Physiologically Based Pharmacokinetic Model To Predict Metoprolol Disposition in Healthy and Disease Populations
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ABSTRACT:
SUBMITTER: Zamir A
PROVIDER: S-EPMC10433471 | biostudies-literature | 2023 Aug
REPOSITORIES: biostudies-literature
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Project description:Pregnancy can increase the risk of latent tuberculosis infection (LTBI) progression to tuberculosis (TB) disease. Isoniazid (INH) is the preferred preventative treatment for LTBI in pregnancy. INH is mainly cleared by N-acetyltransferase 2 (NAT2) but the pharmacokinetics (PK) of INH in different NAT2 phenotypes during pregnancy is not well characterized. To address this knowledge gap, we used physiologically based pharmacokinetic (PBPK) modeling to evaluate NAT2 phenotype-specific effects of pregnancy on INH disposition. A whole-body PBPK model for INH was developed and verified for non-pregnant NAT2 fast (FA), intermediate (IA), and slow (SA) acetylators. Model predictive performance was assessed using a drug-specific model acceptance criterion for mean plasma area under the curve (AUC) and peak plasma concentration (Cmax ), and the absolute average fold error (AAFE) for individual plasma concentrations. The verified model was extended to simulate INH disposition during pregnancy in NAT2 SA, IA, and FA populations. A sensitivity analysis was conducted using the verified PBPK model and known changes in INH disposition during pregnancy to determine whether NAT2 activity changes during pregnancy or other INH clearance pathways are altered. This analysis suggested that NAT2 activity is unchanged while other INH clearance pathways increase by ~80% during pregnancy. The model was applied to explore the effect of pregnancy on INH disposition in two ethnic populations with different NAT2 phenotype distributions and with high TB burden. Our PBPK model can be used to predict INH disposition during pregnancy in diverse populations and expanded to other drugs cleared by NAT2 during pregnancy.
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Project description:Conducting pharmacokinetic (PK) studies in pregnant women is challenging. Therefore, we asked if a physiologically based pharmacokinetic (PBPK) model could be used to evaluate different dosing regimens for pregnant women. We refined and verified our previously published pregnancy PBPK model by incorporating cytochrome P450 CYP1A2 suppression (based on caffeine PK) and CYP2D6 induction (based on metoprolol PK) into the model. This model accounts for gestational age-dependent changes in maternal physiology and hepatic CYP3A activity. For verification, the disposition of CYP1A2-metabolized drug theophylline (THEO) and CYP2D6-metabolized drugs paroxetine (PAR), dextromethorphan (DEX), and clonidine (CLO) during pregnancy was predicted. Our PBPK model successfully predicted THEO disposition during the third trimester (T3). Predicted mean postpartum to third trimester (PP:T3) ratios of THEO area under the curve (AUC), maximum plasma concentration, and minimum plasma concentration were 0.76, 0.95, and 0.66 versus observed values 0.75, 0.89, and 0.72, respectively. The predicted mean PAR steady-state plasma concentration (Css) ratio (PP:T3) was 7.1 versus the observed value 3.7. Predicted mean DEX urinary ratio (UR) (PP:T3) was 2.9 versus the observed value 1.9. Predicted mean CLO AUC ratio (PP:T3) was 2.2 versus the observed value 1.7. Sensitivity analysis suggested that a 100% induction of CYP2D6 during T3 was required to recover the observed PP:T3 ratios of PAR Css, DEX UR, and CLO AUC. Based on these data, it is prudent to conclude that the magnitude of hepatic CYP2D6 induction during T3 ranges from 100 to 200%. Our PBPK model can predict the disposition of CYP1A2, 2D6, and 3A drugs during pregnancy.
