A semi-mechanistic model to predict the effects of liver cirrhosis on drug clearance

Exploring the Pharmacokinetics of Drugs in Disabled Saudi Patients: A Systematic Review

Background/Objectives: Disability is a term that involves mental, intellectual, or sensory impairment resulting in the loss of one's ability to walk or perform the activities necessary to live in a society. This study aims to collect all the data regarding the absorption, distribution, and disposition of drugs in disabled Saudi patients, i.e., patients suffering from epilepsy, cancer, cardiovascular diseases, etc., and then compare these results with data reported in other ethnicities. Methods: An exhaustive online search used the key terms in Google Scholar, PubMed, Cochrane Library, and Science Direct to extract all articles that met the eligibility criteria. All research studies containing pharmacokinetic (PK) parameters (area under the curve from 0 to infinity (AUC0-∞), maximal plasma concentration (Cmax), clearance (CL), volume of distribution, time to reach maximum plasma concentration, and half-life) were included in this review. Results: In pediatric epileptic patients, carbamazepine showed a notable decrease in Cmax with increasing age, which may be due to ontogenetic changes in its disposition. The AUC0-∞ of busulphan in adult hematopoietic stem cell transplantation patients was recorded as 4392.5 ± 1354.65 μg·h/mL, with high inter-individual variability. Moreover, the CL of vancomycin was reported to be 25% higher among cancer patients in comparison to non-cancer subjects. Conclusions: The complications in disabled patients due to alterations in cytochrome P450 enzymes, pathophysiology, genetics, and ethnicity emphasize the significance of patient-centered drug dosing. These findings may aid healthcare physicians in refining therapeutic care in this population.

Clinical Exploration and Physiologically Based Modelling of the Impact of Hepatic Impairment on Entrectinib Pharmacokinetics

BACKGROUND AND OBJECTIVES

This study investigates the pharmacokinetics (PK) of entrectinib and its metabolite M5 (CYP3A4 substrates) in patients with hepatic impairment (HI) and applies physiologically based pharmacokinetic (PBPK) modelling to understand the observed changes mechanistically.

METHOD

After a single oral administration of entrectinib at 100 mg, measured plasma concentrations for entrectinib and M5 in control subjects and HI patients were compared to predictions made with Simcyp®. Model sensitivity analyses explored the possible reasons for mismatches to observed data. Reduced oral absorption due to lower bile salt (BS) levels in the intestinal lumen in hepatic impairment was examined.

RESULTS

Physiologically based pharmacokinetic model simulations overestimated the 80% increase in entrectinib area under the plasma concentration curve between 0h to infinity (AUCinf) observed in patients with severe HI, predicting a > 2-fold rise. Observed maximal plasma concentration (Cmax) increased by 25% from controls to mild HI but decreased by 61% from mild to severe HI. Although the model predicted Cmax within a 2-fold range, there was a trend to greater over-prediction with increasing HI severity. For M5, PBPK modelling did not capture the observed trends well. The Cmax and AUCinf were overestimated in HI patients and the trend to reduction of Cmax with minimal change in AUCinf with increasing severity of HI was not well captured. Decreasing Simcyp® default luminal BS concentrations by 2-, 6-, and 8.7-fold for mild, moderate, and severe HI improved the predictions for both entrectinib and M5.

CONCLUSION

Physiologically based pharmacokinetic model simulations tended to overestimate the observed moderate changes in entrectinib exposures due to HI. For improved prediction of poorly soluble lipophilic drugs like entrectinib there is a need for PBPK models of HI to account for additional pathophysiological changes such as reduced intestinal BS levels.

TRIAL REGISTRATION

NCT number: NCT04226833.

Pharmacokinetic Prediction of Immediate- and Extended-Release Tablets for Patients with Liver Disease Using Whole Body Physiologically-Based Pharmacokinetic Modeling for the Antipsychotic Drug Quetiapine

Although quetiapine metabolism occurs extensively in the liver and careful dosing is recommended in patients with liver disease, there has been a paucity of pharmacometric studies to adjust the clinical dose of quetiapine according to liver-disease severity. This study aimed to establish a whole-body, physiologically-based pharmacokinetic (WB-PBPK) model to explain interindividual variability in quetiapine PK and quantitatively predict PK in patients with liver disease. The developed WB-PBPK model well described the PK characteristics of different quetiapine regimens in healthy populations. The PK predictions could also be applied to patients with schizophrenia (without significant differences from healthy subjects). For the same total dose of quetiapine, both immediate-release (IR) and extended-release (ER) tablets showed significantly increased exposure and decreased clearance in patients with liver disease compared to healthy subjects. The model showed that steady-state plasma quetiapine concentrations exceeded the usual therapeutic range after multiple doses of IR tablets 250 mg three times daily or ER tablets 800 mg once daily in patients with liver disease. Therefore, the doses of quetiapine IR or ER tablets could be reduced by 0.10-0.50 times depending on liver-disease severity, so that mean steady-state plasma concentrations could be positioned near the therapeutic range. WB-PBPK modeling for quetiapine enabled quantitative prediction of PK according to IR or ER formulation and liver-disease severity. The results of this study provide useful data for improving the therapeutic use of quetiapine by enabling dose selection based on formulation and liver-disease severity.

Model-Based Dose Selection of a Sphingosine-1-Phosphate Modulator, Etrasimod, in Patients with Various Degrees of Hepatic Impairment

BACKGROUND/OBJECTIVES

Etrasimod is a newly FDA-approved Sphingosine-1-Phosphate modulator indicated for moderate and severe ulcerative colitis. It is extensively metabolized in the liver via the cytochrome P450 system and may accumulate markedly in patients with hepatic dysfunction, exposing them to toxicity. The aim of the current study is to utilize a physiologically-based pharmacokinetic modeling approach to evaluate the impact of hepatic impairment on the pharmacokinetic behavior of etrasimod and to appropriately select dosage regimens for patients with chronic liver disease; Methods: PK-Sim was used to develop the etrasimod PBPK model, which was verified using clinical data from healthy subjects and subsequently adapted to reflect the physiological changes associated with varying degrees of hepatic dysfunction; Results: Simulations indicated that hepatic clearance of etrasimod is clearly reduced in patients with Child-Pugh B and C liver impairment. Based on these findings, dosing adjustments were proposed to achieve therapeutic exposures equivalent to those in individuals with normal liver function. In the Child-Pugh B and C population groups, 75% and 62.5%, respectively, of the standard dose were enough to have comparable exposure to the healthy population. These adjusted dosages aim to mitigate the risk of drug toxicity while maintaining efficacy; Conclusions: The PBPK model provides a robust framework for individualizing drug therapy in patients with hepatic impairment, ensuring safer and more effective treatment outcomes. Further clinical studies are warranted to verify these dosing recommendations and to refine the model for broader clinical applications.

Advancing understanding of human variability through toxicokinetic modeling, in vitro-in vivo extrapolation, and new approach methodologies

The merging of physiology and toxicokinetics, or pharmacokinetics, with computational modeling to characterize dosimetry has led to major advances for both the chemical and pharmaceutical research arenas. Driven by the mutual need to estimate internal exposures where in vivo data generation was simply not possible, the application of toxicokinetic modeling has grown exponentially in the past 30 years. In toxicology the need has been the derivation of quantitative estimates of toxicokinetic and toxicodynamic variability to evaluate the suitability of the tenfold uncertainty factor employed in risk assessment decision-making. Consideration of a host of physiologic, ontogenetic, genetic, and exposure factors are all required for comprehensive characterization. Fortunately, the underlying framework of physiologically based toxicokinetic models can accommodate these inputs, in addition to being amenable to capturing time-varying dynamics. Meanwhile, international interest in advancing new approach methodologies has fueled the generation of in vitro toxicity and toxicokinetic data that can be applied in in vitro-in vivo extrapolation approaches to provide human-specific risk-based information for historically data-poor chemicals. This review will provide a brief introduction to the structure and evolution of toxicokinetic and physiologically based toxicokinetic models as they advanced to incorporate variability and a wide range of complex exposure scenarios. This will be followed by a state of the science update describing current and emerging experimental and modeling strategies for population and life-stage variability, including the increasing application of in vitro-in vivo extrapolation with physiologically based toxicokinetic models in pharmaceutical and chemical safety research. The review will conclude with case study examples demonstrating novel applications of physiologically based toxicokinetic modeling and an update on its applications for regulatory decision-making. Physiologically based toxicokinetic modeling provides a sound framework for variability evaluation in chemical risk assessment.

Effect of protein binding on the pharmacokinetics of the six substrates in the Basel phenotyping cocktail in healthy subjects and patients with liver cirrhosis

Phenotyping serves to estimate enzyme activities in healthy persons and patients in vivo. Low doses of enzyme-specific substrates are administered, and activities estimated using metabolic ratios (MR, calculated as AUCmetabolite/AUCparent). We administered the Basel phenotyping cocktail containing caffeine (CYP1A2 substrate), efavirenz (CYP2B6), flurbiprofen (CYP2C9), omeprazole (CYP2C19), metoprolol (CYP2D6) and midazolam (CYP3A) to 36 patients with liver cirrhosis and 12 control subjects and determined free and total plasma concentrations over 24 h. Aims were to assess whether MRs reflect CYP activities in patients with liver cirrhosis and whether MRs calculated with free plasma concentrations (MRfree) provide better estimates than with total concentrations (MRtotal). The correlation of MRtotal with MRfree was excellent (R2 >0.910) for substrates with low (<30 %, caffeine and metoprolol) and intermediate protein binding (≥30 and <99 %, midazolam and omeprazole) but weak (R2 <0.30) for substrates with high protein binding (≥99 %, efavirenz and flurbiprofen). The correlations between MRtotal and MRfree with CYP activities were good (R2 >0.820) for CYP1A2, CYP2C19 and CYP2D6. CYP3A4 activity was reflected better by midazolam elimination than by midazolam MRtotal or MRfree. The correlation between MRtotal and MRfree with CYP activity was not significant or weak for CYP2B6 and CYP2C9. In conclusion, MRs of substrates with an extensive protein binding (>99 %) show high inter-patient variabilities and do not accurately reflect CYP activity in patients with liver cirrhosis. Protein binding of the probe drugs has a high impact on the precision of CYP activity estimates and probe drugs with low or intermediate protein binding should be preferred.

