Prediction of Pharmacokinetics and Penetration of Moxifloxacin in Human with Intra-Abdominal Infection Based on Extrapolated PBPK Model

Predictive Performance of Physiologically Based Pharmacokinetic Modelling of Beta-Lactam Antibiotic Concentrations in Adipose, Bone, and Muscle Tissues

Physiologically based pharmacokinetic (PBPK) models consist of compartments representing different tissues. As most models are only verified based on plasma concentrations, it is unclear how reliable associated tissue profiles are. This study aimed to assess the accuracy of PBPK-predicted beta-lactam antibiotic concentrations in different tissues and assess the impact of using effect site concentrations for evaluation of target attainment. Adipose, bone, and muscle concentrations of five beta-lactams (piperacillin, cefazolin, cefuroxime, ceftazidime, and meropenem) in healthy adults were collected from literature and compared with PBPK predictions. Model performance was evaluated with average fold errors (AFEs) and absolute AFEs (AAFEs) between predicted and observed concentrations. In total, 26 studies were included, 14 of which reported total tissue concentrations and 12 unbound interstitial fluid (uISF) concentrations. Concurrent plasma concentrations, used as baseline verification of the models, were fairly accurate (AFE: 1.14, AAFE: 1.50). Predicted total tissue concentrations were less accurate (AFE: 0.68, AAFE: 1.89). A slight trend for underprediction was observed but none of the studies had AFE or AAFE values outside threefold. Similarly, predictions of microdialysis-derived uISF concentrations were less accurate than plasma concentration predictions (AFE: 1.52, AAFE: 2.32). uISF concentrations tended to be overpredicted and two studies had AFEs and AAFEs outside threefold. Pharmacodynamic simulations in our case showed only a limited impact of using uISF concentrations instead of unbound plasma concentrations on target attainment rates. The results of this study illustrate the limitations of current PBPK models to predict tissue concentrations and the associated need for more accurate models. SIGNIFICANCE STATEMENT: Clinical inaccessibility of local effect site concentrations precipitates a need for predictive methods for the estimation of tissue concentrations. This is the first study in which the accuracy of PBPK-predicted tissue concentrations of beta-lactam antibiotics in humans were assessed. Predicted tissue concentrations were found to be less accurate than concurrent predicted plasma concentrations. When using PBPK models to predict tissue concentrations, this potential relative loss of accuracy should be acknowledged when clinical tissue concentrations are unavailable to verify predictions.

Migalastat Tissue Distribution: Extrapolation From Mice to Humans Using Pharmacokinetic Modeling and Comparison With Agalsidase Beta Tissue Distribution in Mice

Approved therapies for Fabry disease (FD) include migalastat, an oral pharmacological chaperone, and agalsidase beta and agalsidase alfa, 2 forms of enzyme replacement therapy. Broad tissue distribution may be beneficial for clinical efficacy in FD, which has severe manifestations in multiple organs. Here, migalastat and agalsidase beta biodistribution were assessed in mice and modeled using physiologically based pharmacokinetic (PBPK) analysis, and migalastat biodistribution was subsequently extrapolated to humans. In mice, migalastat concentration was highest in kidneys and the small intestine, 2 FD-relevant organs. Agalsidase beta was predominantly sequestered in the liver and spleen (organs unaffected in FD). PBPK modeling predicted that migalastat 123 mg every other day resulted in concentrations exceeding the in vitro half-maximal effective concentration in kidneys, small intestine, skin, heart, and liver in human subjects. However, extrapolation of mouse agalsidase beta concentrations to humans was unsuccessful. In conclusion, migalastat may distribute to tissues that are inaccessible to intravenous agalsidase beta in mice, and extrapolation of mouse migalastat concentrations to humans showed adequate tissue penetration, particularly in FD-relevant organs.

Involvement of glutamate receptors of the paragigantocellularis lateralis nucleus in the pain modulatory effect of 17β-estradiol in male rats

The pain modulatory role of the paragigantocellularis lateralis nucleus (LPGi) and the 17β-estradiol has thoroughly been probed. This study investigates the contribution of ionotropic glutamate receptors in pain modulatory effect of intra-LPGi injection of 17β-estradiol. For this purpose, the LPGi nucleus cannulation was performed and drugs were injected into this nucleus, 15 min prior to the formalin test. The duration of formalin-induced flexing and licking behaviors was recorded for 60 min immediately after formalin injection. The results showed that the flexing behavior is significantly decreased by intra-LPGi injection of 0.8 µmol 17β-estradiol duringboth phases of formalin test (P < 0.001). However, 17β-estradiol attenuated the licking duration only in the second phase (P < 0.001). Interestingly, NMDA and AMPA/kainate receptor antagonists (AP5 and CNQX, respectively) significantly counteracted the analgesic effect of intra-LPGi injection of 17β-estradiol in both phases of the formalin test (P < 0.001). Consequently, the revealing results showed that the analgesic effect of intra-LPGi injection of 17β-estradiol on acute inflammatory pain might be mediated via the activation of ionotropic glutamate receptors.

