Pharmacokinetics, Mass Balance and Metabolism of [14C]HSK21542, a Novel Kappa Opioid Receptor Agonist, in Humans.

BACKGROUND AND OBJECTIVE: HSK21542, a synthetic short-chain polypeptide, is a selective peripheral kappa opioid receptor (KOR) agonist. In this single-centre, non-randomized, open-label study, the pharmacokinetics, mass balance, metabolism and excretion of HSK21542 were investigated. METHODS: A single intravenous dose of 2 µg/0.212 µCi/kg [14C]HSK21542 was administered to six healthy male subjects. Samples of blood, urine and faeces were collected for quantitative determination of total radioactivity and unchanged HSK21542, and identification of metabolites. RESULTS: The mean total recovery was 81.89% of the radiolabelled dose over 240 h post-dose, with 35.60% and 46.30% excreted in faeces and urine, respectively. The mean maximum concentration (Cmax), the half-life (t1/2) and the area under the concentration-time curve (AUC0-t) of total radioactivity (TRA) in plasma were 20.4 ±4.16 ng Eq./g, 1.93 ± 0.322 h and 21.8 ± 2.93 h·ng Eq./g, respectively, while the Cmax, t1/2 and the AUC0-t of unchanged HSK21542 were 18.3 ± 3.36 ng/mL, 1.66 ± 0.185 h and 18.4 ± 2.24 h·ng/mL, respectively. The blood-to-plasma ratios of TRA at several times ranged from 0.46 to 0.54. [14C]HSK21542 was detected as the main circulating substance in plasma, accounting for 92.17% of the AUC of TRA. The unchanged parent compound was the only major radioactive chemical in urine (100.00% of TRA) and faeces (93.53% of TRA). Metabolites were very minor components. CONCLUSIONS: HSK21542 was barely metabolized in vivo and mainly excreted with unchanged HSK21542 as its main circulating component in plasma. It was speculated that renal excretion was the principal excretion pathway, and faecal excretion was the secondary pathway. CLINICAL TRIAL REGISTRATION NUMBER: NCT05835934.

A model based on machine learning for the prediction of cyclosporin A trough concentration in Chinese allo-HSCT patients.

BACKGROUND: Cyclosporin A is a calcineurin inhibitor which has a narrow therapeutic window and high interindividual variability. Various population pharmacokinetic models have been reported; however, professional software and technical personnel were needed and the variables of the models were limited. Therefore, the aim of this study was to establish a model based on machine learning to predict CsA trough concentrations in Chinese allo-HSCT patients. METHODS: A total of 7874 cases of CsA therapeutic drug monitoring data from 2069 allo-HSCT patients were retrospectively included. Sequential forward selection was used to select variable subsets, and eight different algorithms were applied to establish the prediction model. RESULTS: XGBoost exhibited the highest prediction ability. Except for the variables that were identified by previous studies, some rarely reported variables were found, such as norethindrone, WBC, PAB, and hCRP. The prediction accuracy within ±30% of the actual trough concentration was above 0.80, and the predictive ability of the models was demonstrated to be effective in external validation. CONCLUSION: In this study, models based on machine learning technology were established to predict CsA levels 3-4 days in advance during the early inpatient phase after HSCT. A new perspective for CsA clinical application is provided.

Development of Physiology Based Pharmacokinetic Model to Predict the Drug Interactions of Voriconazole and Venetoclax.