Physiologically based pharmacokinetic model of brivaracetam to predict the exposure and dose exploration in hepatic impairment and elderly populations

Brivaracetam (BRV) is a new third-generation antiseizure medication for the treatment of focal epileptic seizures. Its use has been increasing among epileptic populations in recent years, but pharmacokinetic (PK) behavior may change in hepatic impairment and the elderly populations. Due to ethical constraints, clinical trials are difficult to conduct and data are limited. This study used PK-Sim® to develop a physiologically based pharmacokinetic (PBPK) model for adults and extrapolate it to hepatic impairment and the elderly populations. The model was evaluated with clinical PK data, and dosage explorations were conducted. For the adult population with mild hepatic impairment, the dose is recommended to be adjusted to 70 % of the recommended dose, and to 60 % for moderate and severe hepatic impairment. For the elderly population with mild hepatic impairment under 80 years old, it is recommended that the dose be adjusted to 60 % of the recommended dose and to 50 % for moderate and severe conditions. The elderly population with hepatic impairment over 80 years old is adjusted to 50 % of the recommended dose for all stages. Healthy elderly do not need to adjust. The BRV PBPK model was successfully developed, studying exposure in hepatic impairment and elderly populations and optimizing dosing regimens.

Quantitatively Predicting Effects of Exercise on Pharmacokinetics of Drugs Using a Physiologically Based Pharmacokinetic Model

Exercise significantly alters human physiological functions, such as increasing cardiac output and muscle blood flow and decreasing glomerular filtration rate (GFR) and liver blood flow, thereby altering the absorption, distribution, metabolism, and excretion of drugs. In this study, we aimed to establish a database of human physiological parameters during exercise and to construct equations for the relationship between changes in each physiological parameter and exercise intensity, including cardiac output, organ blood flow (e.g., muscle blood flow and kidney blood flow), oxygen uptake, plasma pH and GFR, etc. The polynomial equation P = ΣaiHRi was used for illustrating the relationship between the physiological parameters (P) and heart rate (HR), which served as an index of exercise intensity. The pharmacokinetics of midazolam, quinidine, digoxin, and lidocaine during exercise were predicted by a whole-body physiologically based pharmacokinetic (WB-PBPK) model and the developed database of physiological parameters following administration to 100 virtual subjects. The WB-PBPK model simulation results showed that most of the observed plasma drug concentrations fell within the 5th-95th percentiles of the simulations, and the estimated peak concentrations (Cmax) and area under the curve (AUC) of drugs were also within 0.5-2.0 folds of observations. Sensitivity analysis showed that exercise intensity, exercise duration, medication time, and alterations in physiological parameters significantly affected drug pharmacokinetics and the net effect depending on drug characteristics and exercise conditions. In conclusion, the pharmacokinetics of drugs during exercise could be quantitatively predicted using the developed WB-PBPK model and database of physiological parameters. SIGNIFICANCE STATEMENT: This study simulated real-time changes of human physiological parameters during exercise in the WB-PBPK model and comprehensively investigated pharmacokinetic changes during exercise following oral and intravenous administration. Furthermore, the factors affecting pharmacokinetics during exercise were also revealed.

Treatment of Pain in Cirrhosis: Advice to Caregivers of Those with Rock Livers

PURPOSE

When one considers the significant role of the liver in medication absorption and metabolism, clinicians must appreciate the important ramifications for medication dosing and monitoring in patients with cirrhosis. For many medications, dose adjustments may be necessary to minimize toxicities or avoid adverse effects from drug accumulation. Clinicians could be well served if they can understand in some detail how pharmacokinetic properties are altered in cirrhosis.

METHODS

A PubMed search of the English medical literature starting with 1980 using keywords cirrhosis, pain management, and analgesics was performed, and additional papers were found using references from the first round of papers.

FINDINGS

Patients with cirrhosis often have significant reductions in first-pass metabolism, altered volumes of distribution, and marked reductions in both renal and hepatic elimination of drugs. These factors may contribute to much higher levels of drug exposure compared to the general population. In terms of drug dosing, FDA labeling is often ambiguous and even incongruous with observed pharmacokinetic changes.

IMPLICATIONS

This article may provide guidance for clinicians to optimize pain management in people living with cirrhosis.

KEY MESSAGE

Current FDA labeling for dosing analgesic drugs in patients with cirrhosis is either vague or not consistent with findings from newer pharmacokinetic research. With this review, we hope to provide insight and guidance to clinicians on how to dose-adjust medications commonly utilized in pain management in these patients.

A guide to developing population files for physiologically-based pharmacokinetic modeling in the Simcyp Simulator

The Simcyp Simulator is a software platform widely used in the pharmaceutical industry to conduct stochastic physiologically-based pharmacokinetic (PBPK) modeling. This approach has the advantage of combining routinely generated in vitro data on drugs and drug products with knowledge of biology and physiology parameters to predict a priori potential pharmacokinetic changes in absorption, distribution, metabolism, and excretion for populations of interest. Combining such information with pharmacodynamic knowledge of drugs enables planning for potential dosage adjustment when clinical studies are feasible. Although the conduct of dedicated clinical studies in some patient groups (e.g., with hepatic or renal diseases) is part of the regulatory path for drug development, clinical studies for all permutations of covariates potentially affecting pharmacokinetics are impossible to perform. The role of PBPK in filling the latter gap is becoming more appreciated. This tutorial describes the different input parameters required for the creation of a virtual population giving robust predictions of likely changes in pharmacokinetics. It also highlights the considerations needed to qualify the models for such contexts of use. Two case studies showing the step-by-step development and application of population files for obese or morbidly obese patients and individuals with Crohn's disease are provided as the backbone of our tutorial to give some hands-on and real-world examples.

Combining data on the bioavailability of midazolam and physiologically-based pharmacokinetic modeling to investigate intestinal CYP3A4 ontogeny

Pediatric physiologically-based modeling in drug development has grown in the past decade and optimizing the underlying systems parameters is important in relation to overall performance. In this study, variation of clinical oral bioavailability of midazolam as a function of age is used to assess the underlying ontogeny models for intestinal CYP3A4. Data on midazolam bioavailability in adults and children and different ontogeny patterns for intestinal CYP3A4 were first collected from the literature. A pediatric PBPK model was then used to assess six different ontogeny models in predicting bioavailability from preterm neonates to adults. The average fold error ranged from 0.7 to 1.38, with the rank order of least to most biased model being No Ontogeny < Upreti = Johnson < Goelen < Chen < Kiss. The absolute average fold error ranged from 1.17 to 1.64 with the rank order of most to least precise being Johnson > Upreti > No Ontogeny > Goelen > Kiss > Chen. The optimal ontogeny model is difficult to discern when considering the possible influence of CYP3A5 and other population variability; however, this study suggests that from term neonates and older a faster onset Johnson model with a lower fraction at birth may be close to this. For inclusion in other PBPK models, independent verification will be needed to confirm these results. Further research is needed in this area both in terms of age-related changes in midazolam and similar drug bioavailability and intestinal CYP3A4 ontogeny.

Physiologically-based pharmacokinetic modeling predicts the drug interaction potential of GLS4 in co-administered with ritonavir

GLS4 is a first-in-class hepatitis B virus (HBV) capsid assembly modulator (class I) that is co-administered with ritonavir to maintain the anticipated concentration required for the effective antiviral activity of GLS4. In this study, the first physiologically-based pharmacokinetic (PBPK) model for GLS4/ritonavir was successfully developed. The predictive performance of the PBPK model was verified using data from 39 clinical studies, including single-dose, multiple-dose, food effects, and drug-drug interactions (DDI). The PBPK model accurately described the PK profiles of GLS4 and ritonavir, with predicted values closely aligning with observed data. Based on the verified GLS4/ritonavir model, it prospectively predicts the effect of hepatic impairment (HI) and DDI on its pharmacokinetics (PK). Notably, CYP3A4 inducers significantly influenced GLS4 exposure when co-administered with ritonavir; co-administered GLS4 and ritonavir significantly influenced the exposure of CYP3A4 substrates. Additionally, with the severity of HI increased, there was a corresponding increase in the exposure to GLS4 when co-administered with ritonavir. The GLS4/ritonavir PBPK model can potentially be used as an alternative to clinical studies or guide the design of clinical trial protocols.

Physiologically Based Pharmacokinetic Model for Predicting Omadacycline Pharmacokinetics and Pharmacodynamics in Healthy and Hepatic Impairment Populations

PURPOSE

Omadacycline is a new broad-spectrum aminomethylcycline antibiotic. However, there have been limited pharmacokinetic and pharmacodynamic (PK/PD) studies of omadacycline in patients with hepatic impairment. The aim of this study was to explore the PK/PD of omadacycline intravenous administration in healthy and hepatically impaired populations.

