Auswahl der wissenschaftlichen Literatur zum Thema „P-PBPK model“

Model informed drug development is a valuable tool for drug development and clinical application due to its ability to integrate variability and uncertainty of data. This study aimed to determine an optimal dosage of ceftiofur against P. multocida by ex vivo pharmacokinetic/pharmacodynamic (PK/PD) model and validate the dosage regimens by Physiological based Pharmacokinetic-Pharmacodynamic (PBPK/PD) model. The pharmacokinetic profiles of ceftiofur both in plasma and bronchoalveolar lavage fluid (BALF) are determined. PD performance of ceftiofur against P. multocida was investigated. By establishing PK/PD model, PK/PD parameters and doses were determined. PBPK model and PBPK/PD model were developed to validate the dosage efficacy. The PK/PD parameters, AUC0–24 h/MIC, for bacteriostatic action, bactericidal action and elimination were determined as 44.02, 89.40, and 119.90 h and the corresponding dosages were determined as 0.22, 0.46, and 0.64 mg/kg, respectively. AUC24 h/MIC and AUC 72 h/MIC are simulated by PBPK model, compared with the PK/PD parameters, the therapeutic effect can reach probability of target attainment (PTA) of 90%. The time-courses of bacterial growth were predicted by the PBPK/PD model, which indicated the dosage of 0.46 mg/kg body weight could inhibit the bacterial growth and perform good bactericidal effect.

Fexuprazan is a new drug candidate in the potassium-competitive acid blocker (P-CAB) family. As proton pump inhibitors (PPIs), P-CABs inhibit gastric acid secretion and can be used to treat gastric acid-related disorders such as gastroesophageal reflux disease (GERD). Physiologically based pharmacokinetic (PBPK) models predict drug interactions as pharmacokinetic profiles in biological matrices can be mechanistically simulated. Here, we propose an optimized and validated PBPK model for fexuprazan by integrating in vitro, in vivo, and in silico data. The extent of fexuprazan tissue distribution in humans was predicted using tissue-to-plasma partition coefficients in rats and the allometric relationships of fexuprazan distribution volumes (VSS) among preclinical species. Urinary fexuprazan excretion was minimal (0.29–2.02%), and this drug was eliminated primarily by the liver and metabolite formation. The fraction absorbed (Fa) of 0.761, estimated from the PBPK modeling, was consistent with the physicochemical properties of fexuprazan, including its in vitro solubility and permeability. The predicted oral bioavailability of fexuprazan (38.4–38.6%) was within the range of the preclinical datasets. The Cmax, AUClast, and time-concentration profiles predicted by the PBPK model established by the learning set were accurately predicted for the validation sets.

BackgroundPhysiologically-based pharmacokinetic (PBPK) models are considered a promising approach to better characterize and anticipate the effect of physiological changes on pharmacokinetics in pregnant women. Consequently, multiple pregnancy PBPK models have been developed and verified over the past years. Using acetaminophen (paracetamol) as example, PBPK modeling can provide specific insights into the expected pharmacokinetic changes throughout pregnancy.MethodsTo obtain an overview of pregnancy PBPK models, the scientific literature was systematically screened for publications with a focus on pharmaceutical applications using relevant keywords. Additionally, a pregnancy PBPK model for acetaminophen was developed with the Open Systems Pharmacology software suite (www.open-systems-pharmacology.org) following an established workflow. After model verification around gestational week 30, the model was scaled to earlier stages of pregnancy and molar dose fractions converted to acetaminophen metabolites were estimated for each trimester.ResultsOver the past years, more than 60 different pregnancy PBPK models for more than have 40 drugs been published. More than 70% of these models were developed for the third trimester, while few models have been applied to the first trimester. The developed PBPK model for acetaminophen indicated that the median dose fraction of acetaminophen converted to the reactive metabolite N-acetyl-p-benzoquinonimine (NAPQI) was 11%, 9.0% and 8.2% in the first, second and third trimester, respectively, while for non-pregnant women a value of 7.7% was simulated.ConclusionWhile the overall availability and quality of pregnancy PBPK models is varying considerably, the efforts to establish such models are promising in that they reflect an increased awareness of the necessity to better characterize pharmacokinetics during pregnancy. This is illustrated by the developed PBPK model for acetaminophen where information on NAPQI-formation in vivo is hitherto lacking. Although PBPK models are not a substitute for clinical trials, they constitute an important tool for clinicians in case of missing or incomplete information.Disclosure(s)Nothing to disclose