PURPOSE: Venetoclax (VEN), an anti-tumor drug that is a substrate of cytochrome P450 3A enzyme (CYP3A4), is used to treat leukemia. Voriconazole (VCZ) is an antifungal medication that inhibits CYP3A4. The goal of this study is to predict the effect of VCZ on VEN exposure. METHOD: Two physiological based pharmacokinetics (PBPK) models were developed for VCZ and VEN using the bottom-up and top-down method. VCZ model was also developed to describe the effect of CYP2C19 polymorphism on its pharmacokinetics (PK). The reversible inhibition constant (Ki) of VCZ for CYP3A4 was calibrated using drug-drug interaction (DDI) data of midazolam and VCZ. The clinical verified VCZ and VEN model were used to predict the DDI of VCZ and VEN at clinical dosing scenario. RESULT: VCZ model predicted VCZ exposure in the subjects of different CYP2C19 genotype and DDI related fold changes of sensitive CYP3A substrate with acceptable prediction error. VEN model can capture PK of VEN with acceptable prediction error. The DDI PBPK model predicted that VCZ increased the exposure of VEN by 4.5-9.6 fold. The increase in VEN exposure by VCZ was influenced by subject's CYP2C19 genotype. According to the therapeutic window, VEN dose should be reduced to 100 mg when co-administered with VCZ. CONCLUSION: The PBPK model developed here could support individual dose adjustment of VEN and DDI risk assessment. Predictions using the robust PBPK model confirmed that the 100 mg dose adjustment is still applicable in the presence of VCZ with high inter-individual viability.

Metabolic disposition of the EGFR covalent inhibitor furmonertinib in humans.

Furmonertinib was designed for the treatment of non-small cell lung cancer (NSCLC) patients with EGFR T790M mutation. In this study, we investigated the metabolic disposition and mass balance in humans and tissue distribution in rats. After a single oral administration of 97.9 µCi/81.5 mg [14C]-furmonertinib mesylate to six healthy male volunteers, the absorption process of furmonertinib was fast with a tmax of total plasma radioactivity at 0.75 h. Afterward, furmonertinib was extensively metabolized, with the parent drug and active metabolite AST5902 accounting for 1.68% and 0.97% of total radioactivity in plasma. The terminal t1/2 of total radioactivity in plasma was as long as 333 h, suggesting that the covalent binding of drug-related substances to plasma proteins was irreversible to a great extent. The most abundant metabolites identified in feces were desmethyl metabolite (AST5902), cysteine conjugate (M19), and parent drug (M0), which accounted for 6.28%, 5.52%, and 1.38% of the dose, respectively. After intragastric administration of 124 µCi/9.93 mg/kg [14C]-furmonertinib to rats, drug-related substances were widely and rapidly distributed in tissues within 4 h. The concentration of total radioactivity in the lung was 100-fold higher than that in rat plasma, which could be beneficial to the treatment of lung cancer. Mass balance in humans was achieved with 77.8% of the administered dose recovered in excretions within 35 days after administration, including 6.63% and 71.2% in urine and feces, respectively. In conclusion, [14C]-furmonertinib is completely absorbed and rapidly distributed into lung tissue, extensively metabolized in humans, presented mostly as covalent conjugates in plasma, and slowly eliminated mostly via fecal route.

Feasibility study of 68Ga-labeled CAR T cells for in vivo tracking using micro-positron emission tomography imaging.

Clinical tracking of chimeric antigen receptor (CAR) T cells in vivo by positron emission tomography (PET) imaging is an area of intense interest. But the long-lived positron emitter-labeled CAR T cells stay in the liver and spleen for days or even weeks. Thus, the excessive absorbed effective dose becomes a major biosafety issue leading it difficult for clinical translation. In this study we used 68Ga, a commercially available short-lived positron emitter, to label CAR T cells for noninvasive cell tracking in vivo. CAR T cells could be tracked in vivo by 68Ga-PET imaging for at least 6 h. We showed a significant correlation between the distribution of 89Zr and 68Ga-labeled CAR T cells in the same tissues (lungs, liver, and spleen). The distribution and homing behavior of CAR T cells at the early period is highly correlated with the long-term fate of CAR T cells in vivo. And the effective absorbed dose of 68Ga-labeled CAR T cells is only one twenty-fourth of 89Zr-labeled CAR T cells, which was safe for clinical translation. We conclude the feasibility of 68Ga instead of 89Zr directly labeling CAR T cells for noninvasive tracking of the cells in vivo at an early stage based on PET imaging. This method provides a potential solution to the emerging need for safe and practical PET tracer for cell tracking clinically.

