Development and Evaluation of a Physiologically Based Pharmacokinetic Drug-Disease Model of Propranolol for Suggesting Model Informed Dosing in Liver Cirrhosis Patients

Physiologically Based Pharmacokinetic Modeling of Lacosamide in Patients With Hepatic and Renal Impairment and Pediatric Populations to Support Pediatric Dosing Optimization

PURPOSE

Lacosamide (LCM) is a new-generation anti-seizure medication that is efficacious in patients with focal seizures with or without secondary generalization. Until now, the efficacy, safety, and tolerability of LCM are still lacking in Chinese epilepsy patients, particularly for pediatric populations and patients with renal or hepatic impairment.

METHODS

This study was conducted to develop a physiologically based pharmacokinetic (PBPK) model to characterize the pharmacokinetics of LCM in Chinese populations and predict the pharmacokinetics of LCM in Chinese pediatric populations and patients with renal or hepatic impairment. Using data from clinical investigations, the developed PBPK model was validated by comparing predicted and observed blood concentration data.

FINDINGS

Doses should be reduced to approximately 82%, 75%, 63%, and 76% of the Chinese healthy adult dose in patients with mild, moderate, and severe renal impairment and end-stage renal disease; and approximately 89%, 72%, and 36% of the Chinese healthy adult dose in patients with Child Pugh-A, B, and C hepatic impairment. For pediatric populations, intravenous doses should be adjusted to 1.75 mg/kg for newborns, 2.5 mg/kg for toddlers, 2.2 mg/kg mg for preschool and school age, and 2 mg/kg mg for adolescents to achieve an equivalent plasma exposure of 2 mg/kg LCM in adults. The oral doses should be adjusted to 20 mg for toddlers, 32 mg for preschool, 45 mg for school age, and 95 mg for adolescents to achieve an approximately equivalent plasma exposure of 100 mg LCM in adults.

IMPLICATIONS

The PBPK model of LCM can be utilized to optimize dosage regimens for special populations.

Physiologically based pharmacokinetic modeling of apixaban to predict exposure in populations with hepatic and renal impairment and elderly populations

BACKGROUND

Apixaban is a factor Xa inhibitor with a limited therapeutic index that belongs to the family of oral direct anticoagulants. The pharmacokinetic (PK) behavior of apixaban may be altered in elderly populations and populations with renal or hepatic impairment, necessitating dosage adjustments.

METHODS

This study was conducted to examine how the physiologically based pharmacokinetic (PBPK) model describes the PKs of apixaban in adult and elderly populations and to determine the PKs of apixaban in elderly populations with renal and hepatic impairment. After PBPK models were constructed using the reported physicochemical properties of apixaban and clinical data, they were validated using data from clinical studies involving various dose ranges. Comparing predicted and observed blood concentration data and PK parameters was utilized to evaluate the model's fit performance.

RESULTS

Doses should be reduced to approximately 70% of the healthy adult population for the healthy elderly population to achieve the same PK exposure; approximately 88%, 71%, and 89% of that for the elderly populations with mild, moderate, and severe renal impairment, respectively; and approximately 96%, 81%, and 58% of that for the Child Pugh-A, Child Pugh-B, and Child Pugh-C hepatic impairment elderly populations, respectively to achieve the same PK exposure.

CONCLUSION

The findings indicate that the renal and hepatic function might be considered for apixaban therapy in Chinese elderly patients and the PBPK model can be used to optimize dosage regimens for specific populations.