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Project description:Tuberculosis (TB) is a leading cause of mortality attributed to an infectious agent. TB primarily targets the lungs, but in about 16% cases can affect other organs as well, giving rise to extrapulmonary TB (EPTB). However, an optimal regimen for EPTB treatment is not defined. Although the recommended treatment for most forms of EPTB is the same as pulmonary TB, the pharmacokinetics of EPTB therapy are not as well studied. To address this gap, we formulate a whole-body physiologically-based pharmacokinetic (PBPK) model for EPTB that for the first time includes the ability to simulate drug concentrations in the pleura and lymph node, the most commonly affected sites of EPTB. Using this model, we estimate the time-dependent concentrations, at potential EPTB infection sites, of the following four first-line anti-TB drugs: rifampicin, ethambutol, isoniazid, and pyrazinamide. We use reported plasma concentration kinetics data to estimate model parameters for each drug and validate our model using reported concentration data not used for model formulation or parameter estimation. Model predictions match the validation data, and reported pharmacokinetic parameters (maximum plasma concentration, time to reach maximum concentration) for the drugs. The model also predicts ethambutol, isoniazid, and pyrazinamide concentrations in the pleura that match reported experimental values from an independent study. For each drug, the predicted drug concentrations at EPTB sites are compared with their critical concentration. Simulations suggest that although rifampicin and isoniazid concentrations are greater than critical concentration values at most EPTB sites, the concentrations of ethambutol and pyrazinamide are lower than their critical concentrations at most EPTB sites.
| S-EPMC10508491 | biostudies-literature
Project description:Findings of a recent clinical study showed indomethacin has lower plasma levels and higher steady-state apparent clearance in pregnant subjects when compared to those in non-pregnant subjects reported in separate studies. Thus, in the current work we developed a pregnancy physiological based pharmacokinetic/pharmacodynamic (PBPK/PD) model for indomethacin to explain the differences in indomethacin pharmacokinetics between pregnancy and non-pregnancy. A whole-body PBPK model with key pregnancy-related physiological changes was developed to characterize indomethacin PK in pregnant women and compare these parameters to those in non-pregnant subjects. Data related to maternal physiological and biological changes were obtained from literature and incorporated into the structural PBPK model that describes non-pregnant PK data. Changes in indomethacin area under the curve (AUC), maximum concentration (Cmax) and average steady-state concentration (Cave) in pregnant women were predicted. Model-simulated PK profiles were in agreement with observed data. The predicted mean ratio (non-pregnant:second trimester (T2)) of indomethacin Cave was 1.6 compared to the observed value of 1.59. In addition, the predicted steady-state apparent clearance (CL/Fss) ratio was almost similar to the observed value (0.46 vs. 0.42). Sensitivity analysis suggested changes in CYP2C9 activity, and to a lesser extent UGT2B7, as the primary factor contributing to differences in indomethacin disposition between pregnancy and non-pregnancy. The developed PBPK model which integrates prior physiological knowledge, in vitro and in vivo data, allowed the successful prediction of indomethacin disposition during T2. Our PBPK/PD model suggested a higher indomethacin dosing requirement during pregnancy.
| S-EPMC4592215 | biostudies-literature
Project description:A physiologically based pharmacokinetic (PBPK) model of selegiline (SEL), and its metabolites, was developed in silico to evaluate the disposition differences between healthy and special populations. SEL is metabolized to methamphetamine (MAP) and desmethyl selegiline (DMS) by several CYP enzymes. CYP2D6 metabolizes the conversion of MAP to amphetamine (AMP), while CYP2B6 and CYP3A4 predominantly mediate the conversion of DMS to AMP. The overall prediction error in simulated PK, using the developed PBPK model, was within 0.5-1.5-fold after intravenous and transdermal dosing in healthy and elderly populations. Simulation results generated in the special populations demonstrated that a decrease in cardiac output is a potential covariate that affects the SEL exposure in renally impaired (RI) and hepatic impaired (HI) subjects. A decrease in CYP2D6 levels increased the systemic exposure of MAP. DMS exposure increased due to a reduction in the abundance of CYP2B6 and CYP3A4 in RI and HI subjects. In addition, an increase in the exposure of the primary metabolites decreased the exposure of AMP. No significant difference between the adult and adolescent populations, in terms of PK, were observed. The current PBPK model predictions indicate that subjects with HI or RI may require closer clinical monitoring to identify any untoward effects associated with the administration of transdermal SEL patch.