METHODS

A physiologically based pharmacokinetic (PBPK) model of omadacycline was developed and validated based on published demographic data and the physiochemical properties of omadacycline. The PK processes in healthy adults were simulated and then extrapolated to a hepatically impaired population. Monte Carlo simulations were performed for PD evaluation by calculating the probability of target attainment (PTA) and the cumulative fraction of response (CFR) of the approved dosages.

FINDINGS

In the hepatically impaired population, there was no significant difference in the maximum concentration (Cmax) compared with the healthy population, while the area under the plasma concentration-time curve from the first data point extrapolated to infinity (AUC_inf) showed a slight increase. Monte Carlo simulations indicated that the dosage of 200 mg once daily or 100 mg twice daily intravenously (loading dose) and 100 mg once daily intravenously (maintenance dose) could cover the common pathogens of community-acquired bacterial pneumonia (CABP) and acute bacterial skin and skin structure infections (ABSSSI) : Streptococcus pneumoniae, Haemophilus influenzae, and Staphylococcus aureus.

IMPLICATIONS

Hepatic impairment exerts little impact on the PK properties of omadacycline, and no dosage adjustments are necessary for patients with mild and moderate hepatic impairment. Current dosing regimens are predicted to produce satisfactory therapeutic effects against non-drug-resistant strains of Staphylococcus aureus, Streptococcus pneumoniae, and Haemophilus influenzae but may not produce the desired AUC/MIC ratios in patients with Escherichia coli or Klebsiella pneumoniae.

Effect of Hepatic Impairment on Trofinetide Exposures Using an In Silico Physiologically Based Pharmacokinetic Model

INTRODUCTION

Trofinetide is the first drug to be approved for the treatment of Rett syndrome. Hepatic impairment is not expected to affect the pharmacokinetic (PK) profile of trofinetide because of predominant renal excretion. This study was conducted to help understand the potential impact of any hepatic impairment on trofinetide PK.

METHODS

This study used physiologically based PK modeling to estimate trofinetide exposure (maximum drug concentration and area under the concentration-time curve from time zero to infinity) in virtual patients with mild, moderate, and severe hepatic impairment (per Child-Pugh classification) compared with virtual healthy subjects following a 12 g oral trofinetide dose.

RESULTS

In individual deterministic simulations for matched individuals and stochastic simulations at the population level (100 virtual individuals simulated per population), as anticipated, predicted plasma exposures were similar for healthy subjects and for patients with mild, moderate, and severe hepatic impairment. However, predicted blood concentration exposures slightly increased with increasing severity of hepatic impairment because of change in hematocrit levels.

CONCLUSION

This study indicates that hepatic impairment is not expected to have a clinically relevant effect on exposure to trofinetide.

Physiologically Based Pharmacokinetic Modeling to Predict the Impact of Liver Cirrhosis on Glucuronidation via UGT1A4 and UGT2B7/2B4-A Case Study with Midazolam

Hepatic impairment, due to liver cirrhosis, decreases the activity of cytochrome P450 enzymes (CYPs). The use of physiologically based pharmacokinetic (PBPK) modeling to predict this effect for CYP substrates has been well-established, but the effect of cirrhosis on uridine-glucuronosyltransferase (UGT) activities is less studied and few PBPK models have been reported. UGT enzymes are involved in primary N-glucuronidation of midazolam and glucuronidation of 1'-OH-midazolam following CYP3A hydroxylation. In this study, Simcyp was used to establish PBPK models for midazolam, its primary metabolites midazolam-N-glucuronide (UGT1A4) and 1'-OH midazolam (CYP3A4/3A5), and the secondary metabolite 1'-OH-midazolam-O-glucuronide (UGT2B7/2B4), allowing to simulate the impact of liver cirrhosis on the primary and secondary glucuronidation of midazolam. The model was verified in noncirrhotic subjects before extrapolation to cirrhotic patients of Child-Pugh (CP) classes A, B, and C. Our model successfully predicted the exposures of midazolam and its metabolites in noncirrhotic and cirrhotic patients, with 86% of observed plasma concentrations within 5th-95th percentiles of predictions and observed geometrical mean of area under the plasma concentration curve between 0 hours to infinity and maximal plasma concentration within 0.7- to 1.43-fold of predictions. The simulated metabolic ratio defined as the ratio of the glucuronide metabolite AUC over the parent compound AUC (AUCglucuronide/AUCparent, metabolic ratio [MR]), was calculated for midazolam-N-glucuronide to midazolam (indicative of UGT1A4 activity) and decreased by 40% (CP A), 48% (CP B), and 75% (CP C). For 1'-OH-midazolam-O-glucuronide to 1'-OH-midazolam, the MR (indicative of UGT2B7/2B4 activity) dropped by 35% (CP A), 51% (CP B), and 64% (CP C). These predicted MRs were corroborated by the observed data. This work thus increases confidence in Simcyp predictions of the effect of liver cirrhosis on the pharmacokinetics of UGT1A4 and UGT2B7/UGT2B4 substrates. SIGNIFICANCE STATEMENT: This article presents a physiologically based pharmacokinetic model for midazolam and its metabolites and verifies the accurate simulation of pharmacokinetic profiles when using the Simcyp hepatic impairment population models. Exposure changes of midazolam-N-glucuronide and 1'-OH-midazolam-O-glucuronide reflect the impact of decreases in UGT1A4 and UGT2B7/2B4 glucuronidation activity in cirrhotic patients. The approach used in this study may be extended to verify the modeling of other uridine glucuronosyltransferase enzymes affected by liver cirrhosis.

Investigating clinical pharmacokinetics of brivaracetam by using a pharmacokinetic modeling approach

The development of technology and the processing speed of computing machines have facilitated the evaluation of advanced pharmacokinetic (PK) models, making modeling processes simple and faster. The present model aims to analyze the PK of brivaracetam (BRV) in healthy and diseased populations. A comprehensive literature review was conducted to incorporate the BRV plasma concentration data and its input parameters into PK-Sim software, leading to the creation of intravenous (IV) and oral models for both populations. The developed physiologically based pharmacokinetic (PBPK) model of BRV was then assessed using the visual predictive checks, mean observed/predicted ratios (Robs/pre), and average fold error for PK parameters including the maximum systemic concentration (Cmax), the area under the curve at time 0 to t (AUC0-∞), and drug clearance (CL). The PBPK model of BRV demonstrated that mean Robs/pre ratios of the PK parameters remained within the acceptable limits when assessed against a twofold error margin. Furthermore, model predictions were carried out to assess how AUC0-∞ is affected following the administration of BRV in individuals with varying degrees of liver cirrhosis, ranging from different child-pugh (CP) scores like A, B, and C. Moreover, dose adjustments were recommended by considering the variations in Cmax and CL in various kidney disease stages (mild to severe).

In Vitro to In Vivo Scalars for Drug Clearance in Nonalcoholic Fatty Liver and Steatohepatitis

In vitro-in vivo extrapolation (IVIVE) allows prediction of clinical outcomes across populations from in vitro data using specific scalars tailored to the biologic characteristics of each population. This study experimentally determined scalars for patients with varying degrees of nonalcoholic fatty liver disease (NAFLD), ranging from fatty liver to nonalcoholic steatohepatitis (NASH) and cirrhosis. Microsomal, S9, and cytosol fractions were extracted from 36 histologically normal and 66 NAFLD livers (27 nonalcoholic fatty liver [NAFL], 13 NASH, and 26 NASH with cirrhosis). Corrected microsomal protein per gram liver (MPPGL) progressively decreased with disease severity (26.8, 27.4, and 24.3 mg/g in NAFL, NASH, and NASH/cirrhosis, respectively, compared with 35.6 mg/g in normal livers; ANOVA, P < 0.001). Homogenate, S9, and cytosolic protein showed a consistent trend of decline in NASH/cirrhosis relative to normal control (post-hoc t test, P < 0.05). No differences across the groups were observed in homogenate, S9, cytosolic, and microsomal protein content in matched kidney samples. MPPGL-based scalars that combine protein content with liver size revealed that the reduction in MPPGL in NAFL and NASH was compensated by the reported increase in liver size (relative scalar ratios of 0.96 and 0.99, respectively), which was not the case with NASH/cirrhosis (ratio of 0.63), compared with healthy control. Physiologically based pharmacokinetics-informed global sensitivity analysis of the relative contribution of IVIVE scalars (hepatic CYP3A4 abundance, MPPGL, and liver size) to variability in exposure (area under the curve) to three CYP3A substrates (alprazolam, midazolam, and ibrutinib) revealed enzyme abundance as the most significant parameter, followed by MPPGL, whereas liver volume was the least impactful factor. SIGNIFICANCE STATEMENT: Nonalcoholic fatty liver disease-specific scalars necessary for extrapolation from in vitro systems to liver tissue are lacking. These are required in clearance prediction and dose selection in nonalcoholic fatty liver and steatohepatitis populations. Previously reported disease-driven changes have focused on cirrhosis, with no data on the initial stages of liver disease. The authors obtained experimental values for microsomal, cytosolic, and S9 fractions and assessed the relative impact of microsomal scalars on predicted exposure to substrate drugs using physiologically based pharmacokinetics.