Effect of changes in metabolic enzymes and transporters on drug metabolism in the context of liver disease: Impact on pharmacokinetics and drug-drug interactions

Changes in the pharmacokinetic and resulting pharmacodynamic properties of drugs are common in many chronic liver diseases, leading to adverse effects, drug interactions and increased risk of over- or underdosing of medications. Structural and functional hepatic impairment can have major effects on drug metabolism and transport. This review summarizes research on the functional changes in phase I and II metabolic enzymes and in transport proteins in patients with metabolic diseases such as type 2 diabetes, metabolic dysfunction-associated steatotic liver disease, metabolic dysfunction-associated steatohepatitis and cirrhosis, providing a clinical perspective on how these changes affect drug uptake and metabolism. Generally, a decrease in expression and/or activity of many enzymes of the cytochrome P450 family (e.g. CYP2E1 and CYP3A4), and of influx and efflux transporters (e.g. organic anion-transporting polypeptide [OATP]1B1, OATP2B1, OAT2 and bile salt export pump), has been recently documented in patients with liver disease. Decreased enzyme levels often correlate with increased severity of chronic liver disease. In subjects with hepatic impairment, there is potential for strong alterations of drug pharmacokinetics due to reduced absorption, increased volume of distribution, metabolism and extraction. Due to the altered pharmacokinetics, specific drug-drug interactions are also a potential issue to consider in patients with liver disease. Given the huge burden of liver disease in western societies, there is a need to improve awareness among all healthcare professionals and patients with liver disease to ensure appropriate drug prescriptions.

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.

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 To Predict Metoprolol Disposition in Healthy and Disease Populations

The evolution in the development of drugs has increased the popularity of physiologically based pharmacokinetic (PBPK) models. This study seeks to assess the PK of metoprolol in populations with healthy, chronic kidney disease (CKD), and acute myocardial infarction (AMI) conditions by developing and evaluating PBPK models. An extensive literature review for identifying and selecting plasma concentration vs time profile data and other drug-related parameters was undergone for their integration into the PK-Sim program followed by the development of intravenous, oral, and diseased models. The developed PBPK model of metoprolol was then evaluated using the visual predictive checks, mean observed/predicted ratios (Robs/pre), and average fold error for all PK parameters, i.e., the area under the curve (AUC), maximal plasma concentration, and clearance. The model evaluation depicted that none of the PK parameters were out of the allowed range (2-fold error) in the case of the mean Robs/pre ratios. The model anticipations were executed to determine the influence of diseases on unbound and total AUC after the application of metoprolol in healthy, moderate, and severe CKD. The dosage reductions were also suggested based on differences in unbound and total AUC in different stages of CKD. The developed PBPK models have successfully elaborated the PK changes of metoprolol occurring in healthy individuals and those with renal and heart diseases (CKD & AMI), which may be fruitful for dose optimization among diseased patients.

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.

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.

Prediction of Janagliflozin Pharmacokinetics in Type 2 Diabetes Mellitus Patients with Liver Cirrhosis or Renal Impairment Using a Physiologically Based Pharmacokinetic Model

Janagliflozin is a sodium-glucose cotransporter 2 (SGLT2) inhibitor for type 2 diabetes mellitus (T2DM). The janagliflozin pharmacokinetics (PK) in T2DM patients with cirrhosis or renal impairment (RI) are unknown. To predict the janagliflozin PK in these patients, we constructed a physiologically based PK (PBPK) model that predicted the janagliflozin PK in normal animals. The model was extrapolated to healthy humans and optimized with the measured data. A PBPK model for T2DM patients was developed and optimized with the measured data. Based on the physiological alterations in cirrhosis or RI patients, the T2DM model was applied to predict the janagliflozin PK in these patients. Results were validated using fold error values. The predicted AUC values were 21880, 24881, 26996, and 28419 ng/ml·h in T2DM patients with no cirrhosis, Child-Pugh-A, B, and C, respectively, and those in T2DM patients with RI-mild, RI-moderate, and RI-severe were 21810, 21840, and 22845 ng/ml·h, respectively. Janagliflozin exposure increased with increasing cirrhosis severity, whereas it remained stable regardless of the RI severity. The PBPK model predicted the janagliflozin PK in patients with T2DM and liver cirrhosis or RI. Dose adjustment is less critical for these patients. Risk benefit assessment in janagliflozin dosing for T2DM patients with liver disease is recommended.

Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations

The physiologically based pharmacokinetic (PBPK) approach can be used to develop mathematical models for predicting the absorption, distribution, metabolism, and elimination (ADME) of administered drugs in virtual human populations. Haloperidol is a typical antipsychotic drug with a narrow therapeutic index and is commonly used in the management of several medical conditions, including psychotic disorders. Due to the large interindividual variability among patients taking haloperidol, it is very likely for them to experience either toxic or subtherapeutic effects. We intend to develop a haloperidol PBPK model for identifying the potential sources of pharmacokinetic (PK) variability after intravenous and oral administration by using the population-based simulator, PK-Sim. The model was initially developed and evaluated to predict the PK of haloperidol and its reduced metabolite in adult healthy population after intravenous and oral administration. After evaluating the developed PBPK model in healthy adults, it was used to predict haloperidol–rifampicin drug–drug interaction and was extended to tuberculosis patients. The model evaluation was performed using visual assessments, prediction error, and mean fold error of the ratio of the observed-to-predicted values of the PK parameters. The predicted PK values were in good agreement with the corresponding reported values. The effects of the pathophysiological changes and enzyme induction associated with tuberculosis and its treatment, respectively, on haloperidol PK, have been predicted precisely. For all clinical scenarios that were evaluated, the predicted values were within the acceptable two-fold error range.

Nanoclay-Based Composite Films for Transdermal Drug Delivery: Development, Characterization, and in silico Modeling and Simulation

Purpose

Halloysite nanotubes (HNTs) are a versatile and highly investigated clay mineral due to their natural availability, low cost, strong mechanical strength, biocompatibility, and binding properties. The present work explores its role for retarding and controlling the drug release from the composite polymer matrix material.

Methods

For this purpose, nanocomposite films comprising propranolol HCl and different concentrations of HNTs were formulated using the “solution casting method”. The menthol in a concentration of 1% w/v was used as a permeation enhancer, and its effect on release and permeation was also determined. Quality characteristics of the nanocomposite were determined, and in vitro release and permeation studies were performed using the Franz diffusion system. The data was analyzed using various mathematical models and permeation parameters. Optimized formulation was also subjected to skin irritation test, FTIR, DSC, and SEM study. Systemic absorption and disposition of propranolol HCl from the nanocomposites were predicted using the GastroPlus TCAT® model.

Results

The control in drug release rate was associated with the higher concentration of HNTs. F8 released 50% of propranolol within 8 hours (drug, HNTs ratio, 1:2). The optimized formulation (F6) with drug: HNTs (2:1), exhibited drug release 80% in 4 hours, with maximum flux of 145.812 µg/cm²hr. The optimized formulation was found to be a non-irritant for skin with a shelf life of 35.46 months (28–30 ℃). The in silico model predicted C_max, T_max, AUC_t, and AUC_inf as 32.113 ng/mL, 16.58 h, 942.34 ng/mL×h, and 1102.9 ng/mL×h, respectively.

Conclusion

The study demonstrated that HNTs could be effectively used as rate controlling agent in matrix type transdermal formulations.

The emerging role of physiologically-based pharmacokinetic/biopharmaceutics modeling in formulation development

Computer-based (in silico) modeling & simulation tools have been embraced in different fields of pharmaceutics for a variety of applications. Among these, physiologically-based pharmacokinetic/biopharmaceutics modeling (PBPK/PBBM) emerged as a particularly useful tool in formulation development. PBPK/PBBM facilitated strategies have been increasingly evaluated over the past few years, as demonstrated by several reports from the pharmaceutical industry, and a number of research and review papers on this subject. Also, the leading regulatory authorities have recently issued guidance on the use of PBPK modeling in formulation design. In silico PBPK models can comprise different dosing routes (oral, intraoral, parenteral, inhalation, ocular, dermal etc.), although the majority of published examples refer to modeling of oral drugs performance. In order to facilitate the use of PBPK modeling tools, a couple of companies have launched commercially available software such as GastroPlus™, Simcyp™ PBPK Simulator and PK-Sim®. This paper highlights various application fields of PBPK/PBBM modeling, along with the basic principles, advantages and limitations of this approach, and provides relevant examples to demonstrate the practical utility of modeling & simulation tools in different stages of formulation development.