Women commonly take medication during lactation. Currently, there is little information about the exposure-related safety of maternal medicines for breastfed infants. The aim was to explore the performance of a generic physiologically-based pharmacokinetic (PBPK) model to predict concentrations in human milk for ten physiochemically diverse medicines. First, PBPK models were developed for “non-lactating” adult individuals in PK-Sim/MoBi v9.1 (Open Systems Pharmacology). The PBPK models predicted the area-under-the-curve (AUC) and maximum concentrations (Cmax) in plasma within a two-fold error. Next, the PBPK models were extended to include lactation physiology. Plasma and human milk concentrations were simulated for a three-months postpartum population, and the corresponding AUC-based milk-to-plasma (M/P) ratios and relative infant doses were calculated. The lactation PBPK models resulted in reasonable predictions for eight medicines, while an overprediction of human milk concentrations and M/P ratios (>2-fold) was observed for two medicines. From a safety perspective, none of the models resulted in underpredictions of observed human milk concentrations. The present effort resulted in a generic workflow to predict medicine concentrations in human milk. This generic PBPK model represents an important step towards an evidence-based safety assessment of maternal medication during lactation, applicable in an early drug development stage.

Buprenorphine plays a crucial role in the therapeutic management of pain in adults, adolescents and pediatric subpopulations. However, only few pharmacokinetic studies of buprenorphine in children, particularly neonates, are available as conducting clinical trials in this population is especially challenging. Physiologically-based pharmacokinetic (PBPK) modeling allows the prediction of drug exposure in pediatrics based on age-related physiological differences. The aim of this study was to predict the pharmacokinetics of buprenorphine in pediatrics with PBPK modeling. Moreover, the drug-drug interaction (DDI) potential of buprenorphine with CYP3A4 and P-glycoprotein perpetrator drugs should be elucidated. A PBPK model of buprenorphine and norbuprenorphine in adults has been developed and scaled to children and preterm neonates, accounting for age-related changes. One-hundred-percent of the predicted AUClast values in adults (geometric mean fold error (GMFE): 1.22), 90% of individual AUClast predictions in children (GMFE: 1.54) and 75% in preterm neonates (GMFE: 1.57) met the 2-fold acceptance criterion. Moreover, the adult model was used to simulate DDI scenarios with clarithromycin, itraconazole and rifampicin. We demonstrate the applicability of scaling adult PBPK models to pediatrics for the prediction of individual plasma profiles. The novel PBPK models could be helpful to further investigate buprenorphine pharmacokinetics in various populations, particularly pediatric subgroups.

Abstract Purpose Limited information is available regarding the drug–drug interaction (DDI) potential of molecular targeted agents and rituximab plus cyclophosphamide, doxorubicin (hydroxydaunorubicin), vincristine (Oncovin), and prednisone (R-CHOP) therapy. The addition of the Bruton tyrosine kinase (BTK) inhibitor ibrutinib to R-CHOP therapy results in increased toxicity versus R-CHOP alone, including higher incidence of peripheral neuropathy. Vincristine is a substrate of P-glycoprotein (P-gp, ABCB1); drugs that inhibit P-gp could potentially cause increased toxicity when co-administered with vincristine through DDI. While the combination of the BTK inhibitor acalabrutinib and R-CHOP is being explored clinically, the DDI potential between these therapies is unknown. Methods A human mechanistic physiology-based pharmacokinetic (PBPK) model of vincristine following intravenous dosing was developed to predict potential DDI interactions with combination therapy. In vitro absorption, distribution, metabolism, and excretion and in vivo clinical PK parameters informed PBPK model development, which was verified by comparing simulated vincristine concentrations with observed clinical data. Results While simulations suggested no DDI between vincristine and ibrutinib or acalabrutinib in plasma, simulated vincristine exposure in muscle tissue was increased in the presence of ibrutinib but not acalabrutinib. Extrapolation of the vincristine mechanistic PBPK model to other P-gp substrates further suggested DDI risk when ibrutinib (area under the concentration–time curve [AUC] ratio: 1.8), but not acalabrutinib (AUC ratio: 0.92), was given orally with venetoclax or digoxin. Conclusion Overall, these data suggest low DDI risk between acalabrutinib and P-gp substrates with negligible increase in the potential risk of vincristine-induced peripheral neuropathy when acalabrutinib is added to R-CHOP therapy.