The Effect of Inflammatory Bowel Disease and Irritable Bowel Syndrome on Pravastatin Oral Bioavailability: In vivo and in silico evaluation using bottom-up wbPBPK modeling

The common disorders irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD) can modify the drugs' pharmacokinetics via their induced pathophysiological changes. This work aimed to investigate the impact of these two diseases on pravastatin oral bioavailability. Rat models for IBS and IBD were used to experimentally test the effects of IBS and IBD on pravastatin pharmacokinetics. Then, the observations made in rats were extrapolated to humans using a mechanistic whole-body physiologically-based pharmacokinetic (wbPBPK) model. The rat in vivo studies done herein showed that IBS and IBD decreased serum albumin (> 11% for both), decreased PRV binding in plasma, and increased pravastatin absolute oral bioavailability (0.17 and 0.53 compared to 0.01) which increased plasma, muscle, and liver exposure. However, the wbPBPK model predicted muscle concentration was much lower than the pravastatin toxicity thresholds for myotoxicity and rhabdomyolysis. Overall, IBS and IBD can significantly increase pravastatin oral bioavailability which can be due to a combination of increased pravastatin intestinal permeability and decreased pravastatin gastric degradation resulting in higher exposure. This is the first study in the literature investigating the effects of IBS and IBD on pravastatin pharmacokinetics. The high interpatient variability in pravastatin concentrations as induced by IBD and IBS can be reduced by oral administration of pravastatin using enteric-coated tablets. Such disease (IBS and IBD)-drug interaction can have more drastic consequences for narrow therapeutic index drugs prone to gastric degradation, especially for drugs with low intestinal permeability.

A Comprehensive Physiologically Based Pharmacokinetic Model of Nadolol in Adults with Renal Disease and Pediatrics with Supraventricular Tachycardia

Nadolol is a long-acting non-selective β-adrenergic antagonist that helps treat angina and hypertension. The current study aimed to develop and validate the physiologically based pharmacokinetic model (PBPK) of nadolol in healthy adults, renal-compromised, and pediatric populations. A comprehensive PBPK model was established by utilizing a PK-Sim simulator. After establishing and validating the model in healthy adults, pathophysiological changes i.e., blood flow, hematocrit, and GFR that occur in renal failure were incorporated in the developed model, and the drug exposure was assessed through Box plots. The pediatric model was also developed and evaluated by considering the renal maturation process. The validation of the models was carried out by visual predictive checks, calculating predicted to observed (Rpre/obs) and the average fold error (AFE) of PK parameters i.e., the area under the concentration-time curve (AUC0-t), the maximum concentration in plasma (Cmax), and CL (clearance). The presented PBPK model successfully simulates the nadolol PK in healthy adults, renal-impaired, and pediatric populations, as the Rpre/obs values of all PK parameters fall within the acceptable range. The established PBPK model can be useful in nadolol dose optimization in patients with renal failure and children with supraventricular tachycardia.

Simultaneously Predicting the Pharmacokinetics of CES1-Metabolized Drugs and Their Metabolites Using Physiologically Based Pharmacokinetic Model in Cirrhosis Subjects

Hepatic carboxylesterase 1 (CES1) metabolizes numerous prodrugs into active ingredients or direct-acting drugs into inactive metabolites. We aimed to develop a semi-physiologically based pharmacokinetic (semi-PBPK) model to simultaneously predict the pharmacokinetics of CES1 substrates and their active metabolites in liver cirrhosis (LC) patients. Six prodrugs (enalapril, benazepril, cilazapril, temocapril, perindopril and oseltamivir) and three direct-acting drugs (flumazenil, pethidine and remimazolam) were selected. Parameters such as organ blood flows, plasma-binding protein concentrations, functional liver volume, hepatic enzymatic activity, glomerular filtration rate (GFR) and gastrointestinal transit rate were integrated into the simulation. The pharmacokinetic profiles of these drugs and their active metabolites were simulated for 1000 virtual individuals. The developed semi-PBPK model, after validation in healthy individuals, was extrapolated to LC patients. Most of the observations fell within the 5th and 95th percentiles of simulations from 1000 virtual patients. The estimated AUC and Cmax were within 0.5-2-fold of the observed values. The sensitivity analysis showed that the decreased plasma exposure of active metabolites due to the decreased CES1 was partly attenuated by the decreased GFR. Conclusion: The developed PBPK model successfully predicted the pharmacokinetics of CES1 substrates and their metabolites in healthy individuals and LC patients, facilitating tailored dosing of CES1 substrates in LC patients.

Toward improved predictions of pharmacokinetics of transported drugs in hepatic impairment: Insights from the extended clearance model

Hepatic impairment (HI) moderately (<5-fold) affects the systemic exposure (i.e., area under the plasma concentration-time curve [AUC]) of drugs that are substrates of the hepatic sinusoidal organic anion transporting polypeptide (OATP) transporters and are excreted unchanged in the bile and/or urine. However, the effect of HI on their AUC is much greater (>10-fold) for drugs that are also substrates of cytochrome P450 (CYP) 3A enzymes. Using the extended clearance model, through simulations, we identified the ratio of sinusoidal efflux clearance (CL) over the sum of metabolic and biliary CLs as important in predicting the impact of HI on the AUC of dual OATP/CYP3A substrates. Because HI may reduce hepatic CYP3A-mediated CL to a greater extent than biliary efflux CL, the greater the contribution of the former versus the latter, the greater the impact of HI on drug AUC ratio (AUCRHI ). Using physiologically-based pharmacokinetic modeling and simulation, we predicted relatively well the AUCRHI of OATP substrates that are not significantly metabolized (pitavastatin, rosuvastatin, valsartan, and gadoxetic acid). However, there was a trend toward underprediction of the AUCRHI of the dual OATP/CYP3A4 substrates fimasartan and atorvastatin. These predictions improved when the sinusoidal efflux CL of these two drugs was increased in healthy volunteers (i.e., before incorporating the effect of HI), and by modifying the directionality of its modulation by HI (i.e., increase or decrease). To accurately predict the effect of HI on AUC of hepatobiliary cleared drugs it is important to accurately predict all hepatobiliary pathways, including sinusoidal efflux CL.

Physiologically based pharmacokinetic modeling of candesartan to predict the exposure in hepatic and renal impairment and elderly populations

Background

Candesartan cilexetil is a widely used angiotensin II receptor blocker with minimal adverse effects and high tolerability for the treatment of hypertension. Candesartan is administered orally as the prodrug candesartan cilexetil, which is wholly and swiftly converted to the active metabolite candesartan by carboxylesterase during absorption in the intestinal tract. In populations with renal or hepatic impairment, candesartan's pharmacokinetic (PK) behavior may be altered, necessitating dosage adjustments.

Objectives

This study was conducted to examine how the physiologically based PK (PBPK) model characterizes the PKs of candesartan in adult and geriatric populations and to predict the PKs of candesartan in elderly populations with renal and hepatic impairment.

Design

After developing PBPK models using the reported physicochemical properties of candesartan and clinical data, these models were validated using data from clinical investigations involving various dose ranges.

Methods

Comparing predicted and observed blood concentration data and PK parameters was used to assess the fit performance of the models.

Results

Doses should be reduced to approximately 94% of Chinese healthy adults for the Chinese healthy elderly population; approximately 92%, 68%, and 64% of that of the Chinese healthy adult dose in elderly populations with mild, moderate, and severe renal impairment, respectively; and approximately 72%, 71%, and 52% of that of the Chinese healthy adult dose in elderly populations with Child-Pugh-A, Child-Pugh-B, and Child-Pugh-C hepatic impairment, respectively.

Conclusion

The results suggest that the PBPK model of candesartan can be utilized to optimize dosage regimens for special populations.

A Physiologically Based Pharmacokinetic Model to Predict Systemic Ondansetron Concentration in Liver Cirrhosis Patients

INTRODUCTION

Ondansetron is a drug that is routinely prescribed for the management of nausea and vomiting associated with cancer, radiation therapy, and surgical operations. It is mainly metabolized in the liver, and it might accumulate in patients with hepatic impairment and lead to unwanted adverse events.

METHODS

A physiologically based pharmacokinetic (PBPK) model was developed to predict the exposure of ondansetron in healthy and liver cirrhosis populations. The population-based PBPK simulator PK-Sim was utilized for simulating ondansetron exposure in healthy and liver cirrhosis populations.

RESULTS

The developed model successfully described the pharmacokinetics of ondansetron in healthy and liver cirrhosis populations. The predicted area under the curve, maximum systemic concentration, and clearance were within the allowed twofold range. The exposure of ondansetron in the population of Child-Pugh class C has doubled in comparison to Child-Pugh class A. The dose has to be adjusted for liver cirrhosis patients to ensure comparable exposure to a healthy population.

CONCLUSION

In this study, the developed PBPK model has described the pharmacokinetics of ondansetron successfully. The PBPK model has been successfully evaluated to be used as a tool for dose adjustments in liver cirrhosis patients.

Incorporation and Performance Verification of Hepatic Portal Blood Flow Shunting in Minimal and Full PBPK Models of Liver Cirrhosis

Patho-physiological changes in liver cirrhosis create portacaval shunts that allow blood flow to bypass the hepatic portal vein into the systemic circulation affecting drug pharmacokinetics (PKs). The objectives of this work were to implement a physiologically-based pharmacokinetic (PBPK) framework describing shunted blood flows in virtual patients with differing degrees of liver cirrhosis; and to assess the minimal and full PBPK model's performance using drugs with intermediate to high hepatic extraction. Single dose concentration-time profiles and PK parameters for oral ibrutinib, midazolam, propranolol, and buspirone were simulated in healthy volunteers (HVs) and subjects with cirrhosis (Child-Pugh severity score (CP-A, CP-B, or CP-C)). Model performance was verified by comparing predicted to observed fold-changes in PK parameters between HVs and cirrhotic subjects. The verified model was used to simulate the PK changes for simvastatin in patients with cirrhosis. The predicted area under the curve ratios (AUCCirr :AUCHV ) for ibrutinib were 3.38, 6.87, and 11.46 using the minimal PBPK model with shunt and 1.61, 2.58, and 4.33 without the shunt, these compared with observed values of 4.33, 8.14, and 9.04, respectively. For ibrutinib, propranolol, and buspirone, including a shunt in the PBPK model improved the prediction of the AUCCirr :AUCHV and maximum plasma concentration ratios (CmaxCirr :CmaxHV ). For midazolam, an intermediate extraction drug, the differences were less clear. Simulated simvastatin dose adjustments in cirrhosis suggested that 20 mg in CP-A and 10 mg in CP-B could be used clinically. A mechanistic model-informed understanding of the anatomic and pathophysiology of cirrhosis will facilitate improved dose prediction and adjustment in this vulnerable population.

