Guide to development of compound files for PBPK modeling in the Simcyp population-based simulator.

The Simcyp Simulator is a software platform for population physiologically-based pharmacokinetic (PBPK) modeling and simulation. It links in vitro data to in vivo absorption, distribution, metabolism, excretion and pharmacokinetic/pharmacodynamic outcomes to explore clinical scenarios and support drug development decisions, including regulatory submissions and drug labels. This tutorial describes the different input parameters required, as well as the considerations needed when developing a PBPK model within the Simulator, for a small molecule intended for oral administration. A case study showing the development and application of a PBPK model for ondansetron is herein used to aid the understanding of different PBPK model development concepts.

A Laboratory-Specific Scaling Factor to Predict the In Vivo Human Clearance of Aldehyde Oxidase Substrates.

Aldehyde oxidase (AO) efficiently metabolizes a range of compounds with N-containing heterocyclic aromatic rings and/or aldehydes. The limited knowledge of AO activity and abundance (in vitro and in vivo) has led to poor prediction of in vivo systemic clearance (CL) using in vitro-to-in vivo extrapolation approaches, which for drugs in development can lead to their discontinuation. We aimed to identify appropriate scaling factors to predict AO CL of future new chemical entities (NCEs). The metabolism of six AO substrates was measured in human liver cytosol (HLC) and S9 fractions. Measured blood-to-plasma ratios and free fractions (in the in vitro system and in plasma) were used to develop physiologically based pharmacokinetic models for each compound. The impact of extrahepatic metabolism was explored, and the intrinsic clearance required to recover in vivo profiles was estimated and compared with in vitro measurements. Using HLC data and assuming only hepatic metabolism, a systematic underprediction of clearance was observed (average fold underprediction was 3.8). Adding extrahepatic metabolism improved the accuracy of the results (average fold error of 1.9). A workflow for predicting metabolism of an NCE by AO is proposed, and an empirical (laboratory-specific) scaling factor of three on the predicted intravenous CL allows a reasonable prediction of the available clinical data. Alternatively, considering also extrahepatic metabolism, an scaling factor of 6.5 applied on the intrinsic clearance could be used. Future research should focus on the impact of the in vitro study designs and the contribution of extrahepatic metabolism to AO-mediated clearance to understand the mechanisms behind the systematic underprediction. SIGNIFICANCE STATEMENT: This works describes the development of scaling factors to allow in vitro-in vivo extrapolation of the clearance of compounds by aldehyde oxidase metabolism in humans. In addition, physiologically based pharmacokinetic models were developed for each of the aldehyde oxidase substrate compounds investigated.

Electrospun Scaffolds Containing Silver-Doped Hydroxyapatite with Antimicrobial Properties for Applications in Orthopedic and Dental Bone Surgery.

Preventing the development of osteomyelitis while enhancing bone regeneration is challenging, with relatively little progress to date in translating promising technologies to the clinic. Nanoscale hydroxyapatite (nHA) has been employed as a bone graft substitute, and recent work has shown that it may be modified with silver to introduce antimicrobial activity against known pathogens. The aim of this study was to incorporate silver-doped nHA into electrospun scaffolds for applications in bone repair. Silver-doped nHA was produced using a modified, rapid mixing, wet precipitation method at 2, 5, 10 mol.% silver. The silver-doped nHA was added at 20 wt.% to a polycaprolactone solution for electrospinning. Bacteria studies demonstrated reduced bacterial presence, with Escherichia coli and Staphylococcus aureus undetectable after 96 h of exposure. Mesenchymal stem cells (MSCs) were used to study both toxicity and osteogenicity of the scaffolds using PrestoBlue® and alkaline phosphatase (ALP) assays. Innovative silver nHA scaffolds significantly reduced E. coli and S. aureus bacterial populations while maintaining cytocompatibility with mammalian cells and enhancing the differentiation of MSCs into osteoblasts. It was concluded that silver-doped nHA containing scaffolds have the potential to act as an antimicrobial device while supporting bone tissue healing for applications in orthopedic and dental bone surgery.

Population Pharmacokinetic Modeling of Tenofovir in the Genital Tract of Male HIV-Infected Patients.

