Application of a systems approach to the bottom-up assessment of pharmacokinetics in obese patients: expected variations in clearance

Physiologically based pharmacokinetic modeling in obesity: applications and challenges

INTRODUCTION

Rising global obesity rates pose a threat to people's health. Obesity causes a series of pathophysiologic changes, making the response of patients with obesity to drugs different from that of nonobese, thus affecting the treatment efficacy and even leading to adverse events. Therefore, understanding obesity's effects on pharmacokinetics is essential for the rational use of drugs in patients with obesity.

AREAS COVERED

Articles related to physiologically based pharmacokinetic (PBPK) modeling in patients with obesity from inception to October 2023 were searched in PubMed, Embase, Web of Science and the Cochrane Library. This review outlines PBPK modeling applications in exploring factors influencing obesity's effects on pharmacokinetics, guiding clinical drug development and evaluating and optimizing clinical use of drugs in patients with obesity.

EXPERT OPINION

Obesity-induced pathophysiologic alterations impact drug pharmacokinetics and drug-drug interactions (DDIs), altering drug exposure. However, there is a lack of universal body size indices or quantitative pharmacology models to predict the optimal for the patients with obesity. Therefore, dosage regimens for patients with obesity must consider individual physiological and biochemical information, and clinically individualize therapeutic drug monitoring for highly variable drugs to ensure effective drug dosing and avoid adverse effects.

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.

Development of a Physiologically Based Pharmacokinetic Population Model for Diabetic Patients and its Application to Understand Disease-drug-drug Interactions

INTRODUCTION

The activity changes of cytochrome P450 (CYP450) enzymes, along with the complicated medication scenarios in diabetes mellitus (DM) patients, result in the unanticipated pharmacokinetics (PK), pharmacodynamics (PD), and drug-drug interactions (DDIs). Physiologically based pharmacokinetic (PBPK) modeling has been a useful tool for assessing the influence of disease status on CYP enzymes and the resulting DDIs. This work aims to develop a novel diabetic PBPK population model to facilitate the prediction of PK and DDI in DM patients.

METHODS

First, mathematical functions were constructed to describe the demographic and non-CYP physiological characteristics specific to DM, which were then incorporated into the PBPK model to quantify the net changes in CYP enzyme activities by comparing the PK of CYP probe drugs in DM versus non-DM subjects.

RESULTS

The results show that the enzyme activity is reduced by 32.3% for CYP3A4/5, 39.1% for CYP2C19, and 27% for CYP2B6, while CYP2C9 activity is enhanced by 38% under DM condition. Finally, the diabetic PBPK model was developed through integrating the DM-specific CYP activities and other parameters and was further used to perform PK simulations under 12 drug combination scenarios, among which 3 combinations were predicted to result in significant PK changes in DM, which may cause DDI risks in DM patients.

CONCLUSIONS

The PBPK modeling applied herein provides a quantitative tool to assess the impact of disease factors on relevant enzyme pathways and potential disease-drug-drug-interactions (DDDIs), which may be useful for dosing regimen optimization and minimizing the DDI risks associated with the treatment of DM.

Impact of Obesity on Hepatic Drug Clearance: What are the Influential Variables?

Drug clearance in obese subjects varies widely among different drugs and across subjects with different severity of obesity. This study investigates correlations between plasma clearance (CLp) and drug- and patient-related characteristics in obese subjects, and evaluates the systematic accuracy of common weight-based dosing methods. A physiologically-based pharmacokinetic (PBPK) modeling approach that uses recent information on obesity-related changes in physiology was used to simulate CLp for a normal-weight subject (body mass index [BMI] = 20) and subjects with various severities of obesity (BMI 25-60) for hypothetical hepatically cleared drugs with a wide range of properties. Influential variables for CLp change were investigated. For each drug and obese subject, the exponent that yields perfect allometric scaling of CLp from normal-weight subjects was assessed. Among all variables, BMI and relative changes in enzyme activity resulting from obesity proved highly correlated with obesity-related CLp changes. Drugs bound to α1-acid glycoprotein (AAG) had lower CLp changes compared to drugs bound to human serum albumin (HSA). Lower extraction ratios (ER) corresponded to higher CLp changes compared to higher ER. The allometric exponent for perfect scaling ranged from -3.84 to 3.34 illustrating that none of the scaling methods performed well in all situations. While all three dosing methods are generally systematically accurate for drugs with unchanged or up to 50% increased enzyme activity in subjects with a BMI below 30 kg/m2, in any of the other cases, information on the different drug properties and severity of obesity is required to select an appropriate dosing method for individuals with obesity.