Physiologically based pharmacokinetic model combined with reverse dose method to study the nephrotoxic tolerance dose of tacrolimus

Nephrotoxicity is the most common side effect that severely limits the clinical application of tacrolimus (TAC), an immunosuppressive agent used in kidney transplant patients. This study aimed to explore the tolerated dose of nephrotoxicity of TAC in individuals with different CYP3A5 genotypes and liver conditions. We established a human whole-body physiological pharmacokinetic (WB-PBPK) model and validated it using data from previous clinical studies. Following the injection of 1 mg/kg TAC into the tail veins of male rats, we developed a rat PBPK model utilizing the drug concentration-time curve obtained by LC-MS/MS. Next, we converted the established rat PBPK model into the human kidney PBPK model. To establish renal concentrations, the BMCL5 of the in vitro CCK-8 toxicity response curve (drug concentration range: 2-80 mol/L) was extrapolated. To further investigate the acceptable levels of nephrotoxicity for several distinct CYP3A5 genotypes and varied hepatic function populations, oral dosing regimens were extrapolated utilizing in vitro-in vivo extrapolation (IVIVE). The PBPK model indicated the tolerated doses of nephrotoxicity were 0.14-0.185 mg/kg (CYP3A5 expressors) and 0.13-0.155 mg/kg (CYP3A5 non-expressors) in normal healthy subjects and 0.07-0.09 mg/kg (CYP3A5 expressors) and 0.06-0.08 mg/kg (CYP3A5 non-expressors) in patients with mild hepatic insufficiency. Further, patients with moderate hepatic insufficiency tolerated doses of 0.045-0.06 mg/kg (CYP3A5 expressors) and 0.04-0.05 mg/kg (CYP3A5 non-expressors), while in patients with moderate hepatic insufficiency, doses of 0.028-0.04 mg/kg (CYP3A5 expressors) and 0.022-0.03 mg/kg (CYP3A5 non-expressors) were tolerated. Overall, our study highlights the combined usage of the PBPK model and the IVIVE approach as a valuable tool for predicting toxicity tolerated doses of a drug in a specific group.

The Activity of Members of the UDP-Glucuronosyltransferase Subfamilies UGT1A and UGT2B is Impaired in Patients with Liver Cirrhosis

BACKGROUND AND OBJECTIVE

The impact of liver cirrhosis on the activity of UDP-glucuronosyltransferases (UGTs) is currently not well characterized. We investigated the glucuronidation capacity and glucuronide accumulation in patients with liver cirrhosis.

METHODS

We administered the Basel phenotyping cocktail (caffeine, efavirenz, flurbiprofen, omeprazole, metoprolol, midazolam) to patients with liver cirrhosis (n = 16 Child A, n = 15 Child B, n = 5 Child C) and n = 12 control subjects and obtained pharmacokinetic profiles of substrates and primary metabolites and their glucuronides.

RESULTS

Caffeine and its metabolite paraxanthine were only slightly glucuronidated. The metabolic ratio (AUCglucuronide/AUCparent, MR) was not affected for caffeine but decreased by 60% for paraxanthine glucuronide formation in Child C patients. Efavirenz was not glucuronidated whereas 8-hydroxyefavirenz was efficiently glucuronidated. The MR of 8-hydroxyefavirenz-glucuronide formation increased three-fold in Child C patients and was negatively correlated with the glomerular filtration rate. Flurbiprofen and omeprazole were not glucuronidated. 4-Hydroxyflurbiprofen and 5-hydroxyomeprazole were both glucuronidated but the corresponding MRs for glucuronide formation were not affected by liver cirrhosis. Metoprolol, but not α-hydroxymetoprolol, was glucuronidated, and the MR for metoprolol-glucuronide formation dropped by 60% in Child C patients. Both midazolam and its metabolite 1'-hydroxymidazolam underwent glucuronidation, and the corresponding MRs for glucuronide formation dropped by approximately 80% in Child C patients. No relevant glucuronide accumulation occurred in patients with liver cirrhosis.

CONCLUSIONS

Detailed analysis revealed that liver cirrhosis may affect the activity of UGTs of the UGT1A and UGT2B subfamilies according to liver function. Clinically significant glucuronide accumulation did not occur in the population investigated.

CLINICAL TRIAL REGISTRATION

NCT03337945.

Physiologically based pharmacokinetic modeling (PBPK) to predict drug-drug interactions for encorafenib. Part II. Prospective predictions in hepatic and renal impaired populations with clinical inhibitors and inducers

Encorafenib, a potent BRAF kinase inhibitor gets significantly metabolised by CYP3A4 (83%) and CYP2C19 (16%) and is a substrate for P-glycoprotein (P-gp). Due to significant metabolism by CYP3A4, encorafenib exposure can increase in hepatic and renal impairment and may lead to altered magnitude of drug-drug interactions (DDI). Hence, it is necessary to assess the exposures & DDI's in impaired population.Physiologically based pharmacokinetic modelling (PBPK) was utilised to determine the exposures of encorafenib in hepatic and renal impairment along with altered DDI's. Prospective DDI's were predicted with USFDA recommended clinical CYP3A4, CYP2C19, P-gp inhibitors and CYP3A4 inducers.PBPK models for encorafenib, perpetrators simulated PK parameters within 2-folds error. Encorafenib exposures significantly increased in hepatic as compared to renal impairment because of reduced CYP3A4 levels.Hepatic impairment caused changes in inhibition and induction DDI's, when compared to healthy population. Renal impairment did not cause significant changes in DDIs except for itraconazole. P-gp, CYP2C19 inhibitors did not result in altered DDI's. The DDI's were found to have insignificant correlation with relative exposure increase of perpetrators in case of impairment. Overall, this work signifies use of PBPK modelling for DDI's evaluations in hepatic and renal impairment populations.

Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach

Hydroxychloroquine (HCQ), a congener of chloroquine, is widely used in prophylaxis and the treatment of malaria, and also as a cure for rheumatoid arthritis, systemic lupus erythematosus, and various other diseases. Physiologically based pharmacokinetic modeling (PBPK) has attracted great interest in the past few years in predicting drug pharmacokinetics (PK). This study focuses on predicting the PK of HCQ in the healthy population and extrapolating it to the diseased populations, i.e., liver cirrhosis and chronic kidney disease (CKD), utilizing a systematically built whole-body PBPK model. The time vs. concentration profiles and drug-related parameters were obtained from the literature after a laborious search and in turn were integrated into PK-Sim software for designing healthy intravenous, oral, and diseased models. The model's evaluation was performed using observed-to-predicted ratios (Robs/Rpre) and visual predictive checks within a 2-fold error range. The healthy model was then extrapolated to liver cirrhosis and CKD populations after incorporating various disease-specific pathophysiological changes. Box-whisker plots showed an increase in AUC_0-t in liver cirrhosis, whereas a decrease in AUC_0-t was seen in the CKD population. These model predictions may assist clinicians in adjusting the administered HCQ doses in patients with different degrees of hepatic and renal impairment.

Physiologically Based Pharmacokinetic Modelling to Predict Pharmacokinetics of Enavogliflozin, a Sodium-Dependent Glucose Transporter 2 Inhibitor, in Humans

Enavogliflozin is a sodium-dependent glucose cotransporter 2 (SGLT2) inhibitor approved for clinical use in South Korea. As SGLT2 inhibitors are a treatment option for patients with diabetes, enavogliflozin is expected to be prescribed in various populations. Physiologically based pharmacokinetic (PBPK) modelling can rationally predict the concentration–time profiles under altered physiological conditions. In previous studies, one of the metabolites (M1) appeared to have a metabolic ratio between 0.20 and 0.25. In this study, PBPK models for enavogliflozin and M1 were developed using published clinical trial data. The PBPK model for enavogliflozin incorporated a non-linear urinary excretion in a mechanistically arranged kidney model and a non-linear formation of M1 in the liver. The PBPK model was evaluated, and the simulated pharmacokinetic characteristics were in a two-fold range from those of the observations. The pharmacokinetic parameters of enavogliflozin were predicted using the PBPK model under pathophysiological conditions. PBPK models for enavogliflozin and M1 were developed and validated, and they seemed useful for logical prediction.

Blood coagulation factors and platelet response to drug-induced hepatitis and hepatosis in rats

BACKGROUND

Knowing the variability of blood coagulation responses to liver damage of different origins can provide a key to curing liver tissues or to mitigating treatment side effects. The aim of the present work was to compare the changes in the main components of hemostasis under experimental drug-induced hepatosis and hepatitis in rats.