The aims of this study were to describe the blood plasma (BP) and seminal plasma (SP) pharmacokinetics of tenofovir (TFV) in HIV-1-infected men, to assess the role of genetic polymorphism in the variability of TFV transfer into the male genital tract, and to evaluate the impact of TFV SP exposure on seminal plasma HIV load (spVL). Men from the Evarist-ANRS EP 49 study treated with TFV as part of their antiretroviral therapy were included in the study. A total of 248 and 217 TFV BP and SP concentrations from 129 men were available for the analysis. For pharmacogenetic assessment, a total of 121 single nucleotide polymorphisms (SNP) were genotyped. Data were analyzed using a nonlinear mixed-effects modeling approach. TFV pharmacokinetics were best described by a two-compartment model for BP and by an effect compartment with different input and output constants for SP. TFV exposures (area under the concentration-time curve from 0 to 24 h [AUC0-24]) were higher in SP than in BP (median AUC0-24, 7.01 versus 2.97 mg · liter-1 · h, respectively). The median (range) SP-to-BP AUC0-24 ratio was 2.24 (0.53 to 34.13). After correction for multiple testing, none of the SNPs were significantly associated with the TFV transfer rate constant. The impact of the TFV SP AUC0-24 or TFV SP-to-BP AUC0-24 ratio on spVL was not significant (P = 0.808 and 0.768, respectively). This is the first population model describing TFV pharmacokinetics in the male genital tract. TFV SP concentrations were higher than BP concentrations. Despite TFV SP exposures being higher than BP exposures, an spVL was detectable for 12.2% of the men.

A Physiologically-Based Pharmacokinetic Model to Predict Human Fetal Exposure for a Drug Metabolized by Several CYP450 Pathways.

BACKGROUND: Pregnant women and their fetuses are exposed to numerous drugs; however, they are orphan populations with respect to the safety and efficacy of drugs. Therefore, the prediction of maternal and fetal drug exposure prior to administration would be highly useful. METHODS: A physiologically-based pharmacokinetic (PBPK) model for nevirapine, which is metabolized by the cytochrome P450 (CYP) 3A4, 2B6 and 2D6 pathways, was developed to predict maternal and fetal pharmacokinetics (PK). The model was developed in both non-pregnant and pregnant women, and all physiological and enzymatic changes that could impact nevirapine PK were taken into account. Transplacental parameters estimated from ex vivo human placenta perfusion experiments were included in this PBPK model. To validate the model, observed maternal and cord blood concentrations were compared with predicted concentrations, and the impact of fetal clearance on fetal PK was investigated. RESULTS: By implementing physiological changes, including CYP3A4, 2D6 and 2B6 inductions, we predicted a clearance increase of 21 % in late pregnancy. The PBPK model successfully predicted the disposition for both non-pregnant and pregnant populations. Parameters obtained from the ex vivo experiments allowed the prediction of nevirapine concentrations that matched observed cord blood concentrations. The fetal-to-maternal area under the curve ratio (0-24 h interval) was 0.77, and fetal metabolism had no significant effect on fetal PK. CONCLUSIONS: The PBPK approach is a useful tool for quantifying a priori the drug exposure of metabolized drugs during pregnancy, and can be applied to evaluate alternative dosing regimens to optimize drug therapy. This approach, including ex vivo human placental perfusion parameters, is a promising approach for predicting human fetal exposure.

Prediction of human fetal pharmacokinetics using ex vivo human placenta perfusion studies and physiologically based models.

AIMS: Pregnant women can be exposed to numerous drugs during the gestational period. For obvious ethical reasons, in vivo studies of fetal exposure to drugs are limited. Information about the transplacental transfer of drugs prior to their administration to pregnant women would be highly useful. In the present study, a novel approach was developed quantitatively predict or to predict the fetal exposure to drugs administered to the mother quantitatively. METHODS: Transplacental parameters estimated from ex vivo human placenta perfusion experiments were implemented in pregnancy-physiologically based pharmacokinetic (p-PBPK) models in order to predict fetal PK. Thereafter, fetal PK profiles for two antiretroviral drugs, tenofovir (TFV) and emtricitabine (FTC) were simulated. These predictions were then compared to observed cord blood concentrations, to validate these models. RESULTS: Parameters obtained from the ex vivo experiments enabled a good prediction of observed cord blood concentrations without additional a scaling factor. Moreover, a sensitivity analysis showed that fetal predictions were sensitive to changes in transplacental parameters values obtained ex vivo. CONCLUSION: The integration of ex vivo human placental perfusion parameters in a p-PBPK model should be a promising new approach for predicting human fetal exposure to xenobiotics.