| S-EPMC7600566 | biostudies-literature
Project description:Over the last several decades, angiotensin-converting enzyme inhibitors (ACEIs) have been a staple in the treatment of hypertension and renovascular disorders in children. One of the ACEIs, captopril, is projected to have all the benefits of traditional vasodilators. However, conducting clinical trials for determining the pharmacokinetics (PK) of a drug is challenging, particularly in pediatrics. As a result, modeling and simulation methods have been developed to identify the safe and effective dosages of drugs. The physiologically based pharmacokinetic (PBPK) modeling is a well-established method that permits extrapolation from adult to juvenile populations. By using SIMCYP simulator, as a modeling platform, a previously developed PBPK drug-disease model of captopril was scaled to renally impaired pediatrics population for predicting captopril PK. The visual predictive checks, predicted/observed ratios (ratiopred/obs), and the average fold error of PK parameters were used for model evaluation. The model predictions were comparable with the reported PK data of captopril in mild and severe chronic kidney disease (CKD) patients, as the mean ratiopred/obs Cmax and AUC0-t were 1.44 (95% CI 1.07 - 1.80) and 1.26 (95% CI 0.93 - 1.59), respectively. The successfully developed captopril-CKD pediatric model can be used in suggesting drug dosing in children diagnosed with different stages of CKD.
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Project description:Labetalol is a drug that exhibits both alpha and beta-adrenergic receptor-blocking properties. The American Heart Association/American Stroke Association (AHA/ASA) has recommended labetalol as an initial treatment option for the management of severe hypertension. The physiologically based pharmacokinetic (PBPK) model is an in silico approach to determining the pharmacokinetics (PK) of a drug by incorporating blood flow and tissue composition of the organs. This study was conducted to evaluate the primary reasons for the difference in PK after intravenous (IV) and oral administration in healthy and diseased (renal and hepatic) populations. A comprehensive literature search was done using two databases, PubMed and Google Scholar. Various PK parameters were screened for the development of the PBPK model utilizing a population-based PK-Sim simulator. Simulations were performed after creating building blocks firstly in healthy individuals and then in diseased patients after IV and oral administration. The disposition of labetalol after IV and oral administration occurring in patients with the hepatic and renal disease was predicted. The model was evaluated by calculating the Robs/pred ratio and average fold error (AFE), which was in the two-fold error range. Moreover, Box-whisker plots were made to compare the overall concentration of the drug in the body at various stages of disease severity. The presented model provides useful quantitative estimates of drug dosing in patients fighting against severe chronic diseases.
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Project description:Minimal physiologically based pharmacokinetic (mPBPK) models provide a simple and sensible approach that incorporates physiological elements into pharmacokinetic (PK) analysis when only plasma data are available. With this modeling concept, a second-generation mPBPK model was further developed with specific accommodations for the unique PK properties of monoclonal antibodies (mAb). This study applied this model to extensively survey mAb PK in man in order to seek general perspectives on mAb distributional and elimination features. Profiles for 72 antibodies were successfully analyzed with this model. The model results provide assessment regarding: (1) predominant clearance site, in plasma or interstitial fluid (ISF); (2) mAb ISF concentrations in two groups of lumped tissues with continuous (V(tight)) or fenestrated (V(leaky)) vascular endothelium; (3) Transcapillary escape rate (TER), an indicator of systemic vascular permeability. For 93% of surveyed mAbs, the model assuming clearance from plasma (CL) produced better or at least equivalent model performance than the model with clearance from ISF and yielded most consistent values of vascular reflection coefficients (σ1 and σ2) among all antibodies. The average mAb ISF concentration in V(tight) and V(leaky) at equilibrium was predicted to be about 6.8 and 37.9% of that in plasma. A positive correlation was detected between plasma clearance and TER among most mAbs, which could be interpreted as both parameters having common determinants related to ISF tissue distribution in this model context. The mAbs with relative higher plasma clearance (>0.035 L/h/70 kg) did not reveal such positive correlation between clearance and TER, implying that the factors contributing to high clearance may not necessarily increase tissue distribution and penetration. In conclusion, this mPBPK model offers a more mechanistic approach for analyzing plasma mAb PK than compartment models and generates parameters providing useful intrinsic distributional and elimination insights for a large number of mAbs that were examined in man.