Uptake transporter organic anion transporting polypeptides (OATPs), efflux transporters (P-gp, BCRP and MRP2) and cytochrome P450 enzymes (CYP450s) are widely expressed in the liver, intestine or kidney. They coordinately work to control drug disposition, termed as “interplay of transporters and enzymes”. Cyclosporine A (CsA) is an inhibitor of OATPs, P-gp, MRP2, BCRP and CYP3As. Drug–drug interaction (DDI) of CsA with victim drugs occurs via disordering interplay of transporters and enzymes. We aimed to establish a whole-body physiologically-based pharmacokinetic (PBPK) model which predicts disposition of CsA and nine victim drugs including atorvastatin, cerivastatin, pravastatin, rosuvastatin, fluvastatin, simvastatin, lovastatin, repaglinide and bosentan, as well as drug–drug interactions (DDIs) of CsA with nine victim drugs to investigate the integrated effect of enzymes and transporters in liver, intestinal and kidney on drug disposition. Predictions were compared with observations. Most of the predictions were within 0.5–2.0 folds of observations. Atorvastatin was represented to investigate individual contributions of transporters and CYP3As to atorvastatin disposition and their integrated effect. The contributions to atorvastatin disposition were hepatic OATPs >> hepatic CYP3A > intestinal CYP3As ≈ efflux transporters (P-gp/BCRP/MRP2). The results got the conclusion that the developed PBPK model characterizing the interplay of enzymes and transporters was successfully applied to predict the pharmacokinetics of 10 OATP substrates and DDIs of CsA with 9 victim drugs.

Background: Clozapine is a key antipsychotic drug for treatment-resistant schizophrenia but exhibits highly variable pharmacokinetics and a propensity for serious adverse effects. Currently, these challenges are addressed using therapeutic drug monitoring (TDM). This study primarily sought to (i) verify the importance of covariates identified in a prior clozapine population pharmacokinetic (popPK) model in the absence of environmental covariates using physiologically based pharmacokinetic (PBPK) modelling, and then to (ii) evaluate the performance of the popPK model as an adjunct or alternative to TDM-guided dosing in an active TDM population. Methods: A popPK model incorporating age, metabolic activity, sex, smoking status and weight was applied to predict clozapine trough concentrations (Cmin) in a PBPK-simulated population and an active TDM population comprising 142 patients dosed to steady state at Flinders Medical Centre in Adelaide, South Australia. Post hoc analyses were performed to deconvolute the impact of physiological and environmental covariates in the TDM population. Results: Analysis of PBPK simulations confirmed age, cytochrome P450 1A2 activity, sex and weight as physiological covariates associated with variability in clozapine Cmin (R2 = 0.7698; p = 0.0002). Prediction of clozapine Cmin using a popPK model based on these covariates accounted for <5% of inter-individual variability in the TDM population. Post hoc analyses confirmed that environmental covariates accounted for a greater proportion of the variability in clozapine Cmin in the TDM population. Conclusions: Variability in clozapine exposure was primarily driven by environmental covariates in an active TDM population. Pharmacokinetic modelling can be used as an adjunct to TDM to deconvolute sources of variability in clozapine exposure.

Fexuprazan is a potassium-competitive acid blocker (P-CAB). The compounds in this newly developed drug family suppress intragastric acidity. As there are already other acid-suppressing drugs on the market, such as H2 antagonists and proton pump inhibitors (PPIs), it would be informative to compare the biological effects of fexuprazan against another approved drug with the same indication. The drug concentration predicted by the pharmacokinetic (PK) model could serve as an input function for a pharmacodynamic (PD) model. The apparent pharmacokinetics of fexuprazan could be described by a simpler model. However, a physiologically based pharmacokinetic (PBPK) model was developed in a previous study. A one-compartment model was also proposed in the present study. Both the newly suggested model and the previously validated PBPK model were used as input functions of the PD models. Our simulation revealed that the effects of fexuprazan could be effectively simulated by the proposed PK–PD models. A PK–PD model was also proposed for the oral administration of the PPI reference drug esomeprazole. A model-based analysis was then performed for intragastric pH using several dosing methods. The expected pH could be predicted for both drugs under several dosing regimens using the proposed PK–PD models.

Exposure to environmental chemicals with hormonal effects, such as organochlorine compounds (OCs), during developmental periods of breast cells may have an impact on the incidence of breast cancer later in life. However, the assessment of exposure to these chemicals that occurred in early life at the time of breast cancer development in adult women is a difficult challenge in epidemiological studies. Plasma levels of the OCs p,p’-dichlorodiphenyl dichloroethene (DDE) and polychlorinated biphenyl congener 153 (PCB153) were measured in 695 cases and 1055 controls of a population-based case-control study conducted in France (CECILE study). Based on these values, we used a physiologically-based pharmacokinetic (PBPK) model to estimate PCB153 levels at age 11–20 years when the women were adolescents. Overall, there was no clear association between breast cancer risk and measured levels of DDE and PCB153 at the time of diagnosis, but there was a trend of decreasing odds ratios of breast cancer with increasing DDE and PCB153 levels in women aged 50 years and over. The PBPK model revealed that PCB153 concentrations estimated during adolescence were highest in the youngest women born after 1960 who reached adolescence at a time when environmental contamination was maximum, and very low in the oldest women who attained adolescence before the contamination peak. Negative associations between breast cancer and PCB153 estimates during adolescence were also found. The negative associations between DDE and PCB153 levels measured at the time of diagnosis or estimated during adolescence in our study were unexplained. Further investigations are needed to clarify whether this finding is real or related to study artifacts. However, this study suggests that using PBPK models in epidemiological studies to back-estimate OC exposures during early life stages may be useful to address critical questions on cancer development.