Pharmacokinetics, mass balance, and metabolism of [14C]vicagrel, a novel irreversible P2Y12 inhibitor in humans.

Vicagrel, a novel irreversible P2Y12 receptor inhibitor, is undergoing phase III trials for the treatment of acute coronary syndromes in China. In this study, we evaluated the pharmacokinetics, mass balance, and metabolism of vicagrel in six healthy male Chinese subjects after a single oral dose of 20 mg [14C]vicagrel (120 µCi). Vicagrel absorption was fast (Tmax = 0.625 h), and the mean t1/2 of vicagrel-related components was ~38.0 h in both plasma and blood. The blood-to-plasma radioactivity AUCinf ratio was 0.55, suggesting preferential distribution of drug-related material in plasma. At 168 h after oral administration, the mean cumulative excreted radioactivity was 96.71% of the dose, including 68.03% in urine and 28.67% in feces. A total of 22 metabolites were identified, and the parent vicagrel was not detected in plasma, urine, or feces. The most important metabolic spot of vicagrel was on the thiophene ring. In plasma pretreated with the derivatization reagent, M9-2, which is a methylated metabolite after thiophene ring opening, was the predominant drug-related component, accounting for 39.43% of the radioactivity in pooled AUC0-8 h plasma. M4, a mono-oxidation metabolite upon ring-opening, was the most abundant metabolite in urine, accounting for 16.25% of the dose, followed by M3-1, accounting for 12.59% of the dose. By comparison, M21 was the major metabolite in feces, accounting for 6.81% of the dose. Overall, renal elimination plays a crucial role in vicagrel disposition, and the thiophene ring is the predominant metabolic site.

Multicenter-Based Population Pharmacokinetic Analysis of Ciclosporin in Hematopoietic Stem Cell Transplantation Patients.

PURPOSE: To explore the contribution of physiological characteristics to variability in ciclosporin pharmacokinetics in hematopoietic stem cell transplantation patients. METHODS: Clinical data from 563 patients were collected from centers in three regions. Ciclosporin concentrations were measured using immunoassays. The patients' demographics, hematological and biological indicators, coadministered drugs, region, and disease diagnosis were recorded from medical records. Data analysis was performed using NONMEM based on a one-compartment model to describe the pharmacokinetics of ciclosporin. The reliability and stability of the final model were evaluated using bootstrap resampling, goodness-of-fit plots, and prediction-corrected visual predictive checks. RESULTS: The population estimate of the clearance (CL) was 30.4 L/h, the volume of distribution (V) was 874.0 L and the bioavailability (F) was 81.1%. The between-subject variability in these parameters was 26.3, 68.0, and 110.8%, respectively. Coadministration of fluconazole, itraconazole, or voriconazole decreased CL by 17.6%, 28.4%, and 29.2%, respectively. Females' CL increased by approximately 12.0%. In addition, CL and V decreased with hematocrit, total protein, and uric acid increase, and CL also decreased with age and aspartate aminotransferase increase. However, CL increased with creatinine clearance increase. CONCLUSIONS: A multicenter-based population pharmacokinetic model of ciclosporin was established. The pharmacokinetics of ciclosporin exhibited discrepancies among different regions.

Metabolism and disposition of pyrotinib in healthy male volunteers: covalent binding with human plasma protein.