The Impact of Paediatric Obesity on Drug Pharmacokinetics: A Virtual Clinical Trials Case Study with Amlodipine

The incidence of paediatric obesity continues to rise worldwide and contributes to a range of diseases including cardiovascular disease. Obesity in children has been shown to impact upon the plasma concentrations of various compounds, including amlodipine. Nonetheless, information on the influence of obesity on amlodipine pharmacokinetics and the need for dose adjustment has not been studied previously. This study applied the physiologically based pharmacokinetic modelling and established a paediatric obesity population to assess the impact of obesity on amlodipine pharmacokinetics in children and explore the possible dose adjustments required to reach the same plasma concentration as non-obese paediatrics. The difference in predicted maximum concentration (Cmax) and area under the curve (AUC) were significant between children with and without obesity across the age group 2 to 18 years old when a fixed-dose regimen was used. On the contrary, a weight-based dose regimen showed no difference in Cmax between obese and non-obese from 2 to 9 years old. Thus, when a fixed-dose regimen is to be administered, a 1.25- to 1.5-fold increase in dose is required in obese children to achieve the same Cmax concentration as non-obese children, specifically for children aged 5 years and above.

Physiologically Based Pharmacokinetic (PBPK) Model Predictions of Disease Mediated Changes in Drug Disposition in Patients with Nonalcoholic Fatty Liver Disease (NAFLD)

PURPOSE

This study was designed to verify a virtual population representing patients with nonalcoholic fatty liver disease (NAFLD) to support the implementation of a physiologically based pharmacokinetic (PBPK) modeling approach for prediction of disease-related changes in drug pharmacokinetics.

METHODS

A virtual NAFLD patient population was developed in GastroPlus (v.9.8.2) by accounting for pathophysiological changes associated with the disease and proteomics-informed alterations in the abundance of metabolizing enzymes and transporters pertinent to drug disposition. The NAFLD population model was verified using exemplar drugs where elimination is influenced predominantly by cytochrome P450 (CYP) enzymes (chlorzoxazone, caffeine, midazolam, pioglitazone) or by transporters (rosuvastatin, 11C-metformin, morphine and the glucuronide metabolite of morphine).

RESULTS

PBPK model predictions of plasma concentrations of all the selected drugs and hepatic radioactivity levels of 11C-metformin were consistent with the clinically-observed data. Importantly, the PBPK simulations using the virtual NAFLD population model provided reliable estimates of the extent of changes in key pharmacokinetic parameters for the exemplar drugs, with mean predicted ratios (NAFLD patients divided by healthy individuals) within 0.80- to 1.25-fold of the clinically-reported values, except for midazolam (prediction-fold difference of 0.72).

CONCLUSION

A virtual NAFLD population model within the PBPK framework was successfully developed with good predictive capability of estimating disease-related changes in drug pharmacokinetics. This supports the use of a PBPK modeling approach for prediction of the pharmacokinetics of new investigational or repurposed drugs in patients with NAFLD and may help inform dose adjustments for drugs commonly used to treat comorbidities in this patient population.

The impact of obesity on doravirine exposure in people with HIV

Obesity incidence is increasing among people with HIV. Doravirine is a recommended first-line antiretroviral drug in many countries with no data from people with obesity. This study investigates the exposure of doravirine 100 mg standard dose in obese versus normal weight patients using clinical data combined with physiologically based pharmacokinetic modelling. Results from both approaches showed an elevated doravirine exposure during obesity, yet within the safety range of doravirine with no need for dose modification.