METHODS

We modeled diclofenac-induced hepatitis and tetracycline-induced hepatosis. Hemostasis response was gauged by measuring fibrinogen, factor X, protein C (PC), and prothrombin in plasma. The decarboxylated form of prothrombin was detected by measuring prothrombin index and ecamulin index. Platelet reactivity was studied using aggregometry.

RESULTS

Both hepatitis and hepatosis decreased the synthesis of fibrinogen, factor X, and prothrombin. However, protein carboxylation was not disrupted in hepatosis but was much impaired in hepatitis. PC decreased in both models as a consequence of its consumption possibly during inflammatory response. Platelet aggregation rate was lower in hepatosis but higher in hepatitis.

CONCLUSIONS

Our findings imply the need for a thorough monitoring of the hemostasis system in liver diseases to avoid possible thrombotic complications. Its state indicates the disorder's rate and character.

Predicting changes in the pharmacokinetics of CYP3A-metabolized drugs in hepatic impairment and insights into factors driving these changes

Physiologically based pharmacokinetic models, populated with drug-metabolizing enzyme and transporter (DMET) abundance, can be used to predict the impact of hepatic impairment (HI) on the pharmacokinetics (PK) of drugs. To increase confidence in the predictive power of such models, they must be validated by comparing the predicted and observed PK of drugs in HI obtained by phenotyping (or probe drug) studies. Therefore, we first predicted the effect of all stages of HI (mild to severe) on the PK of drugs primarily metabolized by cytochrome P450 (CYP) 3A enzymes using the default HI module of Simcyp Version 21, populated with hepatic and intestinal CYP3A abundance data. Then, we validated the predictions using CYP3A probe drug phenotyping studies conducted in HI. Seven CYP3A substrates, metabolized primarily via CYP3A (fraction metabolized, 0.7-0.95), with low to high hepatic availability, were studied. For all stages of HI, the predicted PK parameters of drugs were within twofold of the observed data. This successful validation increases confidence in using the DMET abundance data in HI to predict the changes in the PK of drugs cleared by DMET for which phenotyping studies in HI are not available or cannot be conducted. In addition, using CYP3A drugs as an example, through simulations, we identified the salient PK factors that drive the major changes in exposure (area under the plasma concentration-time profile curve) to drugs in HI. This theoretical framework can be applied to any drug and DMET to quickly determine the likely magnitude of change in drug PK due to HI.

Torsemide Pharmacometrics in Healthy Adult Populations Including CYP2C9 Genetic Polymorphisms and Various Patient Groups through Physiologically Based Pharmacokinetic-Pharmacodynamic Modeling

Torsemide is a widely used diuretic in clinical practice. In this study, pharmacokinetic (PK) and pharmacodynamic (PD) simulations of torsemide for various population groups and exposure scenarios were performed through human-scale physiologically-based PK-PD (PBPK-PD) modeling of torsemide. For PBPK-PD modeling of torsemide, invitro and clinical data of torsemide reported previously were used. After exposure to clinical doses of torsemide, observed plasma (or serum) concentration and urine torsemide excretion profiles were used as PK-data, and observed urinary sodium excretion rate was used as PD-data. The model was then extended to take into account physiological and biochemical factors according to different CYP2C9 phenotypes or patient populations. The established model captured various torsemide clinical results well. Differences in torsemide PKs and PDs between patient groups or CYP2C9 genetic polymorphisms were modelologically identified. It was confirmed that degrees of differences in torsemide PKs and PDs by disease groups were greater than those according to different CYP2C9 phenotypes. According to torsemide administration frequency or dose change, it was confirmed that although the difference in plasma PKs between groups (healthy adult and patient groups) could increase to 14.80 times, the difference in PDs was reduced to 1.01 times. Results of this study suggested that it is very important to consider disease groups in the setting of torsemide clinical therapy and that it is difficult to predict PD proportionally with only differences in PKs of torsemide between population groups. The PBPK-PD model established in this study is expected to be utilized for various clinical cases involving torsemide application in the future, enabling optimal drug therapy.

Development and Evaluation of a Physiologically Based Pharmacokinetic Model of Labetalol in Healthy and Diseased Populations

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.

Physiologically Based Pharmacokinetic (PBPK) Modeling of Lornoxicam: Exploration of doses for CYP2C9 Genotypes and Patients with Cirrhosis

Lornoxicam physiologically based pharmacokinetic (PBPK) models were developed and validated on the basis of clinical pharmacokinetic results obtained by considering CYP2C9 genetic polymorphisms in healthy adult populations. PBPK models were extended to predict lornoxicam pharmacokinetics for patients with cirrhosis by quantitatively examining the pathophysiological information associated with cirrhosis. The predicted plasma exposure to lornoxicam was approximately 1.12-2.83 times higher in the CYP2C9*1/*3 and *1/*13 groups than in the CYP2C9*1/*1 group of healthy adult populations and patients with cirrhosis. The predicted plasma exposure to lornoxicam was approximately 1.28-3.61 times higher in patients with cirrhosis than in healthy adult populations. If the relationship between lornoxicam exposure in plasma and drug efficacy was proportional, then the proposed adjusted doses of lornoxicam for each group varied from 1.25 mg to 8 mg. As the severity of cirrhosis increased, or when the CYP2C9 genotype was *1 heterozygous, the dose adjustment range of lornoxicam increased. Therefore, the effect of pathophysiological factors (cirrhosis severity) on the pharmacokinetics of lornoxicam might be more important than that of CYP2C9 genetic factors. These results could be useful for broadening the scope of clinical application of lornoxicam by enabling dose selection based on CYP2C9 genotypes and liver cirrhosis degree.

Design and conduct considerations for studies in patients with hepatic impairment

Despite the liver being the primary site for clearance of xenobiotics utilizing a myriad of mechanisms ranging from cytochrome P450 enzyme pathways, glucuronidation, and biliary excretion, there is a dearth of information available as to how the severity of hepatic impairment (HI) can alter drug absorption and disposition (i.e., pharmacokinetics [PK]) as well as their efficacy and safety or pharmacodynamics (PD). In general, regulatory agencies recommend conducting PK studies in subjects with HI when hepatic metabolism/excretion accounts for more than 20% of drug elimination or if the drug has a narrow therapeutic range. In this tutorial, we provide an overview of the global regulatory landscape, clinical measures for hepatic function assessment, methods to stage HI severity, and consequently the impact on labeling. In addition, we provide an in-depth practical guidance for designing and conducting clinical trials for patients with HI and on the application of modeling and simulation strategies in lieu of dedicated trials for dosing recommendations in patients with HI.

A review on the clinical pharmacokinetics of hydralazine

INTRODUCTION

Hydralazine is a vasodilator used to treat hypertension, pre-eclampsia, and heart failure. The current article reviews the clinical pharmacokinetics (PK) of hydralazine, which can be useful for clinicians in optimizing its dose and dosing frequency to avoid adverse effects and unexpected interactions that could risk patients' lives.

AREAS COVERED

This review has summarized the PK parameters for hydralazine after performing an extensive literature search. It includes 20 publications that were selected after applying eligibility criteria out of a pool of literature that was searched using Google Scholar, PubMed, Cochrane Central, and EBSCO databases. The included studies consisted of concentration vs. time profiles of hydralazine. If the PK data were not tabulated in the given study, the concentration vs. time profiles were scanned for the extraction of the PK data. The PK parameters were calculated by applying a non-compartmental analysis (NCA).

EXPERT OPINION

The current review will aid clinicians in understanding hydralazine PK in different disease populations. This clinical PK data might also be helpful in the development of a pharmacokinetic model of hydralazine.

Prediction for optimal dosage of pazopanib under various clinical situations using physiologically based pharmacokinetic modeling

This study aimed to apply a physiologically based pharmacokinetic (PBPK) model to predict optimal dosing regimens of pazopanib (PAZ) for safe and effective administration when co-administered with CYP3A4 inhibitors, acid-reducing agents, food, and administered in patients with hepatic impairment. Here, we have successfully developed the population PBPK model and the predicted PK variables by this model matched well with the clinically observed data. Most ratios of prediction to observation were between 0.5 and 2.0. Suitable dosage modifications of PAZ have been identified using the PBPK simulations in various situations, i.e., 200 mg once daily (OD) or 100 mg twice daily (BID) when co-administered with the two CYP3A4 inhibitors, 200 mg BID when simultaneously administered with food or 800 mg OD when avoiding food uptake simultaneously. Additionally, the PBPK model also suggested that dosing does not need to be adjusted when co-administered with esomeprazole and administration in patients with wild hepatic impairment. Furthermore, the PBPK model also suggested that PAZ is not recommended to be administered in patients with severe hepatic impairment. In summary, the present PBPK model can determine the optimal dosing adjustment recommendations in multiple clinical uses, which cannot be achieved by only focusing on AUC linear change of PK.

Clinical pharmacokinetics of nadolol: A systematic review

WHAT IS KNOWN AND OBJECTIVE

Nadolol is a non-selective beta-adrenergic antagonist that is used for the treatment of hypertension and angina. The primary route for its administration is oral. It is given once daily as it has a longer half-life (t½). The purpose of conducting this systematic review is to provide a comprehensive view of all the available pharmacokinetic (PK) data on nadolol in humans. This review aimed to systematically collate and analyze publish data on the clinical PK of nadolol in humans and this can be beneficial for the clinicians in dosage adjustments.

METHODS

Two electronic databases PubMed and Google Scholar were used for conducting a systematic literature search. All the relevant articles containing PK data of nadolol in humans were retrieved. A total of 1275 articles were searched from both databases and after applying eligibility criteria finally, 22 articles were included for conducting the systematic review.