Enzyme and Transporter Kinetics for CPT-11 (Irinotecan) and SN-38: An Insight on Tumor Tissue Compartment Pharmacokinetics Using PBPK

BACKGROUND

Computational tools are becoming more and more powerful and comprehensive as compared to past decades in facilitating pharmaceutical, pharmacological and clinical practice. Anticancer agents are used either as monotherapy or in combination therapy to treat malignant conditions of the body. A single antineoplastic agent may be used in different types of malignancies at different doses according to the stage of the disease.

OBJECTIVE

To study the behavior of CPT-11 (Irinotecan) and its metabolite SN-38 in tumor tissue compartment through the Whole Body-Physiologically Pharmacokinetics (WB-PBPK) and to determine the activity of metabolic enzymes and transporters participating in the disposition of CPT-11 and SN-38 working in their physiological environment inside the human body.

METHODS

Whole body PBPK approach is used to determine the activity of different metabolic enzymes and transporters involved in the disposition of CPT-11 and its active metabolite, SN-38. The concentrations and pharmacokinetic parameters of the parent compound and its metabolite administered at clinically applicable dose via the intravenous route in the tumor tissue are predicted using this approach.

RESULTS

The activity rate constants of metabolic enzymes and transporters of CPT-11 are derived at their natural anatomic locations. Concentration-time curves of CPT-11 and SN-38 with their 5th to 95th percentage range are achieved at the tumor tissue level. Mean tumor tissue pharmacokinetics of both compounds are determined in a population of 100 individuals.

CONCLUSION

Tumor tissue concentration-time curves of CPT-11 and SN-38 can be determined via PBPK modeling. Rate constants of enzymes and transporters can be shown for healthy and tumor bearing individuals. The results will throw light on the effective concentration of active compound at its target tissue at the clinically applied IV dose.

Predicting the Effects of Different Triazole Antifungal Agents on the Pharmacokinetics of Tamoxifen

Tamoxifen is an antiestrogen drug that is widely used in the adjuvant chemotherapy of estrogen receptor-α (ERα)-positive breast cancer. Chemotherapy could suppress immune function in breast cancer patients, which may cause invasive fungal infections (IFIs). Triazoles (voriconazole, fluconazole, and itraconazole) were commonly used for IFI. The physiologically based pharmacokinetic (PBPK) models were developed to investigate the influence of different triazoles on tamoxifen pharmacokinetics in this paper. To investigate the influence of different triazoles (voriconazole, fluconazole, itraconazole) on tamoxifen pharmacokinetics. Adjusted physicochemical data and pharmacokinetic parameters of voriconazole, fluconazole, itraconazole, and tamoxifen were obtained from published literatures. PBPK models were built and verified in healthy subjects using GastroPlus™. Voriconazole, itraconazole, and tamoxifen were administered orally. Fluconazole was administered intravenously. Simulated plasma concentration-time curves of the voriconazole, fluconazole, itraconazole, and tamoxifen showed good agreement with the observed profiles, respectively. The DDI simulations showed that the pharmacokinetic parameters of tamoxifen were increased by various degrees when coadministered with different triazoles. In healthy subjects, the area under the plasma concentration-time curve from 0 to t h (AUC_0-t) of tamoxifen was increased by 41%, 5%, and1% when coadministrated with voriconazole, fluconazole, and itraconazole, respectively. The PBPK models adequately characterized the pharmacokinetics of tamoxifen and triazoles. Among the three triazoles, voriconazole exhibited the greatest effect on tamoxifen pharmacokinetics. In clinical practice, an effective dosage adjustment of tamoxifen may need to be considered and TDM for tamoxifen is advisable to guide dosing and optimize therapy when coadministered with voriconazole.

Influence of different proton pump inhibitors on the pharmacokinetics of voriconazole

This study aimed to determine the influence of proton pump inhibitors (PPIs) on the pharmacokinetics of voriconazole and to characterise potential drug-drug interactions (DDIs) between voriconazole and various PPIs (omeprazole, esomeprazole, lansoprazole and rabeprazole). Using adjusted physicochemical data and the pharmacokinetic (PK) parameters of voriconazole and PPIs, physiologically based pharmacokinetic (PBPK) models were built and were verified in healthy subjects using GastroPlus^TM to predict the plasma concentration-time profiles of voriconazole and PPIs. These models were then used to assess potential DDIs for voriconazole when administered with PPIs. The results indicated the PBPK model-simulated plasma concentration-time profiles of both voriconazole and PPIs were consistent with the observed profiles. In addition, the DDI simulations suggested that the PK values of voriconazole increased to various degrees when combined with several PPIs. The area under the plasma concentration-time curve for the time of the simulation (AUC_0-t) of voriconazole was increased by 39%, 18%, 12% and 1% when co-administered with omeprazole, esomeprazole, lansoprazole and rabeprazole, respectively. Omeprazole was the most potent CYP2C19 inhibitor tested, whereas rabeprazole had no influence on voriconazole (omeprazole > esomeprazole > lansoprazole > rabeprazole). However, in consideration of the therapeutic concentration range, dosage adjustment of voriconazole is unnecessary regardless of which PPI was co-administered.