Animal-to-Human Dose Translation of ANTHRASIL for Treatment of Inhalational Anthrax in Healthy Adults, Obese Adults, and Pediatric Subjects

Anthrax Immune Globulin Intravenous (AIGIV [ANTHRASIL]), was developed for the treatment of toxemia associated with inhalational anthrax. It is a plasma product collected from individuals vaccinated with anthrax vaccine and contains antitoxin IgG antibodies against Bacillus anthracis protective antigen. A pharmacokinetic (PK) and exposure-response model was constructed to assess the PKs of AIGIV in anthrax-free and anthrax-exposed rabbits, non-human primates and anthrax-free humans, as well as the relationship between AIGIV exposure and survival from anthrax, based on available preclinical/clinical studies. The potential effect of anthrax on the PKs of AIGIV was evaluated and estimates of survival odds following administration of AIGIV protective doses with and without antibiotic co-treatment were established. As the developed PK model can simulate exposure of AIGIV in any species for any dosing scenario, the relationship between the predicted area under the concentration curve of AIGIV in humans and the probability of survival observed in preclinical studies was explored. Based on the simulation results, the intravenous administration of 420 U (units of potency as measured by validated Toxin Neutralization Assay) of AIGIV is expected to result in a > 80% probability of survival in more than 90% of the human population. Additional simulations suggest that exposure levels were similar in healthy and obese humans, and exposure in pediatrics is expected to be up to approximately seven-fold higher than in healthy adults, allowing for doses in pediatric populations that ranged from one to seven vials. Overall, the optimal human dose was justified based on the PK/pharmacodynamic (PD) properties of AIGIV in animals and model-based translation of PK/PD to predict human exposure and efficacy.

Model-Informed Approaches to Support Drug Development for Patients With Obesity: A Regulatory Perspective

Obesity, which is defined as having a body mass index of 30 kg/m2 or greater, has been recognized as a serious health problem that increases the risk of many comorbidities (eg, heart disease, stroke, and diabetes) and mortality. The high prevalence of individuals who are classified as obese calls for additional considerations in clinical trial design. Nevertheless, gaining a comprehensive understanding of how obesity affects the pharmacokinetics (PK), pharmacodynamics (PD), and efficacy of drugs proves challenging, primarily as obese patients are seldom selected for enrollment at the early stages of drug development. Over the past decade, model-informed drug development (MIDD) approaches have been increasingly used in drug development programs for obesity and its related diseases as they use and integrate all available sources and knowledge to inform and facilitate clinical drug development. This review summarizes the impact of obesity on PK, PD, and the efficacy of drugs and, more importantly, provides an overview of the use of MIDD approaches in drug development and regulatory decision making for patients with obesity: estimating PK, PD, and efficacy in specific dosing scenarios, optimizing dose regimen, and providing evidence for seeking new indication(s). Recent review cases using MIDD approaches to support dose selection and provide confirmatory evidence for effectiveness for patients with obesity, including pediatric patients, are discussed. These examples demonstrate the promise of MIDD as a valuable tool in supporting clinical trial design during drug development and facilitating regulatory decision-making processes for the benefit of patients with obesity.

PBPK Modeling of Azithromycin Systemic Exposure in a Roux-en-Y Gastric Bypass Surgery Patient Population

In this investigation, PBPK modeling using the Simcyp® Simulator was performed to evaluate whether Roux-en-Y gastric bypass (RYGB) surgery impacts the oral absorption and bioavailability of azithromycin. An RYGB surgery patient population was adapted from the published literature and verified using the same probe medications, atorvastatin and midazolam. Next, a PBPK model of azithromycin was constructed to simulate changes in systemic drug exposure after the administration of different oral formulations (tablet, suspension) to patients pre- and post-RYGB surgery using the developed and verified population model. Clinically observed changes in azithromycin systemic exposure post-surgery following oral administration (single-dose tablet formulation) were captured using PBPK modeling based on the comparison of model-predicted exposure metrics (Cmax, AUC) to published clinical data. Model simulations predicted a 30% reduction in steady-state AUC after surgery for three- and five-day multiple dose regimens of an azithromycin tablet formulation. The relative bioavailability of a suspension formulation was 1.5-fold higher than the tablet formulation after multiple dosing. The changes in systemic exposure observed after surgery were used to evaluate the clinical efficacy of azithromycin against two of the most common pathogens causing community acquired pneumonia based on the corresponding AUC24/MIC pharmacodynamic endpoint. The results suggest lower bioavailability of the tablet formulation post-surgery may impact clinical efficacy. Overall, the research demonstrates the potential of a PBPK modeling approach as a framework to optimize oral drug therapy in patients post-RYGB surgery.