RESULTS AND DISCUSSION

The area under the plasma concentration curve (AUC) and maximum plasma concentration (C_max ) of nadolol increased in a dose-dependent manner. The t½ of nadolol was increased to double (18.2-68.6 h) in the patients with chronic kidney disease while the serum t½ became shorter (3.2-4.3 h) when administered to the children. The bioavailability of nadolol was greatly reduced by the coadministration of green tea. Nadolol can be effectively removed by hemodialysis. It undergoes enterohepatic circulation thus activated charcoal decreased its bioavailability.

WHAT IS NEW AND CONCLUSION

Since, there is no previous report of a systematic review on the PK of nadolol, the current review encompasses all the relevant published articles on nadolol in humans. The analysis and understanding of PK parameters (AUC, C_max , and t½) of nadolol may be helpful in the development and evaluation of PK models.

Altered intravenous drug disposition in people living with cystic fibrosis: A meta‐analysis integrating top‐down and bottom‐up data

Cystic fibrosis (CF) has been linked to altered drug disposition in various studies. However, the magnitude of these changes, influencing factors, and underlying mechanisms remain a matter of debate. The primary aim of this work was therefore to quantify changes in drug disposition (top‐down) and the pathophysiological parameters known to affect pharmacokinetics (PKs; bottom‐up). This was done through meta‐analyses and meta‐regressions in addition to theoretical PK simulations. Volumes of distribution and clearances were found to be elevated in people living with CF. These increases were larger in studies which included patients with pulmonary exacerbations. Differences in clearance were smaller in more recent studies and when results were normalized to body surface area or lean body mass instead of body weight. For the physiological parameters investigated, measured glomerular filtration rate and serum cytokine concentrations were found to be elevated in people living with CF, whereas serum albumin and creatinine levels were decreased. Possible pathophysiological mechanisms for these alterations relate to renal hyperfiltration, increases in free fraction, and inflammation. No differences were detected for cardiac output, body fat, fat free mass, hematocrit, creatinine clearance, and the activity of drug metabolizing enzymes. These findings imply that, in general, lower total plasma concentrations of drugs can be expected in people living with CF, especially when pulmonary exacerbations are present. Given the potential effect of CF on plasma protein binding and the variability in outcome observed between studies, the clinical relevance of adapting existing dosage regimens should be evaluated on a case‐by‐case basis.

Cytochrome P450 enzymes in the pediatric population: Connecting knowledge on P450 expression with pediatric pharmacokinetics

Cytochrome P450 enzymes play an important role in the pharmacokinetics, efficacy, and toxicity of drugs. Age-dependent changes in P450 enzyme expression have been studied based on several detection systems, as well as by deconvolution of in vivo pharmacokinetic data observed in pediatric populations. The age-dependent changes in P450 enzyme expression can be important determinants of drug disposition in childhood, in addition to the changes in body size and the other physiological parameters, and effects of pharmacogenetics and disease on organ functions. As a tool incorporating drug-specific and body-specific factors, physiologically-based pharmacokinetic (PBPK) models have become increasingly used to characterize and explore mechanistic insights into drug disposition. Thus, PBPK models can be a bridge between findings from basic science and utilization in predictive science. Pediatric PBPK models incorporate additional system specific information on developmental physiology and ontogeny and have been used to predict pharmacokinetic parameters from preterm neonates onwards. These models have been advocated by regulatory authorities in order to support pediatric clinical trials. The purpose of this chapter is to highlight accumulated knowledge and findings from basic research focusing on P450 enzymes, as well as the current status and future challenges of expanding the utilization of pediatric PBPK modeling.

Liver Cirrhosis Affects the Pharmacokinetics of the Six Substrates of the Basel Phenotyping Cocktail Differently

BACKGROUND

Activities of hepatic cytochrome P450 enzymes (CYPs) are relevant for hepatic clearance of drugs and known to be decreased in patients with liver cirrhosis. Several studies have reported the effect of liver cirrhosis on CYP activity, but the results are partially conflicting and for some CYPs lacking.

OBJECTIVE

In this study, we aimed to investigate the CYP activity in patients with liver cirrhosis with different Child stages (A-C) using the Basel phenotyping cocktail approach.

METHODS

We assessed the pharmacokinetics of the six compounds and their CYP-specific metabolites of the Basel phenotyping cocktail (CYP1A2: caffeine, CYP2B6: efavirenz, CYP2C9: flurbiprofen, CYP2C19: omeprazole, CYP2D6: metoprolol, CYP3A: midazolam) in patients with liver cirrhosis (n = 16 Child A cirrhosis, n = 15 Child B cirrhosis, n = 5 Child C cirrhosis) and matched control subjects (n = 12).

RESULTS

While liver cirrhosis only marginally affected the pharmacokinetics of the low to moderate extraction drugs efavirenz and flurbiprofen, the elimination rate of caffeine was reduced by 51% in patients with Child C cirrhosis. For the moderate to high extraction drugs omeprazole, metoprolol, and midazolam, liver cirrhosis decreased the elimination rate by 75%, 37%, and 60%, respectively, increased exposure, and decreased the apparent systemic clearance (clearance/bioavailability). In patients with Child C cirrhosis, the metabolic ratio (ratio of the area under the plasma concentration-time curve from 0 to 24 h of the metabolite to the parent compound), a marker for CYP activity, decreased by 66%, 47%, 92%, 73%, and 43% for paraxanthine/caffeine (CYP1A2), 8-hydroxyefavirenz/efavirenz (CYP2B6), 5-hydroxyomeprazole/omeprazole (CYP2C19), α-hydroxymetoprolol/metoprolol (CYP2D6), and 1'-hydroxymidazolam/midazolam (CYP3A), respectively. In comparison, the metabolic ratio 4-hydroxyflurbiprofen/flurbiprofen (CYP2C9) remained unchanged.

CONCLUSIONS

Liver cirrhosis affects the activity of CYP isoforms differently. This variability must be considered for dose adjustment of drugs in patients with liver cirrhosis.

CLINICAL TRIAL REGISTRATION

NCT03337945.

Physiologically based pharmacokinetic combined BTK occupancy modeling for optimal dosing regimen prediction of acalabrutinib in patients alone, with different CYP3A4 variants, co-administered with CYP3A4 modulators and with hepatic impairment

PURPOSE

To develop a mathematical model combined between physiologically based pharmacokinetic and BTK occupancy (PBPK-BO) to simultaneously predict pharmacokinetic (PK) and pharmacodynamic (PD) changes of acalabrutinib (ACA) and active metabolite ACP-5862 in healthy humans as well as PD in patients. Next, to use the PBPK-BO to determine the optimal dosing regimens in patients alone, with different CYP3A4 variants, when co-administration with four CYP3A4 modulators and in patients with hepatic impairment, respectively.

METHODS

The PBPK-BO model was built using physicochemical and biochemical properties of ACA and ACP-5862 and then verified by observed PK and PD data from healthy humans and patients. Finally, the model was applied to determine optimal dosing regimens in various clinical situations.

RESULTS

The simulations demonstrated that 100 mg ACA twice daily (BID) was the optimal dosing regimen in patients alone. Additionally, dosage regimens might be reduced to 50 mg BID in patients with five CYP3A4 variants. Moreover, the dosing regimen should be modified to 100 mg (even to 50 mg) once daily (QD) when co-administration with erythromycin or clarithromycin, and be increased to 200 mg BID with rifampicin, and but be avoided co-administration with itraconazole. Furthermore, dosage regimen simulations showed that optimal dosing might be decreased to 50 mg BID in patients with mild and moderate hepatic impairment, and be avoided taking ACA in severely hepatically impaired patients.

CONCLUSION

This PBPK-BO model can predict PK and PD in healthy humans and patients and also predict the optimal dosing regimens in various clinical situations.

Enhancing Atorvastatin In Vivo Oral Bioavailability in the Presence of Inflammatory Bowel Disease and Irritable Bowel Syndrome Using Supercritical Fluid Technology Guided by wbPBPK Modeling in Rat and Human

Inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) are common disorders that can change the body's physiology and drugs pharmacokinetics. Solid dispersion (SD) preparation using supercritical fluid technology (SFT) has many advantages. Our study aimed to explore the effect of IBS and IBD on atorvastatin (ATV) pharmacokinetics, enhance ATV oral bioavailability (BCS II drug) using SFT, and analyze drug-disease-formulation interaction using a whole-body physiologically based pharmacokinetic (wbPBPK) model in rat and human. A novel ATV formulation was prepared using SFT and characterized in vitro and in vivo in healthy, IBS, and IBD rats. The resulting ATV plasma levels were analyzed using a combination of conventional and wbPBPK approaches. The novel formulation increased ATV solubility by 20-fold and resulted in a zero-order release of up to 95%. Both IBS and IBD increased ATV exposure after oral and intravenous administration by more than 30%. The novel SFT formulation increased ATV bioavailability by 28, 14, and 18% in control, IBD, and IBD rat groups and resulted in more consistent exposure as compared to raw ATV solution. Higher improvements in ATV bioavailability of more than 2-fold upon receiving the novel SFT formulation were predicted by the human wbPBPK model as compared to receiving the conventional tablets. Finally, the established wbPBPK model could describe ATV ADME in the presence of IBS and IBD after oral administration of raw ATV and using the novel SFT formula and can help scale the optimized ATV dosing regimens in the presence of IBS and IBD from rats to humans.