Le plomb (Pb) est une neurotoxine très puissante, notamment pour les enfants. Une vaste littérature épidémiologique documente les effets de l'exposition au Pb chez les jeunes enfants. Le Pb est capable de traverser la barrière placentaire pour induire une exposition précoce du fœtus. Cette exposition prénatale est associée à une altération des fonctions cognitives des enfants qui se traduit par des problèmes d'apprentissage, une diminution du quotient intellectuel (QI) et des problèmes de comportement. Pour des raisons d'éthique évidentes, il n'est pas possible de mesurer la concentration de Pb chez le fœtus pendant la grossesse. Ainsi, une seule mesure obtenue dans le sang du cordon ombilical à l'accouchement est disponible pour évaluer l'exposition prénatale. Les modèles pharmacocinétiques basés sur la physiologie de la grossesse (p-PBPK) peuvent être utilisés pour simuler les expositions prénatales tout au long de la grossesse. L'objectif de cette thèse est de fournir un outil capable de simuler les expositions internes du fœtus à partir de données parcellaires, comme par exemple, celles obtenues lors de campagnes de biosurveillance.Une recherche bibliographique a été menée sur l'impact de la grossesse sur les processus ADME du Pb chez la mère et le fœtus. Cette recherche a mis en évidence une augmentation du renouvellement (i.e. cycle de formation et de résorption) de l'os maternel pendant la grossesse. Les marqueurs de la formation et de la résorption de l'os, dosés dans les urines, augmentent linéairement à partir du 2nd trimestre jusqu'à la fin de grossesse. Par ailleurs, les données sur la cinétique du Pb pendant la grossesse chez la mère révèlent une courbe en forme de U : une première phase de diminution lors des 4 premiers mois et suivie d'une seconde phase d'augmentation de la plombémie maternelle. Les valeurs des paramètres modélisant le renouvellement de l'os et le transfert placentaire du Pb ont été calibré à partir des données de la littérature. La performance prédictive de notre modèle a été évaluée en utilisant les rapports de concentrations appariées de Pb dans le sang du cordon ombilical et maternel à l'accouchement, démontrant ainsi une performance satisfaisante entre les prédictions du modèle et les données observées. Une analyse de sensibilité globale du modèle a mis en évidence une forte influence sur les expositions fœtales de la liaison du Pb aux érythrocytes, l'accumulation du Pb dans les os et du coefficient de partage dans le cerveau.Les concentrations de Pb mesurées dans le cordon ombilical à l'accouchement, provenant de l'étude longitudinale française depuis l'enfance (Elfe), ont été utilisées dans le modèle p-PBPK pour simuler les concentrations de Pb dans le cerveau des fœtus. Les simulations effectuées sur la cohorte Elfe révèlent des variations des concentrations prédites de Pb dans le cerveau des fœtus au cours de la grossesse. À la fin de la grossesse, presque la moitié des fœtus de la cohorte Elfe présentaient des concentrations prédites dans le cerveau susceptibles d'induire in vitro et ex vivo des effets sur le neurodéveloppement.Pour conclure, ce travail de thèse met en lumière le potentiel des modèle p-PBPK pour l'évaluation des expositions prénatales. Nous avons démontré la capacité de notre modèle à simuler des indicateurs d'exposition chez le fœtus en tenant compte des mécanismes physiologiques essentiels à la toxicocinétique du Pb pendant la grossesse. Ce modèle peut à l'avenir être couplé à un modèle d'effet tel qu'un chemin d'effet néfaste (AOP) pour aider à prédire les effets du Pb sur le neurodéveloppement des enfants
Lead (Pb) is a highly potent neurotoxin, especially for children. A vast epidemiological literature documents the effects of Pb exposure in young children. Pb can cross the placental barrier to induce early fetal exposure. This prenatal exposure is associated with impaired cognitive function in children, resulting in learning problems, decreased intelligence quotient (IQ) and behavioral problems. For obvious ethical reasons, it is not possible to measure Pb concentrations in the fetus during pregnancy. Consequently, a single measurement obtained from umbilical cord blood at delivery is available to assess prenatal exposure. Thankfully, Pregnancy physiologically based pharmacokinetic (p-PBPK) models can be used to simulate prenatal exposures throughout pregnancy. The aim of this thesis is to provide a tool capable of simulating internal fetal exposures, from incomplete data, such as those obtained during biomonitoring campaigns.A literature search was carried out on the impact of pregnancy on the ADME processes of Pb in both the mother and fetus. This research highlighted an increase in maternal bone turnover (i.e. cycle of formation and resorption) during pregnancy. Indeed, urinary markers of bone formation and resorption linearly increase from the 2nd trimester until the end of pregnancy. Furthermore, data on the kinetic of Pb during pregnancy reveal a distinctive U-shaped trend, an initial phase of decrease during the first 4 months followed by a second phase of increase in maternal blood lead levels. The parameter values modeling bone turnover and placental transfer of Pb were calibrated using literature data. The predictive performance of our p-PBPK model was assessed using paired concentrations of Pb in umbilical cord and maternal blood at delivery, demonstrating satisfactory performance between the model predictions and the observed data. A global sensitivity analysis of the model highlighted à strong influence on fetal exposures from the Pb binding to erythrocytes, Pb accumulation in bones and the partition coefficient in the brain.Pb concentrations measured in the umbilical cord at delivery, from the French Longitudinal Study since Infancy (Elfe), were used in the p-PBPK model to simulate Pb concentrations in the fetal brain. Simulations carried out on the Elfe cohort reveal variations in predicted Pb concentrations in fetal brain over the course of pregnancy. By the end of pregnancy, almost half the fetuses in the Elfe cohort had predicted brain concentrations likely to induce in vitro and ex vivo effects on neurodevelopmental.In conclusion, this thesis highlights the potential of p-PBPK models for assessing prenatal exposure. We have demonstrated the ability of our model to simulate fetal exposure indicators, taking into account the physiological mechanisms essential to Pb toxicokinetics during pregnancy. In the future, this model can be coupled with an effect model such as an Adverse Outcome Pathway (AOP) to help predict the effects of Pb on the neurodevelopment of children