A physiologically based pharmacokinetic model of cefepime to predict its pharmacokinetics in healthy, pediatric and disease populations

The physiologically based pharmacokinetic modeling (PBPK) approach can predict drug pharmacokinetics (PK) by combining changes in blood flow and pathophysiological alterations for developing drug-disease models. Cefepime hydrochloride is a parenteral cephalosporin that is used to treat pneumonia, sepsis, and febrile neutropenia, among other things. The current study sought to identify the factors that impact cefepime pharmacokinetics (PK) following dosing in healthy, diseased (CKD and obese), and pediatric populations. For model construction and simulation, the modeling tool PK-SIM was utilized. Estimating cefepime PK following intravenous (IV) application in healthy subjects served as the primary step in the model-building procedure. The prediction of cefepime PK in chronic kidney disease (CKD) and obese populations were performed after the integration of the relevant pathophysiological changes. Visual predictive checks and a comparison of the observed and predicted values of the PK parameters were used to verify the developed model. The results of the PK parameters were consistent with the reported clinical data in healthy subjects. The developed PBPK model successfully predicted cefepime PK as observed from the ratio of the observed and predicted PK parameters as they were within a two-fold error range.

Predictive Performance of Physiologically Based Pharmacokinetic Modelling of Beta-Lactam Antibiotic Concentrations in Adipose, Bone, and Muscle Tissues

Physiologically based pharmacokinetic (PBPK) models consist of compartments representing different tissues. As most models are only verified based on plasma concentrations, it is unclear how reliable associated tissue profiles are. This study aimed to assess the accuracy of PBPK-predicted beta-lactam antibiotic concentrations in different tissues and assess the impact of using effect site concentrations for evaluation of target attainment. Adipose, bone, and muscle concentrations of five beta-lactams (piperacillin, cefazolin, cefuroxime, ceftazidime, and meropenem) in healthy adults were collected from literature and compared with PBPK predictions. Model performance was evaluated with average fold errors (AFEs) and absolute AFEs (AAFEs) between predicted and observed concentrations. In total, 26 studies were included, 14 of which reported total tissue concentrations and 12 unbound interstitial fluid (uISF) concentrations. Concurrent plasma concentrations, used as baseline verification of the models, were fairly accurate (AFE: 1.14, AAFE: 1.50). Predicted total tissue concentrations were less accurate (AFE: 0.68, AAFE: 1.89). A slight trend for underprediction was observed but none of the studies had AFE or AAFE values outside threefold. Similarly, predictions of microdialysis-derived uISF concentrations were less accurate than plasma concentration predictions (AFE: 1.52, AAFE: 2.32). uISF concentrations tended to be overpredicted and two studies had AFEs and AAFEs outside threefold. Pharmacodynamic simulations in our case showed only a limited impact of using uISF concentrations instead of unbound plasma concentrations on target attainment rates. The results of this study illustrate the limitations of current PBPK models to predict tissue concentrations and the associated need for more accurate models. SIGNIFICANCE STATEMENT: Clinical inaccessibility of local effect site concentrations precipitates a need for predictive methods for the estimation of tissue concentrations. This is the first study in which the accuracy of PBPK-predicted tissue concentrations of beta-lactam antibiotics in humans were assessed. Predicted tissue concentrations were found to be less accurate than concurrent predicted plasma concentrations. When using PBPK models to predict tissue concentrations, this potential relative loss of accuracy should be acknowledged when clinical tissue concentrations are unavailable to verify predictions.