Applications, Challenges, and Outlook for PBPK Modeling and Simulation: A Regulatory, Industrial and Academic Perspective

Several regulatory guidances on the use of physiologically based pharmacokinetic (PBPK) analyses and physiologically based biopharmaceutics model(s) (PBBM(s)) have been issued. Workshops are routinely held, demonstrating substantial interest in applying these modeling approaches to address scientific questions in drug development. PBPK models and PBBMs have remarkably contributed to model-informed drug development (MIDD) such as anticipating clinical PK outcomes affected by extrinsic and intrinsic factors in general and specific populations. In this review, we proposed practical considerations for a "base" PBPK model construction and development, summarized current status, challenges including model validation and gaps in system models, and future perspectives in PBPK evaluation to assess a) drug metabolizing enzyme(s)- or drug transporter(s)- mediated drug-drug interactions b) dosing regimen prediction, sampling timepoint selection and dose validation in pediatric patients from newborns to adolescents, c) drug exposure in patients with renal and/or and hepatic organ impairment, d) maternal-fetal drug disposition during pregnancy, and e) pH-mediated drug-drug interactions in patients treated with proton pump inhibitors/acid-reducing agents (PPIs/ARAs) intended for gastric protection. Since PBPK can simulate outcomes in clinical studies with enrollment challenges or ethical issues, the impact of PBPK models on waivers and how to strengthen study waiver is discussed.

Effects of Hepatic Impairment on the Pharmacokinetic Profile and Safety of Lobeglitazone

In this open-label, single-dose, parallel-group study, we compared the pharmacokinetic profile and safety of lobeglitazone, a thiazolidinedione acting as an agonist for peroxisome proliferator-activated receptors, in patients with hepatic impairment (HI) and healthy matched controls for age, sex, and body weight. After a single oral dose of lobeglitazone (0.5 mg), the lobeglitazone (parent drug) and M7 (major metabolite) plasma concentrations and pharmacokinetic parameters were analyzed and compared between the HI patient groups and healthy matched control groups. The geometric mean ratio (GMR; 90% confidence interval [CI]) for maximum concentration (Cmax ) and area under the plasma concentration-time curve from time 0 extrapolated to infinity (AUCinf ) of lobeglitazone was 1.06 (0.90-1.24) and 1.07 (0.82-1.40), respectively, for mild HI vs control A. The GMR (90%CI) of Cmax and AUCinf was 0.70 (0.56-0.88) and 1.00 (0.72-1.37), respectively, for moderate HI vs control B. For M7, the GMR (90%CI) of Cmax and AUCinf was 1.09 (0.75-1.57) and 1.18 (0.71-1.97), respectively, for mild HI vs control A and 1.50 (0.95-2.38) and 1.79 (1.06-3.04), respectively, for moderate HI vs control B. Notable adverse events or tolerability issues were not observed. Lobeglitazone may be safely used in patients with mild or moderate HI without dose adjustment.

Physiologically-Based Pharmacokinetic Modeling Approaches for Patients with SARS-CoV-2 Infection: A Case Study with Imatinib

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection, which causes coronavirus disease 2019 (COVID‐19), manifests as mild respiratory symptoms to severe respiratory failure and is associated with inflammation and other physiological changes. Of note, substantial increases in plasma concentrations of α₁‐acid‐glycoprotein and interleukin‐6 have been observed among patients admitted to the hospital with advanced SARS‐CoV‐2 infection. A physiologically based pharmacokinetic (PBPK) approach is a useful tool to evaluate and predict disease‐related changes on drug pharmacokinetics. A PBPK model of imatinib has previously been developed and verified in healthy people and patients with cancer. In this study, the PBPK model of imatinib was successfully extrapolated to patients with SARS‐CoV‐2 infection by accounting for disease‐related changes in plasma α₁‐acid‐glycoprotein concentrations and the potential drug interaction between imatinib and dexamethasone. The model demonstrated a good predictive performance in describing total and unbound imatinib concentrations in patients with SARS‐CoV‐2 infection. PBPK simulations highlight that an equivalent dose of imatinib may lead to substantially higher total drug concentrations in patients with SARS‐CoV‐2 infection compared to that in patients with cancer, while the unbound concentrations remain comparable between the 2 patient populations. This supports the notion that unbound trough concentration is a better exposure metric for dose adjustment of imatinib in patients with SARS‐CoV‐2 infection, compared to the corresponding total drug concentration. Potential strategies for refinement and generalization of the PBPK modeling approach in the patient population with SARS‐CoV‐2 are also provided in this article, which could be used to guide study design and inform dose adjustment in the future.

PBPK Modelling of Dexamethasone in Patients With COVID-19 and Liver Disease

The aim of the study was to apply Physiologically-Based Pharmacokinetic (PBPK) modelling to predict the effect of liver disease (LD) on the pharmacokinetics (PK) of dexamethasone (DEX) in the treatment of COVID-19. A whole-body PBPK model was created to simulate 100 adult individuals aged 18–60 years. Physiological changes (e.g., plasma protein concentration, liver size, CP450 expression, hepatic blood flow) and portal vein shunt were incorporated into the LD model. The changes were implemented by using the Child-Pugh (CP) classification system. DEX was qualified using clinical data in healthy adults for both oral (PO) and intravenous (IV) administrations and similarly propranolol (PRO) and midazolam (MDZ) were qualified with PO and IV clinical data in healthy and LD adults. The qualified model was subsequently used to simulate a 6 mg PO and 20 mg IV dose of DEX in patients with varying degrees of LD, with and without shunting. The PBPK model was successfully qualified across DEX, MDZ and PRO. In contrast to healthy adults, the simulated systemic clearance of DEX decreased (35%–60%) and the plasma concentrations increased (170%–400%) in patients with LD. Moreover, at higher doses of DEX, the AUC ratio between healthy/LD individuals remained comparable to lower doses. The exposure of DEX in different stages of LD was predicted through PBPK modelling, providing a rational framework to predict PK in complex clinical scenarios related to COVID-19. Model simulations suggest dose adjustments of DEX in LD patients are not necessary considering the low dose administered in the COVID-19 protocol.

Drug-Drug Interactions in People Living with HIV at Risk of Hepatic and Renal Impairment: Current Status and Future Perspectives

Despite the advancement of antiretroviral therapy (ART) for the treatment of human immunodeficiency virus (HIV), drug–drug interactions (DDIs) remain a relevant clinical issue for people living with HIV receiving ART. Antiretroviral (ARV) drugs can be victims and perpetrators of DDIs, and a detailed investigation during drug discovery and development is required to determine whether dose adjustments are necessary or coadministrations are contraindicated. Maintaining therapeutic ARV plasma concentrations is essential for successful ART, and changes resulting from potential DDIs could lead to toxicity, treatment failure, or the emergence of ARV‐resistant HIV. The challenges surrounding DDI management are complex in special populations of people living with HIV, and often lack evidence‐based guidance as a result of their underrepresentation in clinical investigations. Specifically, the prevalence of hepatic and renal impairment in people living with HIV are between five and 10 times greater than in people who are HIV‐negative, with each condition constituting approximately 15% of non‐AIDS‐related mortality. Therapeutic strategies tend to revolve around the treatment of risk factors that lead to hepatic and renal impairment, such as hepatitis C, hepatitis B, hypertension, hyperlipidemia, and diabetes. These strategies result in a diverse range of potential DDIs with ART. The purpose of this review was 2‐fold. First, to summarize current pharmacokinetic DDIs and their mechanisms between ARVs and co‐medications used for the prevention and treatment of hepatic and renal impairment in people living with HIV. Second, to identify existing knowledge gaps surrounding DDIs related to these special populations and suggest areas and techniques to focus upon in future research efforts.

Physiologically based pharmacokinetic (PBPK) modelling of tamsulosin related to CYP2D6*10 allele

Tamsulosin, a selective [Formula: see text]-adrenoceptor blocker, is commonly used for alleviation of lower urinary tract symptoms related to benign prostatic hyperplasia. Tamsulosin is predominantly metabolized by CYP3A4 and CYP2D6 enzymes, and several studies reported the effects of CYP2D6 genetic polymorphism on the pharmacokinetics of tamsulosin. This study aims to develop and validate the physiologically based pharmacokinetic (PBPK) model of tamsulosin in CYP2D6*wt/*wt, CYP2D6*wt/*10, and CYP2D6*10/*10 genotypes, using Simcyp® simulator. Physicochemical, and formulation properties and data for absorption, distribution, metabolism and excretion were collected from previous publications, predicted in the simulator, or optimized in different CYP2D6 genotypes. The tamsulosin PBPK model in CYP2D6*wt/*wt and CYP2D6*wt/*10 genotypes were developed based on the clinical pharmacokinetic study where a single oral dose of 0.2 mg tamsulosin was administered to 25 healthy Korean male volunteers with CYP2D6*wt/*wt and CYP2D6*wt/*10 genotypes. A previous pharmacokinetic study was used to develop the model in CYP2D6*10/*10 genotype. The developed model was validated using other clinical pharmacokinetic studies not used in development. The predicted exposures via the PBPK model in CYP2D6*wt/*10 and CYP2D6*10/*10 genotype was 1.23- and 1.76-fold higher than CYP2D6*wt/*wt genotype, respectively. The simulation profiles were visually similar to the observed profiles, and fold errors of all development and validation datasets were included within the criteria. Therefore, the tamsulosin PBPK model in different CYP2D6 genotypes with regards to CYP2D6*10 alleles was appropriately established. Our model can contribute to the implementation of personalized pharmacotherapy of patients, appropriately predicting the pharmacokinetics of tamsulosin reflecting their demographic and CYP2D6 genotype characteristics without unnecessary drug exposure.