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Patients with hematological malignancies are prone to invasive fungal disease due to long-term chemotherapy or radiotherapy. Voriconazole is a second-generation triazole broad-spectrum antibiotic used to prevent or treat invasive fungal infections. Many population pharmacokinetic (pop PK) models have been published for voriconazole, and various diagnostic methods are available to validate the performance of these pop PK models. However, most of the published models have not been strictly evaluated externally. The purpose of this study is to evaluate these models externally and assess their predictive capabilities.The external dataset consists of adults receiving voriconazole treatment at Fujian Medical University Union Hospital. We re-established the published models based on their final estimated values in the literature and used our external dataset for initial screening. Each model was evaluated based on the following outcomes: prediction-based diagnostics, prediction- and variability-corrected visual predictive check (pvcVPC), normalized prediction distribution errors (NPDE), and Bayesian simulation results with one to two prior observations.A total of 237 samples from 166 patients were collected as an external dataset. After screening, six candidate models suitable for the external dataset were finally obtained for comparison. Among the models, none demonstrated excellent predictive performance. Bayesian simulation shows that all models' prediction precision and accuracy were significantly improved when one or two prior concentrations were given.The published pop PK models of voriconazole have significant differences in prediction performance, and none of the models could perfectly predict the concentrations of voriconazole for our data. Therefore, extensive evaluation should precede the adoption of any model in clinical practice.

PURPOSE: To investigate the metabolic pathways of triapine in primary cultures of human hepatocytes and human hepatic subcellular fractions; to investigate interactions of triapine with tenofovir and emtricitabine; and to evaluate triapine as a perpetrator of drug interactions. The results will better inform future clinical studies of triapine, a radiation sensitizer currently being studied in a phase III study. METHODS: Triapine was incubated with human hepatocytes and subcellular fractions in the presence of a number of inhibitors of drug metabolizing enzymes. Triapine depletion was monitored by LC-MS/MS. Tenofovir and emtricitabine were co-incubated with triapine in primary cultures of human hepatocytes. Triapine was incubated with a CYP probe cocktail and human liver microsomes, followed by LC-MS/MS monitoring of CYP specific metabolite formation. RESULTS: Triapine was not metabolized by FMO, AO/XO, MAO-A/B, or NAT-1/2, but was metabolized by CYP450s. CYP1A2 accounted for most of the depletion of triapine. Tenofovir and emtricitabine did not alter triapine depletion. Triapine reduced CYP1A2 activity and increased CYP2C19 activity. CONCLUSION: CYP1A2 metabolism is the major metabolic pathway for triapine. Triapine may be evaluated in cancer patients in the setting of HIV with emtricitabine or tenofovir treatment. Confirmatory clinical trials may further define the in vivo triapine metabolic fate and quantify any drug-drug interactions.

Objective: Busulfan (BU) is a bi-functional DNA-alkylating agent used in patients undergoing hematopoietic stem cell transplantation (HSCT). Over the last decades, several population pharmacokinetic (pop PK) models of BU have been established, but external evaluation has not been performed for almost all models. The purpose of the study was to evaluate the predictive performance of published pop PK models of intravenous BU in adults using an independent dataset from Chinese HSCT patients, and to identify the best model to guide personalized dosing.Methods: The external evaluation methods included prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. In prediction-based diagnostics, the relative prediction error (PE%) was calculated by comparing the population predicted concentration (PRED) with the observations. Simulation-based diagnostics included the prediction- and variability-corrected visual predictive check (pvcVPC) and the normalized prediction distribution error (NPDE). Bayesian forecasting was executed by giving prior one to four observations. The factors influencing the model predictability, including the impact of structural models, were assessed.Results: A total of 440 concentrations (110 patients) were obtained for analysis. Based on prediction-based diagnostics and Bayesian forecasting, preferable predictive performance was observed in the model developed by Huang et al. The median PE% was -1.44% which was closest to 0, and the maximum F20 of 57.27% and F30 of 72.73% were achieved. Bayesian forecasting demonstrated that prior concentrations remarkably improved the prediction precision and accuracy of all models, even with only one prior concentration.Conclusion: This is the first study to comprehensively evaluate published pop PK models of BU. The model built by Huang et al. had satisfactory predictive performance, which can be used to guide individualized dosage adjustment of BU in Chinese patients.