Considerations for Intravenous Anesthesia Dose in Obese Children: Understanding PKPD

The intravenous induction or loading dose in children is commonly prescribed per kilogram. That dose recognizes the linear relationship between volume of distribution and total body weight. Total body weight comprises both fat and fat-free mass. Fat mass influences the volume of distribution and the use of total body weight fails to recognize the impact of fat mass on pharmacokinetics in children. Size metrics alternative to total body mass (e.g., fat-free and normal fat mass, ideal body weight and lean body weight) have been proposed to scale pharmacokinetic parameters (clearance, volume of distribution) for size. Clearance is the key parameter used to calculate infusion rates or maintenance dosing at steady state. Dosing schedules recognize the curvilinear relationship, described using allometric theory, between clearance and size. Fat mass also has an indirect influence on clearance through both metabolic and renal function that is independent of its effects due to increased body mass. Fat-free mass, lean body mass and ideal body mass are not drug specific and fail to recognize the variable impact of fat mass contributing to body composition in children, both lean and obese. Normal fat mass, used in conjunction with allometry, may prove a useful size metric but computation by clinicians for the individual child is not facile. Dosing is further complicated by the need for multicompartment models to describe intravenous drug pharmacokinetics and the concentration effect relationship, both beneficial and adverse, is often poorly understood. Obesity is also associated with other morbidity that may also influence pharmacokinetics. Dose is best determined using pharmacokinetic-pharmacodynamic (PKPD) models that account for these varied factors. These models, along with covariates (age, weight, body composition), can be incorporated into programmable target-controlled infusion pumps. The use of target-controlled infusion pumps, assuming practitioners have a sound understanding of the PKPD within programs, provide the best available guide to intravenous dose in obese children.

Challenges in Cardiovascular Evaluation and Management of Obese Patients: JACC State-of-the-Art Review

Many unique clinical challenges accompany the diagnosis and treatment of cardiovascular disease (CVD) in people living with overweight/obesity. Similarly, physicians encounter numerous complicating factors when managing obesity among people with CVD. Diagnostic accuracy in CVD medicine can be hampered by the presence of obesity, and pharmacological treatments or cardiac procedures require careful adjustment to optimize efficacy. The obesity paradox concept remains a source of confusion within the clinical community that may cause important risk factors to go unaddressed, and body mass index is a misleading measure that cannot account for body composition (eg, lean mass). Lifestyle modifications that support weight loss require long-term commitment, but cardiac rehabilitation programs represent a potential opportunity for structured interventions, and bariatric surgery may reduce CVD risk factors in obesity and CVD. This review examines the key issues and considerations for physicians involved in the management of concurrent obesity and CVD.

Considerations for Physiologically Based Modeling in Liver Disease: From Nonalcoholic Fatty Liver (NAFL) to Nonalcoholic Steatohepatitis (NASH)

Nonalcoholic fatty liver disease (NAFLD), representing a clinical spectrum ranging from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH), is rapidly evolving into a global pandemic. Patients with NAFLD are burdened with high rates of metabolic syndrome-related comorbidities resulting in polypharmacy. Therefore, it is crucial to gain a better understanding of NAFLD-mediated changes in drug disposition and efficacy/toxicity. Despite extensive clinical pharmacokinetic data in cirrhosis, current knowledge concerning pharmacokinetic alterations in NAFLD, particularly at different stages of disease progression, is relatively limited. In vitro-to-in vivo extrapolation coupled with physiologically based pharmacokinetic and pharmacodynamic (IVIVE-PBPK/PD) modeling offers a promising approach for optimizing pharmacologic predictions while refining and reducing clinical studies in this population. Use of IVIVE-PBPK to predict intra-organ drug concentrations at pharmacologically relevant sites of action is particularly advantageous when it can be linked to pharmacodynamic effects. Quantitative systems pharmacology/toxicology (QSP/QST) modeling can be used to translate pharmacokinetic and pharmacodynamic data from PBPK/PD models into clinically relevant predictions of drug response and toxicity. In this review, a detailed summary of NAFLD-mediated alterations in human physiology relevant to drug absorption, distribution, metabolism, and excretion (ADME) is provided. The application of literature-derived physiologic parameters and ADME-associated protein abundance data to inform virtual NAFLD population development and facilitate PBPK/PD, QSP, and QST predictions is discussed along with current limitations of these methodologies and knowledge gaps. The proposed methodologic framework offers great potential for meaningful prediction of pharmacological outcomes in patients with NAFLD and can inform both drug development and clinical practice for this population.

