with mechanical heart valves, the stable pharmacogenetic-based warfarin dose prediction algorithms have improved the effectiveness and safety of warfarin anticoagulation therapy. Genetic factors are the main factors affecting the stable dose of warfarin. Single nucleotide polymorphisms such as VKORC1 and CYP2C9 affect the anticoagulation effect of warfarin through pharmacodynamic or pharmacokinetic pathways. Age, body surface area, combined use of drugs, and other nongenetic factors also affect the stable dose of warfarin. Previously published algorithms for warfarin dose prediction included mainly the white race, and most algorithms were constructed using traditional multiple linear regression. However, domestic studies have used machine learning methods to construct warfarin dose prediction algorithms based on the Chinese Han post-mechanical valve replacement population and have achieved better prediction efficiency. This article reviews the advances of warfarin anticoagulation influencing factors and the clinical application of stable dose prediction algorithms.
华法林是机械瓣膜置换术后患者不可替代的口服抗凝药物，近年来，基于遗传药理学构建的华法林稳定剂量预测模型一定程度上提高了华法林抗凝治疗的有效性和安全性。遗传因素是影响华法林稳定剂量的主要因素，VKORC1、CYP2C9等基因通过作用于华法林药理或代谢途径影响华法林抗凝效果。此外，年龄、体表面积、合并用药等非遗传因素也对华法林稳定剂量有影响。既往发表的华法林剂量预测模型纳入人群以高加索人为主，模型构建方法多为传统多元线性回归。而国内研究根据中国汉族机械瓣膜置换术后人群，采用机器学习方法构建华法林剂量预测模型并取得了更好的预测效能。.

Cytochrome P450 (CYP) enzymes are involved in the metabolism of approximately 75% of marketed drugs. Inhibition of the major drug-metabolizing P450s could alter drug metabolism and lead to undesirable drug-drug interactions. Therefore, it is of great significance to explore the inhibition of P450s in drug discovery. Currently, machine learning including deep learning algorithms has been widely used for constructing in silico models for the prediction of P450 inhibition. These models exhibited varying predictive performance depending on the use of machine learning algorithms and molecular representations. This leads to the difficulty in the selection of appropriate models for practical use. In this study, we systematically evaluated the conventional machine learning and deep learning models for three major P450 enzymes, CYP3A4, CYP2D6, and CYP2C9 from several perspectives, such as algorithms, molecular representation, and data partitioning strategies. Our results showed that the XGBoost and CatBoost algorithms coupled with the combined fingerprint/physicochemical descriptor features exhibited the best performance with Area Under Curve (AUC)  of 0.92, while the deep learning models were generally inferior to the conventional machine learning models (average AUC reached 0.89) on the same test sets. We also found that data volume and sampling strategy had a minor effect on model performance. We anticipate that these results are helpful for the selection of molecular representations and machine learning/deep learning algorithms in the P450 model construction and the future model development of P450 inhibition.

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.

BACKGROUND: Warfarin is widely used for the prevention and treatment of thrombotic events. This study aimed to examine the influence of gene polymorphisms on the early stage of warfarin therapy in patients following heart valve surgery.
METHODS: Nine single nucleotide polymorphisms were genotyped using microarray chips, categorizing patients into three groups: normal responders (Group I), sensitive responders (Group II), and highly sensitive responders (Group III). The primary clinical outcomes examined were time in therapeutic range (TTR) and international normalized ratio (INR) variability. To investigate potential influencing factors, a generalized linear regression model was employed.
RESULTS: Among 734 patients, the prevalence of CYP2C9*3-1075A > C, CYP2C19*3-636G > A, and CYP2C19*17-806C > T variants were 11.2%, 9.9%, and 1.9% of patients, respectively. VKORC1-1639G > A or the linked -1173C > T variant was observed in 99.0% of the patients. Generalized linear model analysis revealed an impact of sensitivity grouping on INR variability. Compared to Group I, Group II showed higher TTR values (p = 0.023), while INR variability was poorer in Group II (p < 0.001) and Group III (p < 0.001). Individual gene analysis identified significant associations between CYP2C9*3-1075A > C (p < 0.001), VKORC1-1639G > A or the linked -1173 C > T (p = 0.009) and GGCX-3261G > A (p = 0.019) with INR variability.
CONCLUSIONS: The genotypes of CYP2C9, VKORC1, and GGCX were found to have a significant impact on INR variability during the initial phase of warfarin therapy. However, no significant association was observed between TTR and gene polymorphisms. These findings suggest that focusing on INR variability is crucial in clinical practice, and preoperative detection of gene polymorphisms should be considered to assist in the initiation of warfarin therapy.

BACKGROUND: High altitude environment affects the pharmacokinetic (PK) parameters of drugs and the PK parameters are an important theoretical basis for guiding the rational clinical use of drugs. Warfarin is an oral anticoagulant of the coumarin class commonly used in clinical practice, but it has a narrow therapeutic window and wide individual variation. However, the effect of high altitude environment on PK and pharmacodynamic (PD) of warfarin is unclear.
OBJECTIVE: The objective of this study is to investigate the effect of a high altitude environment on PK and PD of warfarin in rats.
METHODS: Rats were randomly divided into plain group and high altitude group and blood samples were collected through the orbital venous plexus after administration of 2 mg/kg warfarin. Warfarin concentrations in plasma samples were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and PK parameters were calculated by the non-compartment model using WinNonlin 8.1 software. Meanwhile, the expression of PXR, P-gp and CYP2C9 in liver tissues was also determined by western blotting. The effect of high altitude environment on PD of warfarin was explored by measuring activated partial thromboplastin time (APTT) and prothrombin time (PT) values and then calculated international normalized ratio (INR) values based on PT.
RESULTS: Significant changes in PK behaviors and PD of warfarin in high altitude-rats were observed. Compared with the plain-rats, the peak concentration (Cmax) and the area under the plasma concentration-time curve (AUC) increased significantly by 50.9% and 107.46%, respectively. At the same time, high altitude environment significantly inhibited the expression of PXR, P-gp and CYP2C9 in liver tissues. The results of the PD study showed that high altitude environments significantly prolonged PT, APTT and INR values.
CONCLUSIONS: High altitude environment inhibited the metabolism and increased the absorption of warfarin in rats and increased the effect of anticoagulant effect, suggesting that the optimal dose of warfarin for patients at high altitude should be reassessed.