Isavuconazole (ISA) is an azole antifungal used in the treatment of invasive aspergillosis and mucormycosis. Patients with mild or moderate hepatic impairment have lower clearance (CL) than the healthy population. Currently, there are no data on ISA in patients with severe hepatic impairment (Child-Pugh class C). The purposes of this study were to build a physiologically based pharmacokinetic (PBPK) model to describe the pharmacokinetics (PK) of intravenous ISA and to predict changes in ISA disposition in different patient populations and in patients with hepatic impairment so as to guide personalized dosing. By incorporating the systemic and drug-specific parameters of ISA, the model was initially developed in a healthy population and was validated with 10 independent PK profiles obtained from healthy subjects and from patients with normal liver function. The results showed satisfactory predictive capacity; most of the relative predictive errors were within ±30% for the area under the concentration-time curve (AUC) and the maximum concentration of the drug in serum (C(max)). The observed concentration-time profiles of ISA in plasma were well described by the model-predicted profiles. The model adequately predicted the reduced CL of ISA in patients with mild or moderate hepatic impairment. Furthermore, the model predicted a decrease in CL of about 60% in patients with severe hepatic impairment. Therefore, we recommend reducing the dose by 50% in patients with severe hepatic impairment. The model also predicted differences in the PK of ISA between Caucasian and Asian populations, with a Chinese/Caucasian CL ratio of 0.67. The PBPK model of ISA that was developed provides a reasonable approach for optimizing the dosage regimen in different ethnic populations and in patients with severe hepatic impairment.

Pregnancy is associated with several physiological changes that can alter the pharmacokinetics (PK) and pharmacodynamics of drugs. These may require dosing changes in pregnant women to achieve drug exposures comparable to the nonpregnant population. There is, however, limited information available on the PK and pharmacodynamics of drugs used during pregnancy. Practical difficulties in performing PK studies and potential liability issues are often the reasons for the availability of limited information. Over the past several years, there has been a rapid development in the application of various modeling strategies such as population PK and physiologically based PK modeling to provide guidance on drug dosing in this special patient population. Population PK models rely on measured PK data, whereas physiologically based PK models integrate physiological, preclinical, and clinical data to quantify changes in PK of drugs in various patient populations. These modeling strategies offer a promising approach to identify the drugs with PK changes during pregnancy and guide dose adjustment in pregnant women. This review focuses on PBPK modeling to guide drug therpay in pregnancy.

Background In the United States, drug addiction has become a nationwide health crisis. Recently, buprenorphine (BUP), a maintenance therapy approved by the Food and Drug Administration, has been increasingly used in pregnant women for the treatment of opioid use disorder. Pregnancy is associated with various anatomic and physiological changes, which may result in altered drug pharmacokinetics (PKs). Previously, we reported that dose-adjusted plasma concentrations of BUP are lower during pregnancy than after pregnancy. The mechanism(s) responsible for this difference has not yet been defined. Our study aimed to evaluate alterations in cytochromes P450 (CYP)- and uridine diphosphate glucunosyltransferases (UGT)-mediated metabolism of BUP during pregnancy to determine the mechanism(s) responsible for this observation. Methods Data from 2 clinical studies were included in the current analysis. Study 1 was a prospective, open-labeled, nonrandomized longitudinal BUP PK study in pregnant women with a singleton gestation, stabilized on twice-daily sublingual BUP opioid substitution therapy. Each subject participated in up to 3 studies during and after pregnancy (the second, third trimester, and postpartum). The design of study 2 was similar to study 1, with patients evaluated at different time points during the pregnancy (first, second-half of pregnancy), as well as during the postpartum period. In addition, the dosing frequency of BUP study 2 participants was not restricted to twice-daily dosing. At each study visit, blood samples were collected before a BUP dose, followed by multiple collection times (10-12) after the dose, for up to 12 hours or till the end of the dosing interval. Plasma concentrations of BUP and 3 metabolites were quantified using validated ultraperformance liquid chromatography-tandem mass spectrometric assays. Results In total, 19, 18, and 14 subjects completed the PK study during 1/2 trimester, third trimester, and postpartum, respectively. The AUC ratios of norbuprenorphine and norbuprenorphine glucuronide to buprenorphine, a measure of CYP3A mediated N-demethylation, were 1.89, 1.84, and 1.33 during the first and second, third trimesters, and postpartum, respectively. The AUC ratios of buprenorphine glucuronide to BUP, indicative of UGT activity, were 0.71, 2.07, and 0.3 at first/second trimesters, third trimester, and postpartum, respectively. Linear mixed-effect modeling analysis indicated that the AUC ratios of CYP- and UGT-mediated metabolism of BUP were significantly higher during pregnancy compared with postpartum. Conclusions The CYP and UGT activities were significantly increased as determined by the metabolic ratios of BUP during pregnancy compared with the postpartum period. The increased UGT activity appeared to account for a substantial part of the observed change in metabolic activity during pregnancy. This is in agreement with the need for BUP dose increment in pregnant women to reach similar BUP exposure and therapeutic effect as in nonpregnant subjects.