scholarly journals PBPK Modeling Approach to Predict the Behavior of Drugs Cleared by Kidney in Pregnant Subjects and Fetus

2021 ◽  
Vol 23 (4) ◽  
Author(s):  
Ke Xu Szeto ◽  
Maxime Le Merdy ◽  
Benjamin Dupont ◽  
Michael B. Bolger ◽  
Viera Lukacova

AbstractThe purpose of this study was to develop a physiologically based pharmacokinetic (PBPK) model predicting the pharmacokinetics (PK) of different compounds in pregnant subjects. This model considers the differences in tissue sizes, blood flow rates, enzyme expression levels, glomerular filtration rates, plasma protein binding, and other factors affected during pregnancy in both the maternal and fetal models. The PBPKPlus™ module in GastroPlus® was used to model the PK of cefuroxime and cefazolin. For both compounds, the model was first validated against PK data in healthy non-pregnant volunteers and then applied to predict pregnant groups PK. The model accurately described the PK in both non-pregnant and pregnant groups and explained well differences in the plasma concentration due to pregnancy. The fetal plasma and amniotic fluid concentrations were also predicted reasonably well at different stages of pregnancy. This work describes the use of a PBPK approach for drug development and demonstrates the ability to predict differences in PK in pregnant subjects and fetal exposure for compounds excreted renally. The prediction for pregnant groups is also improved when the model is calibrated with postpartum or non-pregnant female group if such data are available.

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 813
Author(s):  
Yoo-Seong Jeong ◽  
Min-Soo Kim ◽  
Nora Lee ◽  
Areum Lee ◽  
Yoon-Jee Chae ◽  
...  

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.


2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S669-S669
Author(s):  
Dung N Nguyen ◽  
Xiusheng Miao ◽  
Mindy Magee ◽  
Guoying Tai ◽  
Peter D Gorycki ◽  
...  

Abstract Background Fostemsavir (FTR) is an oral prodrug of the first-in-class attachment inhibitor temsavir (TMR) which is being evaluated in patients with multidrug resistant HIV-1 infection. In vitro studies indicated that TMR and its 2 major metabolites are inhibitors of organic cation transporters (OCT)1, OCT2, and multidrug and toxin extrusion transporters (MATEs). To assess the clinical relevance, of OCT and MATE inhibition, mechanistic static DDI prediction with calculated Imax,u/IC50 ratios was below the cut-off limits for a DDI flag based on FDA guidelines and above the cut-off limits for MATEs based on EMA guidelines. Methods Metformin is a commonly used probe substrate for OCT1, OCT2 and MATEs. To predict the potential for a drug interaction between TMR and metformin, a physiologically based pharmacokinetic (PBPK) model for TMR was developed based on its physicochemical properties, in vitro and in vivo data. The model was verified and validated through comparison with clinical data. The TMR PBPK model accurately described AUC and Cmax within 30% of the observed data for single and repeat dose studies with or without food. The SimCYP models for metformin and ritonavir were qualified using literature data before applications of DDI prediction for TMR Results TMR was simulated at steady state concentrations after repeated oral doses of FTR 600 mg twice daily which allowed assessment of the potential OCT1, OCT2, and MATEs inhibition by TMR and metabolites. No significant increase in metformin systemic exposure (AUC or Cmax) was predicted with FTR co-administration. In addition, a sensitivity analysis was conducted for either hepatic OCT1 Ki, or renal OCT2 and MATEs Ki values. The model output indicated that, a 10-fold more potent Ki value for TMR would be required to have a ~15% increase in metformin exposure Conclusion Based on mechanistic static models and PBPK modeling and simulation, the OCT1/2 and MATEs inhibition potential of TMR and its metabolites on metformin pharmacokinetics is not clinically significant. No dose adjustment of metformin is necessary when co-administered with FTR Disclosures Xiusheng Miao, PhD, GlaxoSmithKline (Employee) Mindy Magee, Doctor of Pharmacy, GlaxoSmithKline (Employee, Shareholder) Peter D. Gorycki, BEChe, MSc, PhD, GSK (Employee, Shareholder) Katy P. Moore, PharmD, RPh, ViiV Healthcare (Employee)


Author(s):  
Armin Sadighi ◽  
Lorenzo Leggio ◽  
Fatemeh Akhlaghi

Abstract Aims A physiologically based pharmacokinetic (PBPK) modeling approach was used to simulate the concentration-time profile of ethanol (EtOH) in stomach, duodenum, plasma and other tissues upon consumption of beer and whiskey under fasted and fed conditions. Methods A full PBPK model was developed for EtOH using the advanced dissolution, absorption and metabolism (ADAM) model fully integrated into the Simcyp Simulator® 15 (Simcyp Ltd., Sheffield, UK). The prediction performance of the developed model was verified and the EtOH concentration-time profile in different organs was predicted. Results Simcyp simulation showed ≤ 2-fold difference in values of EtOH area under the concentration-time curve (AUC) in stomach and duodenum as compared to the observed values. Moreover, the simulated EtOH maximum concentration (Cmax), time to reach Cmax (Tmax) and AUC in plasma were comparable to the observed values. We showed that liver is exposed to the highest EtOH concentration, faster than other organs (Cmax = 839.50 mg/L and Tmax = 0.53 h), while brain exposure of EtOH (AUC = 1139.43 mg·h/L) is the highest among all other organs. Sensitivity analyses (SAs) showed direct proportion of EtOH rate and extent of absorption with administered EtOH dose and inverse relationship with gastric emptying time (GE) and steady-state volume of distribution (Vss). Conclusions The current PBPK model approach might help with designing in vitro experiments in the area of alcohol organ damage or alcohol-drug interaction studies.


Pharmaceutics ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 997 ◽  
Author(s):  
Raul Huet ◽  
Gunnar Johanson

(1) Background: Inhalant abuse and misuse are still widespread problems. 1,1-Difluoroethane abuse is reported to be potentially fatal and to cause acute and chronic adverse health effects. Lab testing for difluoroethane is seldom done, partly because the maximum detection time (MDT) is unknown. We sought to reliably estimate the MDT of difluoroethane in blood after inhalation abuse; (2) Methods: MDT were estimated for the ad ult male American population using a physiologically based pharmacokinetic (PBPK) model and abuse patterns detailed by two individuals. Based on sensitivity analyses, variability in huffing pattern and body mass index was introduced in the model by Monte Carlo simulation; (3) Results: With a detection limit of 0.14 mg/L, the median MDT was estimated to be 10.5 h (5th–95th percentile 7.8–12.8 h) after the 2-h abuse scenario and 13.5 h (10.5–15.8 h) after the 6-h scenario. The ranges reflect variability in body mass index (and, hence, amount of body fat) and, more so, variable inhalation patterns; (4) Conclusions: Our simulations suggest that the MDT of difluoroethane in blood after abuse ranges from 7.8 to 15.8 h. Although shorter compared to many other drugs, these MDT are sufficient to allow for testing several hours after suspected intoxication in a patient.


2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Blessy George ◽  
Annie Lumen ◽  
Christine Nguyen ◽  
Barbara Wesley ◽  
Jian Wang ◽  
...  

Abstract Pregnancy is a period of significant change that impacts physiological and metabolic status leading to alterations in the disposition of drugs. Uncertainty in drug dosing in pregnancy can lead to suboptimal therapy, which can contribute to disease exacerbation. A few studies show there are increased dosing requirements for antidepressants in late pregnancy; however, the quantitative data to guide dose adjustments are sparse. We aimed to develop a physiologically based pharmacokinetic (PBPK) model that allows gestational-age dependent prediction of sertraline dosing in pregnancy. A minimal physiological model with defined gut, liver, plasma, and lumped placental-fetal compartments was constructed using the ordinary differential equation solver package, ‘mrgsolve’, in R. We extracted data from the literature to parameterize the model, including sertraline physicochemical properties, in vitro metabolism studies, disposition in nonpregnant women, and physiological changes during pregnancy. The model predicted the pharmacokinetic parameters from a clinical study with eight subjects for the second trimester and six subjects for the third trimester. Based on the model, gestational-dependent changes in physiology and metabolism account for increased clearance of sertraline (up to 143% at 40 weeks gestational age), potentially leading to under-dosing of pregnant women when nonpregnancy doses are used. The PBPK model was converted to a prototype web-based interactive dosing tool to demonstrate how the output of a PBPK model may translate into optimal sertraline dosing in pregnancy. Quantitative prediction of drug exposure using PBPK modeling in pregnancy will support clinically appropriate dosing and increase the therapeutic benefit for pregnant women.


2019 ◽  
Vol 173 (1) ◽  
pp. 86-99 ◽  
Author(s):  
Pankajini Mallick ◽  
Marjory Moreau ◽  
Gina Song ◽  
Alina Y Efremenko ◽  
Salil N Pendse ◽  
...  

Abstract To address concerns around age-related sensitivity to pyrethroids, a life-stage physiologically based pharmacokinetic (PBPK) model, supported by in vitro to in vivo extrapolation (IVIVE) was developed. The model was used to predict age-dependent changes in target tissue exposure of 8 pyrethroids; deltamethrin (DLM), cis-permethrin (CPM), trans-permethrin, esfenvalerate, cyphenothrin, cyhalothrin, cyfluthrin, and bifenthrin. A single model structure was used based on previous work in the rat. Intrinsic clearance (CLint) of each individual cytochrome P450 or carboxylesterase (CES) enzyme that are active for a given pyrethroid were measured in vitro, then biologically scaled to obtain in vivo age-specific total hepatic CLint. These IVIVE results indicate that, except for bifenthrin, CES enzymes are largely responsible for human hepatic metabolism (>50% contribution). Given the high efficiency and rapid maturation of CESs, clearance of the pyrethroids is very efficient across ages, leading to a blood flow-limited metabolism. Together with age-specific physiological parameters, in particular liver blood flow, the efficient metabolic clearance of pyrethroids across ages results in comparable to or even lower internal exposure in the target tissue (brain) in children than that in adults in response to the same level of exposure to a given pyrethroid (Cmax ratio in brain between 1- and 25-year old = 0.69, 0.93, and 0.94 for DLM, bifenthrin, and CPM, respectively). Our study demonstrated that a life-stage PBPK modeling approach, coupled with IVIVE, provides a robust framework for evaluating age-related differences in pharmacokinetics and internal target tissue exposure in humans for the pyrethroid class of chemicals.


2019 ◽  
Vol 172 (2) ◽  
pp. 330-343
Author(s):  
Alice A Han ◽  
Charles Timchalk ◽  
Zana A Carver ◽  
Thomas J Weber ◽  
Kimberly J Tyrrell ◽  
...  

Abstract Saliva has become a favorable sample matrix for biomonitoring due to its noninvasive attributes and overall flexibility in collection. To ensure measured salivary concentrations reflect the exposure, a solid understanding of the salivary transport mechanism and relationships between salivary concentrations and other monitored matrices (ie, blood, urine) is needed. Salivary transport of a commonly applied herbicide, 2,4-dichlorophenoxyacetic acid (2,4-D), was observed in vitro and in vivo and a physiologically based pharmacokinetic (PBPK) model was developed to translate observations from the cell culture model to those in animal models and further evaluate 2,4-D kinetics in humans. Although apparent differences in experimental in vitro and in vivo saliva:plasma ratios (0.034 and 0.0079) were observed, simulations with the PBPK model demonstrated dynamic time and dose-dependent saliva:plasma ratios, elucidating key mechanisms affecting salivary transport. The model suggested that 2,4-D exhibited diffusion-limited transport to saliva and was additionally impacted by protein binding saturation and permeability across the salivary gland. Consideration of sampling times post-exposure and potential saturation of transport mechanisms are then critical aspects for interpreting salivary 2,4-D biomonitoring observations. This work utilized PBPK modeling in in vitro to in vivo translation to explore benefits and limitations of salivary analysis for occupational biomonitoring.


2017 ◽  
Vol 61 (7) ◽  
Author(s):  
Darren M. Moss ◽  
Paul Domanico ◽  
Melynda Watkins ◽  
Seonghee Park ◽  
Ryan Randolph ◽  
...  

ABSTRACT Tenofovir disoproxil fumarate (TDF), a prodrug of tenofovir, has oral bioavailability (25%) limited by intestinal transport (P-glycoprotein), and intestinal degradation (carboxylesterase). However, the influence of luminal pancreatic enzymes is not fully understood. Physiologically based pharmacokinetic (PBPK) modeling has utility for estimating drug exposure from in vitro data. This study aimed to develop a PBPK model that included luminal enzyme activity to inform dose reduction strategies. TDF and tenofovir stability in porcine pancrelipase concentrations was assessed (0, 0.48, 4.8, 48, and 480 U/ml of lipase; 1 mM TDF; 37°C; 0 to 30 min). Samples were analyzed using mass spectrometry. TDF stability and permeation data allowed calculation of absorption rates within a human PBPK model to predict plasma exposure following 6 days of once-daily dosing with 300 mg of TDF. Regional absorption of drug was simulated across gut segments. TDF was degraded by pancrelipase (half-lives of 0.07 and 0.62 h using 480 and 48 U/ml, respectively). Previously reported maximum concentration (C max; 335 ng/ml), time to C max (T max; 2.4 h), area under the concentration-time curve from 0 to 24 h (AUC0–24; 3,045 ng · h/ml), and concentration at 24 h (C 24; 48.3 ng/ml) were all within a 0.5-fold difference from the simulated C max (238 ng/ml), T max (3 h), AUC0–24 (3,036 ng · h/ml), and C 24 (42.7 ng/ml). Simulated TDF absorption was higher in duodenum and jejunum than in ileum (p<0.05). These data support that TDF absorption is limited by the action of intestinal lipases. Our results suggest that bioavailability may be improved by protection of drug from intestinal transporters and enzymes, for example, by coadministration of enzyme-inhibiting agents or nanoformulation strategies.


2012 ◽  
Vol 2012 ◽  
pp. 1-8
Author(s):  
Chensheng Lu ◽  
Leo Andres

We illustrated the development of a simple pharmacokinetic (SPK) model aiming to estimate the absorbed chlorpyrifos doses using urinary biomarker data, 3,5,6-trichlorpyridinol as the model input. The effectiveness of the SPK model in the pesticide risk assessment was evaluated by comparing dose estimates using different urinary composite data. The dose estimates resulting from the first morning voids appeared to be lower than but not significantly different to those using before bedtime, lunch or dinner voids. We found similar trend for dose estimates using three different urinary composite data. However, the dose estimates using the SPK model for individual children were significantly higher than those from the conventional physiologically based pharmacokinetic (PBPK) modeling using aggregate environmental measurements of chlorpyrifos as the model inputs. The use of urinary data in the SPK model intuitively provided a plausible alternative to the conventional PBPK model in reconstructing the absorbed chlorpyrifos dose.


2018 ◽  
Author(s):  
Dustin F. Kapraun ◽  
John F. Wambaugh ◽  
R. Woodrow Setzer ◽  
Richard S. Judson

ABSTRACTMany parameters treated as constants in traditional physiologically based pharmacokinetic models must be formulated as time-varying quantities when modeling pregnancy and gestation due to the dramatic physiological and anatomical changes that occur during this period. While several collections of empirical models for such parameters have been published, each has shortcomings. We sought to create a repository of empirical models for tissue volumes, blood flow rates, and other quantities that undergo substantial changes in a human mother and her fetus during the time between conception and birth, and to address deficiencies with similar, previously published repositories. We used maximum likelihood estimation to calibrate various models for the time-varying quantities of interest, and then used the Akaike information criterion to select an optimal model for each quantity. For quantities of interest for which time-course data were not available, we constructed composite models using percentages and/or models describing related quantities. In this way, we developed a comprehensive collection of formulae describing parameters essential for constructing a PBPK model of a human mother and her fetus throughout the approximately 40 weeks of pregnancy and gestation. We included models describing blood flow rates through various fetal blood routes that have no counterparts in adults. Our repository of mathematical models for anatomical and physiological quantities of interest provides a basis for PBPK models of human pregnancy and gestation, and as such, it can ultimately be used to support decision-making with respect to optimal pharmacological dosing and risk assessment for pregnant women and their developing fetuses. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.AUTHOR SUMMARYPhysiologically based pharmacokinetic modeling is a well-known technique for making predictions about internal time-course concentrations of a substance that has entered an organism. This tool is widely used in both pharmaceutical research and human health risk assessment because it harnesses one of the fundamental tenets of both pharmacology and toxicology: it is the concentrations of an active chemical that reach internal target tissues, rather than externally applied “doses”, that govern the extent of the response (whether beneficial or adverse). Constructing physiologically based pharmacokinetic models for pregnancy and gestation presents a considerable challenge because many of the required parameters (such as blood flow rates or tissue volumes) that are typically assumed to be constant in adult models or short-duration simulations cannot be assumed to be constant when modeling pregnancy. Here we present models, stated as functions of gestational age, for anatomical and physiological changes that occur in a human mother and fetus during pregnancy and gestation. We evaluated and selected models by applying a consistent statistical technique, and where possible, we compared results produced by our models to those produced by previously-published models. The collection of pregnancy parameter models presented here represents the most comprehensive such collection to date.


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