Pyrotinib is a novel irreversible EGFR/HER2 dual tyrosine kinase inhibitor that is used to treat HER2-positive breast cancer. In this study we investigated the metabolism and disposition of pyrotinib in six healthy Chinese men after a single oral dose of 402 mg of [14C]pyrotinib. At 240 h postdose, the mean cumulative excretion of the dose radioactivity was 92.6%, including 1.7% in urine and 90.9% in feces. In feces, oxidative metabolites were detected as major drug-related materials and the primary metabolic pathways were O-depicoline (M1), oxidation of pyrrolidine (M5), and oxidation of pyridine (M6-1, M6-2, M6-3, and M6-4). In plasma, the major circulating entities identified were pyrotinib, SHR150980 (M1), SHR151468 (M2), and SHR151136 (M5), accounting for 10.9%, 1.9%, 1.0%, and 3.0%, respectively, of the total plasma radioactivity based on the AUC0-∞ ratios. Approximately 58.3% of the total plasma radioactivity AUC0-∞ was attributed to covalently bound materials. After incubation of human plasma with [14C]pyrotinib at 37 °C for 2, 5, 8, and 24 h, the recovery of radioactivity by extraction was 97.4%, 91.8%, 69.6%, and 46.7%, respectively, revealing covalent binding occurred independently of enzymes. A group of pyrotinib adducts, including pyrotinib-lysine and pyrotinib adducts of the peptides Gly-Lys, Lys-Ala, Gly-Lys-Ala, and Lys-Ala-Ser, was identified after HCl hydrolysis of the incubated plasma. Therefore, the amino acid residue Lys190 of human serum albumin was proposed to covalently bind to pyrotinib via Michael addition. Finally, the covalently bound pyrotinib could dissociate from the human plasma protein and be metabolized by oxidation and excreted via feces.

Theory-based pharmacokinetics and pharmacodynamics of S- and R-warfarin and effects on international normalized ratio: influence of body size, composition and genotype in cardiac surgery patients.

AIMS: The aims of this study are to apply a theory-based mechanistic model to describe the pharmacokinetics (PK) and pharmacodynamics (PD) of S- and R-warfarin. METHODS: Clinical data were obtained from 264 patients. Total concentrations for S- and R-warfarin were measured by ultra-high performance liquid tandem mass spectrometry. Genotypes were measured using pyrosequencing. A sequential population PK parameter with data method was used to describe the international normalized ratio (INR) time course. Data were analyzed with NONMEM. Model evaluation was based on parameter plausibility and prediction-corrected visual predictive checks. RESULTS: Warfarin PK was described using a one-compartment model. CYP2C9 *1/*3 genotype had reduced clearance for S-warfarin, but increased clearance for R-warfarin. The in vitro parameters for the relationship between prothrombin complex activity (PCA) and INR were markedly different (A = 0.560, B = 0.386) from the theory-based values (A = 1, B = 0). There was a small difference between healthy subjects and patients. A sigmoid Emax PD model inhibiting PCA synthesis as a function of S-warfarin concentration predicted INR. Small R-warfarin effects was described by competitive antagonism of S-warfarin inhibition. Patients with VKORC1 AA and CYP4F2 CC or CT genotypes had lower C50 for S-warfarin. CONCLUSION: A theory-based PKPD model describes warfarin concentrations and clinical response. Expected PK and PD genotype effects were confirmed. The role of predicted fat free mass with theory-based allometric scaling of PK parameters was identified. R-warfarin had a minor effect compared with S-warfarin on PCA synthesis. INR is predictable from 1/PCA in vivo.

Warfarin dosage adjustment strategy in Chinese population.