Application of Physiologically Based Absorption Modeling to Characterize the Pharmacokinetic Profiles of Oral Extended Release Methylphenidate Products in Adults

A previously presented physiologically-based pharmacokinetic model for immediate release (IR) methylphenidate (MPH) was extended to characterize the pharmacokinetic behaviors of oral extended release (ER) MPH formulations in adults for the first time. Information on the anatomy and physiology of the gastrointestinal (GI) tract, together with the biopharmaceutical properties of MPH, was integrated into the original model, with model parameters representing hepatic metabolism and intestinal non-specific loss recalibrated against in vitro and in vivo kinetic data sets with IR MPH. A Weibull function was implemented to describe the dissolution of different ER formulations. A variety of mathematical functions can be utilized to account for the engineered release/dissolution technologies to achieve better model performance. The physiological absorption model tracked well the plasma concentration profiles in adults receiving a multilayer-release MPH formulation or Metadate CD, while some degree of discrepancy was observed between predicted and observed plasma concentration profiles for Ritalin LA and Medikinet Retard. A local sensitivity analysis demonstrated that model parameters associated with the GI tract significantly influenced model predicted plasma MPH concentrations, albeit to varying degrees, suggesting the importance of better understanding the GI tract physiology, along with the intestinal non-specific loss of MPH. The model provides a quantitative tool to predict the biphasic plasma time course data for ER MPH, helping elucidate factors responsible for the diverse plasma MPH concentration profiles following oral dosing of different ER formulations.

Drug-drug interactions between moxifloxacin and rifampicin based on pharmacokinetics in vivo in rats

Moxifloxacin and rifampicin are all the first-line options for the treatment of active tuberculosis, which are often combined for the treatment of multidrug resistance pulmonary tuberculosis in clinic. However, the potential drug-drug interactions between moxifloxacin and rifampicin were unknown. The aim of this study was to investigate the drug-drug interactions between moxifloxacin and rifampicin based on their pharmacokinetics in vivo after oral administration of the single drug and both drugs, and reveal their mutual effects on their pharmacokinetics. Eighteen male Sprague-Dawley rats were randomly assigned to three groups: moxifloxacin group, rifampicin group and moxifloxacin + rifampicin group. Plasma concentrations of moxifloxacin and rifampicin were determined using LC-MS at the designated time points after drug administration, and the main pharmacokinetic parameters were calculated. In addition, effects of moxifloxacin and rifampicin on their metabolic rate and absorption were investigated using rat liver microsome incubation systems and Caco-2 cell transwell model. The main pharmacokinetic parameters of moxifloxacin including Tmax , Cmax , t1/2 and AUC(0-t) increased more in the moxifloxacin + rifampicin group than in the moxifloxacin group, but the difference was not significant (p > 0.05). However, the pharmacokinetic parameters of rifampicin, including peak concentration, area under the concentration-time curve, half-life and the area under the first moment plasma concentration-time curve, increased significantly (p < 0.05) compared with the rifampicin group, and the time to peak concentration decreased significantly (p < 0.05). The mean residence time of rifampicin also increased in moxifloxacin + rifampicin group compared with the rifampicin group, but the difference was not significant (p > 0.05). The rat liver microsome incubation experiment indicated that moxifloxacin could increase the metabolic rate of rifampicin from 23.7 to 38.7 min. However, the Caco-2 cell transwell experiment showed that moxifloxacin could not affect the absorption rate of rifampicin. These changes could enhance the drug efficacy, but they could also cause drug accumulation, which might induce adverse effect, so it was suggested that the drug dosage should be adjusted and the drug concentration in plasma should be monitored if moxifloxacin and rifampicin are co-administered. Copyright © 2016 John Wiley & Sons, Ltd.

Evaluating a physiologically based pharmacokinetic model for predicting the pharmacokinetics of midazolam in Chinese after oral administration

AIM

To evaluate the SimCYP simulator ethnicity-specific population model for predicting the pharmacokinetics of midazolam, a typical CYP3A4/5 substrate, in Chinese after oral administration.

METHODS

The physiologically based pharmacokinetic (PBPK) model for midazolam was developed using a SimCYP population-based simulator incorporating Chinese population demographic, physiological and enzyme data. A clinical trial was conducted in 40 Chinese subjects (the half was females) receiving a single oral dose of 15 mg midazolam. The subjects were separated into 4 groups based on age (20-50, 51-65, 66-75, and above 76 years), and the pharmacokinetics profiles of each age- and gender-group were determined, and the results were used to verify the PBPK model.

RESULTS

Following oral administration, the simulated profiles of midazolam plasma concentrations over time in virtual Chinese were in good agreement with the observed profiles, as were AUC and Cmax. Moreover, for subjects of varying ages (20-80 years), the ratios of predicted to observed clearances were between 0.86 and 1.12.

CONCLUSION

The SimCYP PBPK model accurately predicted the pharmacokinetics of midazolam in Chinese from youth to old age. This study may provide novel insight into the prediction of CYP3A4/5-mediated pharmacokinetics in the Chinese population relative to Caucasians and other ethnic groups, which can support the rational design of bridging clinical trials.

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification

Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms "PBPK" and "physiologically based pharmacokinetic model" to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines.