Development of a Physiologically Based Pharmacokinetic Model for Prediction of Ethanol Concentration-Time Profile in Different Organs

Concentration Time ◽

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.

Simulating Intestinal Transporter and Enzyme Activity in a Physiologically Based Pharmacokinetic Model for Tenofovir Disoproxil Fumarate

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.00105-17 ◽

2017 ◽

Vol 61 (7) ◽

Cited By ~ 3

Author(s):

Darren M. Moss ◽

Paul Domanico ◽

Melynda Watkins ◽

Seonghee Park ◽

Ryan Randolph ◽

...

Keyword(s):

Enzyme Activity ◽

Tenofovir Disoproxil Fumarate ◽

Drug Exposure ◽

Pbpk Model ◽

Intestinal Transport ◽

Pbpk Modeling ◽

Time Curve ◽

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.

Development of Physiologically Based Pharmacokinetic Model for Orally Administered Fexuprazan in Humans

Pharmaceutics ◽

10.3390/pharmaceutics13060813 ◽

2021 ◽

Vol 13 (6) ◽

pp. 813

Author(s):

Yoo-Seong Jeong ◽

Min-Soo Kim ◽

Nora Lee ◽

Areum Lee ◽

Yoon-Jee Chae ◽

...

Keyword(s):

Gastric Acid ◽

Pbpk Model ◽

Pbpk Modeling ◽

Drug Candidate ◽

Metabolite Formation ◽

Pbpk Models ◽

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.

1315. No Dose Adjustment of Metformin with Fostemsavir Coadministration Based on Mechanistic Static and Physiologically Based Pharmacokinetic Models

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.1497 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S669-S669

Author(s):

Dung N Nguyen ◽

Xiusheng Miao ◽

Mindy Magee ◽

Guoying Tai ◽

Peter D Gorycki ◽

...

Keyword(s):

Dose Adjustment ◽

Pbpk Model ◽

Systemic Exposure ◽

Multidrug Resistant ◽

Pbpk Modeling ◽

Repeat Dose ◽

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)

1,1-Difluoroethane Detection Time in Blood after Inhalation Abuse Estimated by Monte Carlo PBPK Modeling

Pharmaceutics ◽

10.3390/pharmaceutics12100997 ◽

2020 ◽

Vol 12 (10) ◽

pp. 997 ◽

Cited By ~ 1

Author(s):

Raul Huet ◽

Gunnar Johanson

Keyword(s):

Body Mass Index ◽

Monte Carlo ◽

Body Mass ◽

Pbpk Model ◽

Sensitivity Analyses ◽

Pbpk Modeling ◽

Detection Time ◽

Adverse Health Effects ◽

(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.

A Physiologically Based Pharmacokinetic Analysis To Predict the Pharmacokinetics of Intravenous Isavuconazole in Patients with or without Hepatic Impairment

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.02032-20 ◽

2021 ◽

Vol 65 (5) ◽

Author(s):

Huiping Huang ◽

Helin Xie ◽

Nupur Chaphekar ◽

Ruichao Xu ◽

Raman Venkataramanan ◽

...

Keyword(s):

Hepatic Impairment ◽

Pbpk Model ◽

Pharmacokinetic Analysis ◽

Moderate Hepatic Impairment ◽

Healthy Population ◽

Severe Hepatic Impairment ◽

Time Curve ◽

Concentration Time ◽

ABSTRACT Isavuconazole (ISA) is an azole antifungal used in the treatment of invasive aspergillosis and mucormycosis. Patients with mild or moderate hepatic impairment have lower clearance (CL) than the healthy population. Currently, there are no data on ISA in patients with severe hepatic impairment (Child-Pugh class C). The purposes of this study were to build a physiologically based pharmacokinetic (PBPK) model to describe the pharmacokinetics (PK) of intravenous ISA and to predict changes in ISA disposition in different patient populations and in patients with hepatic impairment so as to guide personalized dosing. By incorporating the systemic and drug-specific parameters of ISA, the model was initially developed in a healthy population and was validated with 10 independent PK profiles obtained from healthy subjects and from patients with normal liver function. The results showed satisfactory predictive capacity; most of the relative predictive errors were within ±30% for the area under the concentration-time curve (AUC) and the maximum concentration of the drug in serum (Cmax). The observed concentration-time profiles of ISA in plasma were well described by the model-predicted profiles. The model adequately predicted the reduced CL of ISA in patients with mild or moderate hepatic impairment. Furthermore, the model predicted a decrease in CL of about 60% in patients with severe hepatic impairment. Therefore, we recommend reducing the dose by 50% in patients with severe hepatic impairment. The model also predicted differences in the PK of ISA between Caucasian and Asian populations, with a Chinese/Caucasian CL ratio of 0.67. The PBPK model of ISA that was developed provides a reasonable approach for optimizing the dosage regimen in different ethnic populations and in patients with severe hepatic impairment.

Physiologically Based Pharmacokinetic Modeling of Cefadroxil in Mouse, Rat, and Human to Predict Concentration–Time Profile at Infected Tissue

Frontiers in Pharmacology ◽

10.3389/fphar.2021.692741 ◽

2021 ◽

Vol 12 ◽

Author(s):

Zhongxia Tan ◽

Youxi Zhang ◽

Chao Wang ◽

Le Sun

Keyword(s):

Plasma Concentration ◽

Pbpk Model ◽

Oral Absorption ◽

Time Profile ◽

Infected Tissue ◽

Dose Selection ◽

Pbpk Models ◽

Concentration Time ◽

The aim of this study was to develop physiologically based pharmacokinetic (PBPK) models capable of simulating cefadroxil concentrations in plasma and tissues in mouse, rat, and human. PBPK models in this study consisted of 14 tissues and 2 blood compartments. They were established using measured tissue to plasma partition coefficient (Kp) in mouse and rat, absolute expression levels of hPEPT1 along the entire length of the human intestine, and the transporter kinetic parameters. The PBPK models also assumed that all the tissues were well-stirred compartments with perfusion rate limitations, and the ratio of the concentration in tissue to the unbound concentration in plasma is identical across species. These PBPK models were validated strictly by a series of observed plasma concentration–time profile data. The average fold error (AFE) and absolute average fold error (AAFE) values were all less than 2. The models’ rationality and accuracy were further demonstrated by the almost consistent Vss calculated by the PBPK model and noncompartmental method, as well as the good allometric scaling relationship of Vss and CL. The model suggests that hPEPT1 is the major transporter responsible for the oral absorption of cefadroxil in human, and the plasma concentration–time profiles of cefadroxil were not sensitive to dissolution rate faster than T85% = 2 h. The cefadroxil PBPK model in human is reliable and can be used to predict concentration–time profile at infected tissue. It may be useful for dose selection and informative decision-making during clinical trials and dosage form design of cefadroxil and provide a reference for the PBPK model establishment of hPEPT1 substrate.

Physiologically Based Pharmacokinetic Modeling of Salivary Concentrations for Noninvasive Biomonitoring of 2,4-Dichlorophenoxyacetic Acid (2,4-D)

Toxicological Sciences ◽

10.1093/toxsci/kfz206 ◽

2019 ◽

Vol 172 (2) ◽

pp. 330-343

Author(s):

Alice A Han ◽

Charles Timchalk ◽

Zana A Carver ◽

Thomas J Weber ◽

Kimberly J Tyrrell ◽

...

Keyword(s):

Pbpk Model ◽

Pbpk Modeling ◽

Dichlorophenoxyacetic Acid ◽

Diffusion Limited ◽

Physiologically Based ◽

Dynamic Time ◽

2,4 Dichlorophenoxyacetic Acid

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.

Drug-drug interaction (DDI) assessments of ruxolitinib, a dual substrate of CYP3A4 and CYP2C9, using a verified physiologically based pharmacokinetic (PBPK) model to support regulatory submissions

Drug Metabolism and Personalized Therapy ◽

10.1515/dmpt-2018-0042 ◽

2019 ◽

Vol 34 (2) ◽

Cited By ~ 1

Author(s):

Kenichi Umehara ◽

Felix Huth ◽

Yi Jin ◽

Hilmar Schiller ◽

Vassilios Aslanis ◽

...

Keyword(s):

Dose Reduction ◽

Dose Adjustment ◽

Pbpk Model ◽

Pbpk Modeling ◽

Cyp Enzymes ◽

Physiologically Based ◽

Cyp3a4 Inhibitors ◽

Simulation Results

Abstract Ruxolitinib is mainly metabolized by cytochrome P450 (CYP) enzymes CYP3A4 and CYP2C9 followed by minor contributions of other hepatic CYP enzymes in vitro. A physiologically based pharmacokinetic (PBPK) model was established to evaluate the changes in the ruxolitinib systemic exposures with co-administration of CYP3A4 and CYP2C9 perpetrators. The fractions metabolized in the liver via oxidation by CYP enzymes (fm,CYP3A4 = 0.75, fm,CYP2C9 = 0.19, and fm,CYPothers = 0.06) for an initial ruxolitinib model based on in vitro data were optimized (0.43, 0.56, and 0.01, respectively) using the observed exposure changes of ruxolitinib (10 mg) with co-administered ketoconazole (200 mg). The reduced amount of fm,CYP3A4 was distributed to fm,CYP2C9. For the initial ruxolitinib model with co-administration of ketoconazole, the area under the curve (AUC) increase of 2.60-fold was over-estimated compared with the respective observation (1.91-fold). With the optimized fm values, the predicted AUC ratio was 1.82. The estimated AUC ratios of ruxolitinib by co-administration of the moderate CYP3A4 inhibitor erythromycin (500 mg) and the strong CYP3A4 inducer rifampicin (600 mg) were within a 20% error compared with the clinically observed values. The PBPK modeling results may provide information on the labeling, i.e. supporting a dose reduction by half for co-administration of strong CYP3A4 inhibitors. Furthermore, an AUC increase of ruxolitinib in the absence or presence of the dual CYP3A4 and CYP2C9 inhibitor fluconazole (100–400 mg) was prospectively estimated to be 1.94- to 4.31-fold. Fluconazole simulation results were used as a basis for ruxolitinib dose adjustment when co-administering perpetrator drugs. A ruxolitinib PBPK model with optimized fm,CYP3A4 and fm,CYP2C9 was established to evaluate victim DDI risks. The previous minimal PBPK model was supported by the FDA for the dose reduction strategy, halving the dose with the concomitant use of strong CYP3A4 inhibitors and dual inhibitors on CYP2C9 and CYP3A4, such as fluconazole at ≤200 mg. Fluconazole simulation results were used as supportive evidence in discussions with the FDA and EMA about ruxolitinib dose adjustment when co-administering perpetrator drugs. Thus, this study demonstrated that PBPK modeling can support characterizing DDI liabilities to inform the drug label and might help reduce the number of clinical DDI studies by simulations of untested scenarios, when a robust PBPK model is established.

A Physiologically Based Pharmacokinetic Model of Parathion Based on Chemical-Specific Parameters Determined In Vitro

Journal of the American College of Toxicology ◽

10.3109/10915819009078766 ◽

1990 ◽

Vol 9 (6) ◽

pp. 611-619 ◽

Cited By ~ 13

Author(s):

Lester G. Sultatos

Keyword(s):

Pbpk Model ◽

Equilibrium Dialysis ◽

Distribution Coefficients ◽

Kinetic Constants ◽

Pbpk Modeling ◽

Pbpk Models ◽

Hepatic Extraction Ratio ◽

Physiologically based pharmacokinetic (PBPK) modeling is an approach that has been used to predict successfully the pharmacokinetic disposition of numerous foreign chemicals. The accuracy of a PBPK model is dependent on the reliability of estimates of tissue/blood distribution coefficients (Kp) and appropriate kinetic constants descriptive of the elimination of the chemical under consideration. The present study evaluates the validity of the use of Kp values and kinetic constants determined in vitro for use in a PBPK model for the organothiophosphorus insecticide parathion. Kps were determined by equilibrium dialysis, whereas Vmaxs and Kms descriptive of the biotransformation of parathion were calculated from values determined previously in this laboratory. Using these kinetic constants to calculate a hepatic extraction ratio of parathion in the mouse yielded a value identical to that observed with mouse liver perfusions in situ performed previously in this laboratory. Use of Kp values and kinetic constants determined in vitro in a PBPK model accurately simulated levels of parathion in brain, lungs, blood, and liver up to 3 h after intravenous administration of this insecticide. This study demonstrates that chemical-specific parameters determined entirely in vitro can be used to construct accurate PBPK models.

Development of a Physiologically Based Pharmacokinetic Model for Hydroxychloroquine and Its Application in Dose Optimization in Specific COVID-19 Patients

Frontiers in Pharmacology ◽

10.3389/fphar.2020.585021 ◽

2021 ◽

Vol 11 ◽

Author(s):

Miao Zhang ◽

Xueting Yao ◽

Zhe Hou ◽

Xuan Guo ◽

Siqi Tu ◽

...

Keyword(s):

Pbpk Model ◽

Clinical Findings ◽

Lung Model ◽

Elderly Subjects ◽

Distribution Data ◽

Physiologically Based ◽

Drug Actions

In Feb 2020, we developed a physiologically-based pharmacokinetic (PBPK) model of hydroxychloroquine (HCQ) and integrated in vitro anti-viral effect to support dosing design of HCQ in the treatment of COVID-19 patients in China. This, along with emerging research and clinical findings, supported broader uptake of HCQ as a potential treatment for COVID-19 globally at the beginning of the pandemics. Therefore, many COVID-19 patients have been or will be exposed to HCQ, including specific populations with underlying intrinsic and/or extrinsic characteristics that may affect the disposition and drug actions of HCQ. It is critical to update our PBPK model of HCQ with adequate drug absorption and disposition mechanisms to support optimal dosing of HCQ in these specific populations. We conducted relevant in vitro and in vivo experiments to support HCQ PBPK model update. Different aspects of this model are validated using PK study from 11 published references. With parameterization informed by results from monkeys, a permeability-limited lung model is employed to describe HCQ distribution in the lung tissues. The updated model is applied to optimize HCQ dosing regimens for specific populations, including those taking concomitant medications. In order to meet predefined HCQ exposure target, HCQ dose may need to be reduced in young children, elderly subjects with organ impairment and/or coadministration with a strong CYP2C8/CYP2D6/CYP3A4 inhibitor, and be increased in pregnant women. The updated HCQ PBPK model informed by new metabolism and distribution data can be used to effectively support dosing recommendations for clinical trials in specific COVID-19 patients and treatment of patients with malaria or autoimmune diseases.