| S-EPMC4226811 | biostudies-literature
Project description:Target-mediated drug disposition (TMDD) usually accounts for nonlinear pharmacokinetics (PK) of drugs whose distribution and/or clearance are affected by their targets owing to high affinity and limited capacity. TMDD is frequently reported for monoclonal antibodies (mAb) for such reason. Minimal physiologically-based pharmacokinetic models (mPBPK), which accommodate the unique PK behaviors of mAb, provide a general approach for analyzing mAbs PK and predicting mAb interstitial concentrations in two groups of tissues. This study assessed the feasibility of incorporating TMDD into mPBPK models to consider target-binding in either plasma (cTMDD) or interstitial fluid (ISF) (pTMDD). The dose-related signature profiles of the pTMDD model reveal a parallel early decay phase, in contrast with the cTMDD model that exhibits a faster initial decline for low doses. The parallel early phase in the pTMDD model is associated with the slow perivascular extravasation of mAb, which restricts the initial decline regardless of interstitial target-mediated elimination. The cTMDD and pTMDD models both preserve the long terminal phase that is typically perceived in conventional two-compartment (2CM) and TMDD models. Having TMDD in ISF impacts the typical relationships between plasma concentrations and receptor occupancy, and between saturation of apparent nonlinear clearance and saturation of receptors. The vascular reflection coefficient (σ v ) was found to affect receptor occupancy in ISF. In the cTMDD model, saturation of nonlinear clearance is equivalent to saturation of receptors. However, in the pTMDD model, they are no longer equal and all parameters pertaining to receptors or receptor binding (R total , K D , K ss , k int ) shifts such relationships. Different TMDD models were utilized in analyzing PK for seven mAbs from digitized literature data. When the target is in plasma, the cTMDD model performed similarly to the 2CM and TMDD models, but with one less system parameter. When the target exists in ISF, the pTMDD functioned well in analyzing only plasma data to reflect interstitial target binding properties. Assigning TMDD consistent with target-expressing tissues is important to obtain reliable characterizations of receptors and receptor binding. The mPBPK model exhibits excellent feasibility in integrating TMDD not only in plasma but also in ISF.
| S-EPMC4167346 | biostudies-literature
Project description:PurposeMonoclonal antibodies (mAbs) are commonly administered by subcutaneous (SC) route. However, bioavailability is often reduced after SC administration. In addition, the sequential transfer of mAbs through the SC tissue and lymphatic system is not completely understood. Therefore, major objectives of this study were a) To understand absorption of mAbs via the lymphatic system after SC administration using physiologically based pharmacokinetic (PBPK) modeling, and b) to demonstrate application of the model for prediction of SC pharmacokinetics (PK) of mAbs.MethodsA minimal PBPK model was constructed using various physiological parameters related to the SC injection site and lymphatic system. The remainder of the body organs were represented using a 2-compartment model (central and peripheral compartments), with parameters derived from available intravenous (IV) PK data. The IV and SC clinical PK data of a total of 10 mAbs were obtained from literature. The SC PK data were used to estimate the lymphatic trunk-lymph node (LN) clearance.ResultsThe mean estimated lymphatic trunk-LN clearance obtained from 37 SC PK profiles of mAbs was 0.00213 L/h (0.001332 to 0.002928, 95% confidence intervals). The estimated lymphatic trunk-LN clearance was greater for the mAbs with higher isoelectric point (pI). In addition, the estimated clearance increased with decrease in the bioavailability.ConclusionThe minimal PBPK model identified SC injection site lymph flow, afferent and efferent lymph flows, and volumes associated with the SC injection site, lymphatic capillaries and lymphatic trunk-LN as important physiological parameters governing the absorption of mAbs after SC administration. The model may be used to predict PK of mAbs using the relationship of lymphatic trunk-LN clearance and the pI. In addition, the model can be used as a bottom platform to incorporate SC and lymphatic in vitro clearance data for mAb PK prediction in the future.
| S-EPMC6613546 | biostudies-literature