Nuclear receptors play significant roles in the regulation of transporters and enzymes to balance the level of endogenous molecules and to protect the body from foreign molecules. The vitamin D receptor (VDR) and its natural ligand, 1alpha,25-dihydroxyvitamin D3 [1,25(OH)2D3], was shown to upregulate rat ileal apical sodium dependent bile acid transporter (Asbt) to increase the reclamation of bile acids, ligands of the farnesoid X receptor (FXR). FXR is considered to be an important, negative regulator of the cholesterol metabolizing enzyme, Cyp7a1, which metabolizes cholesterol to bile acids in the liver. In rats, decreased Cyp7a1 and increased P-glycoprotein/multidrug resistance protein 1 (P-gp/Mdr1) expressions pursuant to 1,25(OH)2D3 treatment was viewed as FXR effects in which hepatic VDR protein is poorly expressed. In contrast, changes in rat intestinal and renal transporters such as multidrug resistance associated proteins (Mrp2, Mrp3, and Mrp4), Asbt, and P-gp after administration of 1,25(OH)2D3 were attributed directly as VDR effects due to higher VDR levels expressed in these tissues. Higher VDR expressions were found among mouse hepatocytes compared to those in rats. Hence, fxr(-/-) and fxr(+/+) mouse models were used to discriminate between VDR vs. FXR effects in murine livers. Hepatic Cyp7a1 in mice was found to be upregulated with 1,25(OH)2D3 treatment, via the derepression of the short heterodimer partner (SHP). Putative VDREs, identified in mouse and human SHP promoters, were responsible for the inhibitory effect on SHP. The increase in hepatic Cyp7a1 expression and decreased plasma and liver cholesterol were observed in mice prefed with a Western diet. A strong correlation was found between tissue Cyp7a1 and P-gp changes and 1,25(OH)2D3 plasma and tissue concentrations, confirming that VDR plays an important role in the disposition of xenobiotics and cholesterol metabolism. Moreover, renal and brain Mdr1a/P-gp were found to be directly upregulated by the VDR in mice, and concomitantly, increased renal and brain secretion of digoxin, a P-gp substrate, in vivo. The important observations: the cholesterol lowering and increased brain P-gp efflux activity properties suggest that VDR is a therapeutic target for treatment of hypercholesterolemia and Alzheimer’s diseases, since beta amyloid, precursors of plague, are P-gp substrates.