BACKGROUND: Blood anticoagulation after heart valve replacement is a recognized difficulty all over the world. In this study, we identified the effect of amiodarone on the function of warfarin and confirmed the countermeasure by concluding the genotype distribution of vitamin K epoxide reductase complex 1 (VKORC1) and cytochrome P450 2C9 (CYP2C9) of the patient to predict the security dose of warfarin. METHODS: Studying on the VKORC1 (-1639G>A) and CYP2C9 genotype of 271 cases on heart valve replacement in the First Affiliated Hospital of Soochow University from Jan. 2012 to Jan. 2014. Warfarin's multivariable regression equation was taken to calculate their warfarin dosage. In the study, 80 of them were selected and divided into 4 groups according to their different warfarin dosage and their usage of amiodaron. The differences of INR values at the 5(th), 8(th), 11(th), 14(th) days of operation were analyzed. RESULTS: Among the 80 cases, VKORC1 (-1639G>A) AA types accounted for 90%, and AG types accounted for another 10%, while GG types were not found. In addition that, all of the patients (100%) had CYP2C9*1/*1 type, and CYP2C9*1/*3 had not appeared. There was significant difference in INR values between the groups who used amiodarone or not. The pharmacogenetic equation was accurate in the predicting of the warfarin dosage, so that satisfied anticoagulation efficacy had been achieved in 2 weeks after surgery. CONCLUSION: It is necessary for the patients to do the warfarin pharmacogenetic test to get the suitable dose before heart valve replacement. Amiodarone can enhance the anticoagulant efficacy of warfarin, so the dosages of warfarin should be reduced properly because of the medicine combination, and INR values must be monitored more frequently to make the anticoagulant process secure and efficient.

Ginkgo biloba extracts attenuate lipopolysaccharide-induced inflammatory responses in acute lung injury by inhibiting the COX-2 and NF-κB pathways.

In the present study, we analyzed the role of Ginkgo biloba extract in lipopolysaccharide(LPS)-induced acute lung injury (ALI). ALI was induced in mice by intratracheal instillation of LPS. G. biloba extract (12 and 24 mg·kg(-1)) and dexamethasone (2 mg·kg(-1)), as a positive control, were given by i.p. injection. The cells in the bronchoalveolar lavage fluid (BALF) were counted. The degree of animal lung edema was evaluated by measuring the wet/dry weight ratio. The superoxidase dismutase (SOD) and myeloperoxidase (MPO) activities were assayed by SOD and MPO kits, respectively. The levels of inflammatory mediators, tumor necrosis factor-a, interleukin-1b, and interleukin-6, were assayed by enzyme-linked immunosorbent assay. Pathological changes of lung tissues were observed by H&E staining. The levels of NF-κB p65 and COX-2 expression were detected by Western blotting. Compared to the LPS group, the treatment with the G. biloba extract at 12 and 24 mg·kg(-1) markedly attenuated the inflammatory cell numbers in the BALF, decreased NF-κB p65 and COX-2 expression, and improved SOD activity, and inhibited MPO activity. The histological changes of the lungs were also significantly improved. The results indicated that G. biloba extract has a protective effect on LPS-induced acute lung injury in mice. The protective mechanism of G. biloba extract may be partly attributed to the inhibition of NF-κB p65 and COX-2 activation.

Population pharmacokinetics and individualized dosage prediction of cyclosporine in allogeneic hematopoietic stem cell transplant patients.

BACKGROUND: Cyclosporine (CsA), a potent immunosuppressive agent used to prevent rejection, is characterized by large individual variability. The purpose of this study was to explore the pharmacokinetic characteristics of CsA and establish a CsA population pharmacokinetic model that could be used for personalized therapy in allogeneic hematopoietic stem cell transplant (allo-HSCT) patients. METHODS: Clinical data were obtained from 117 allo-HSCT patients. The data analysis was performed using NONMEM software. A first-order conditional estimation with interaction (FOCE-I) method within NONMEM was used to estimate the parameters. The covariates, including demographics, hematological indices, biochemical levels, concurrent drugs, and genetic polymorphisms of CYP3A4, CYP3A5, and ABCB1, were evaluated quantitatively. The stability of the final model was validated by a nonparametric bootstrap procedure. RESULTS: A total of 1,571 observed concentrations were collected. A 1-compartment model with first-order absorption and elimination adequately described the pharmacokinetics of CsA. The typical values for clearance (CL), volume of distribution (V), and bioavailability were 29.6 L/hr, 605 L, and 0.619, respectively. The interindividual variability of these parameters was 20.4, 66.1, and 30.4%, respectively. The residual error was 31.4% and 23.7 ng/mL. The duration of CsA therapy, hematocrit, antifungal agent administration, triglycerides, and weight were identified as the main covariates that influenced CL, and hematocrit had a significant effect on V. The internal validation showed that the final model was stable and accurate. CONCLUSIONS: This study established a population pharmacokinetic model of CsA in allo-HSCT patients that could provide the foundation for personalized use of CsA in the clinic.