Emtricitabine seminal plasma and blood plasma population pharmacokinetics in HIV-infected men in the EVARIST ANRS-EP 49 study.

We aimed to describe blood plasma (BP) and seminal plasma (SP) pharmacokinetics of emtricitabine (FTC) in HIV-1-infected men, assess its penetration in the male genital tract, and evaluate its impact on seminal plasma HIV load (spVL) detection. Men from the EVARIST ANRS EP49 study receiving combined antiretroviral therapy with FTC and with suppressed BP viral load were included in the study. A total of 236 and 209 FTC BP and SP concentrations, respectively, were available. A population pharmacokinetic model was developed with Monolix 4.1.4. The impact of FTC seminal exposure on spVL detection was explored by receiver operating characteristic (ROC) curves and mixed-effects logistic regressions. FTC BP pharmacokinetics was described by a two-compartment model. The addition of an effect compartment with different input and output constants best described FTC SP pharmacokinetics. No covariates were found to explain the variability in SP. FTC exposures (area under the concentration-time curve from 0 to 24 h [AUC0-24]) were higher in SP than in BP (median AUC0-24, 38.04 and 12.95 mg · liter(-1) · h, respectively). The median (range) SP-to-BP AUC0-24 ratio was 2.91 (0.84 to 10.08). Less than 1% of FTC AUC0-24 ratios were lower than 1. The impact of FTC SP AUC0-24 or FTC SP-to-BP AUC0-24 ratio on spVL detection was not significant (P = 0.943 or 0.893, respectively). This is the first population model describing FTC pharmacokinetics simultaneously in both BP and SP. FTC distributes well in the male genital tract with higher FTC concentrations in SP than in BP. FTC seminal plasma exposures were considered efficient in the majority of men.

Physiologically-based pharmacokinetic modeling of renally excreted antiretroviral drugs in pregnant women.

AIM: Physiological changes during pregnancy can affect drug disposition. Anticipating these changes will help to maximize drug efficacy and safety in pregnant women. Our objective was to determine if physiologically-based pharmacokinetics (PBPK) can accurately predict changes in the disposition of renally excreted antiretroviral drugs during pregnancy. METHODS: Whole body PBPK models were developed for three renally excreted antiretroviral drugs, tenofovir (TFV), emtricitabine (FTC) and lamivudine (3TC). To assess the impact of pregnancy on PK, time-varying pregnancy-related physiological parameters available within the p-PBPK Simcyp software package were used. Renal clearance during pregnancy followed glomerular filtration changes with or without alterations in secretion. PK profiles were simulated and compared with observed data, i.e. area under the curves (AUC), peak plasma concentrations (Cmax ) and oral clearances (CL/F). RESULTS: PBPK models successfully predicted TFV, FTC and 3TC disposition for non-pregnant and pregnant populations. Both renal secretion and filtration changed during pregnancy. Changes in renal clearance secretion were related to changes in renal plasma flow. The maximum clearance increases were approximately 30% (TFV 33%, FTC 31%, 3TC 29%). CONCLUSIONS: Pregnancy PBPK models are useful tools to quantify a priori the drug exposure changes during pregnancy for renally excreted drugs. These models can be applied to evaluate alternative dosing regimens to optimize drug therapy during pregnancy.

Prediction of drug clearance in children.

The pediatric population is often exposed to drugs without sufficient knowledge about pharmacokinetics. The prediction of accurate clearance values in children, especially in neonates and infants, will improve the rational in dosing decisions. Drug clearances from birth to adulthood were compiled after a systematic review of pharmacokinetic reports. The analysis was performed using NONMEM. Clearance predictions were then evaluated by external validation. Prediction errors were also compared with those obtained from weight-based allometric scaling and physiologically based clearance (PBCL) models. For the analysis, 17 and 15 drugs were used for model building and external validation, respectively. A model based on the adult drug clearance value and taking into account both weight and age was retained. Age-related maturation of clearance reached 90% of the adult value within 1.5 years of life. For children less than 2 years old, allometric scaling alone systematically overestimated clearances. Accounting for age improved the clearance prediction in the 6 months-2 years age group (prediction error < 25%). Predictions obtained from the PBCL approach were close to our results. This analysis established a single equation using the adult clearance value as well as individual age and weight to predict drug clearance in children older than 6 months.