Circadian variability of pharmacokinetics of cisplatin in patients with non-small-cell lung carcinoma: analysis with the NONMEM program.

PURPOSE: The aim of this study was to describe the nonlinear pharmacokinetics of total and unbound plasma cisplatin under different administered time in patients with non-small-cell lung carcinoma. METHODS: Patients receiving chemotherapy with cisplatin were included in this analysis. Patients were divided into two groups depending on the administrated time of cisplatin: 6:00 (Group A) and 18:00 (Group B). The population pharmacokinetics of cisplatin was calculated using nonlinear mixed-effects modeling (NONMEM) method, and the possible influence of covariates on the population pharmacokinetics of cisplatin was also explored. RESULTS: The pharmacokinetics of total and unbound cisplatin could be described well by a linear two-compartment model. The mean population estimates for total and unbound drug were, respectively, 0.463 (17.0 %) and 25.4 (14.0 %) l h⁻¹ for clearance (CL), 24.2 (19.9 %) and 20.5 (27.1 %) l for central distribution volume (V1), 10.2 (18.2 %) and 9.82 (28.1) l h⁻¹ for intercompartmental clearance (Q) and 32.0 (24.1 %) and 6.77 (25.4 %) l for peripheral compartment volume (V2). The CL for total and unbound cisplatin was dependent on body surface area (BSA). When cisplatin was administered at 18:00, the CL was 1.38- and 1.22-fold higher than those administered at 6:00 for total and unbound cisplatin, respectively (P < 0.05). The mean parameter estimates from a nonparametric bootstrap procedure were comparable and within 5 % of the estimates from NONMEM. CONCLUSIONS: The results showed that circadian could influence the metabolism of cisplatin and suggested the conventional dose adjustment of cisplatin based on BSA.

[Population pharmacokinetic study of tacrolimus in patients with hematopoietic stem cell transplant].

The present study is to establish the population pharmacokinetic (PPK) model of tacrolimus and to estimate PPK parameters of tacrolimus for the individualization of tacrolimus administration in patients with hematopoietic stem cell transplant. A total of 671 blood samples were collected from 68 hematopoietic stem cell transplant patients and clinical data were retrospectively collected from the medical records of these patients. Population pharmacokinetical analysis was performed using the nonlinear mixed-effect model (NONMEM) program. The Bootstrap and data splitting were used simultaneously to validate the final population pharmacokinetical models. The basic structural model was best described as one-compartment pharmacokinetical model with first-order absorption and elimination. A number of covariates including demographic characteristic, biochemical and hematological index, combined drugs, inter-occasion variability (IOV) and other variables, e.g. primary disease, post operation days (POD), the type of transplantation and the sources of donor, were screened for their influence on the pharmacokinetic parameters of tacrolimus. The population typical values of tacrolimus CL, V, F were 12.1 L x h(-1), 686 L, 42.2%; and the inter-individual variability of these parameters were 23.5%, 96.4%, 43.8%, respectively. The absorption rate constant was fixed 4.3 h(-1). The residual error between observed and model- predicted concentration was 3.03 ng x mL(-1). The CYP enzyme inhibitor (INHI), POD and age were identified to be the main covariates that influence tacrolimus CL, and hemoglobulin (HGB) was the main covariate that may explain the variability in tacrolimus V. The IOV of CL, V, F were 22.2%, 6.23%, 30.3%, respectively. The population pharmacokinetic data obtained in the present study have significant clinical value for the individualization of tacrolimus therapy in hematopoietic stem cell transplant patients.