Development and application of a pediatric mechanistic kidney model

Pediatric physiologically‐based pharmacokinetic (P‐PBPK) models have been used to predict age related changes in the pharmacokinetics (PKs) of renally cleared drugs mainly in relation to changes in glomerular filtration rate. With emerging data on ontogeny of renal transporters, mechanistic models of renal clearance accounting for the role of active and passive secretion should be developed and evaluated. Data on age‐related physiological changes and ontogeny of renal transporters were applied into a mechanistic kidney within a P‐PBPK model. Plasma concentration–time profile and PK parameters of cimetidine, ciprofloxacin, metformin, tenofovir, and zidovudine were predicted in subjects aged 1 day to 18 years. The predicted and observed plasma concentration–time profiles and PK parameters were compared. The predicted concentration–time profile means and 5th and 95th percent intervals generally captured the observed data and variability in various studies. Overall, based on drugs and age bands, predicted to observed clearance were all within two‐fold and in 11 of 16 cases within 1.5‐fold. Predicted to observed area under the curve (AUC) and maximum plasma concentration (C_max) were within two‐fold in 12 of 14 and 12 of 15 cases, respectively. Predictions in neonates and early infants (up to 14 weeks postnatal age) were reasonable with 15–20 predicted PK parameters within two‐fold of the observed. ciprofloxacin but not zidovudine PK predictions were sensitive to basal kidney uptake transporter ontogeny. The results indicate that a mechanistic kidney model accounting for physiology and ontogeny of renal processes and transporters can predict the PK of renally excreted drugs in children. Further data especially in neonates are required to verify the model and ontogeny profiles.

Repository Describing the Anatomical, Physiological, and Biological Changes in an Obese Population to Inform Physiologically Based Pharmacokinetic Models

Background

Obesity is associated with physiological changes that can affect drug pharmacokinetics. Obese individuals are underrepresented in clinical trials, leading to a lack of evidence-based dosing recommendations for many drugs. Physiologically based pharmacokinetic (PBPK) modelling can overcome this limitation but necessitates a detailed description of the population characteristics under investigation.

Objective

The purpose of this study was to develop and verify a repository of the current anatomical, physiological, and biological data of obese individuals, including population variability, to inform a PBPK framework.

Methods

A systematic literature search was performed to collate anatomical, physiological, and biological parameters for obese individuals. Multiple regression analyses were used to derive mathematical equations describing the continuous effect of body mass index (BMI) within the range 18.5–60 kg/m² on system parameters.

Results

In total, 209 studies were included in the database. The literature reported mostly BMI-related changes in organ weight, whereas data on blood flow and biological parameters (i.e. enzyme abundance) were sparse, and hence physiologically plausible assumptions were made when needed. The developed obese population was implemented in Matlab^® and the predicted system parameters obtained from 1000 virtual individuals were in agreement with observed data from an independent validation obese population. Our analysis indicates that a threefold increase in BMI, from 20 to 60 kg/m², leads to an increase in cardiac output (50%), liver weight (100%), kidney weight (60%), both the kidney and liver absolute blood flows (50%), and in total adipose blood flow (160%).

Conclusion

The developed repository provides an updated description of a population with a BMI from 18.5 to 60 kg/m² using continuous physiological changes and their variability for each system parameter. It is a tool that can be implemented in PBPK models to simulate drug pharmacokinetics in obese individuals.

Use of physiologically‐based pharmacokinetic modeling to inform dosing of the opioid analgesics fentanyl and methadone in children with obesity

Obesity is an increasingly alarming public health threat, with nearly 20% of children classified as obese in the United States today. Children with obesity are commonly prescribed the opioids fentanyl and methadone, and accurate dosing is critical to reducing the risk of serious adverse events associated with overexposure. However, pharmacokinetic studies in children with obesity are challenging to conduct, so there is limited information to guide fentanyl and methadone dosing in these children. To address this clinical knowledge gap, physiologically‐based pharmacokinetic models of fentanyl and methadone were developed in adults and scaled to children with and without obesity to explore the interplay of obesity, age, and pharmacogenomics. These models included key obesity‐induced changes in physiology and pharmacogenomic effects. Model predictions captured observed concentrations in children with obesity well, with an overall average fold error of 0.72 and 1.08 for fentanyl and methadone, respectively. Model simulations support a reduced fentanyl dose (1 vs. 2 μg/kg/h) starting at an earlier age (6 years) in virtual children with obesity, highlighting the importance of considering both age and obesity status when selecting an infusion rate most likely to achieve steady‐state concentrations within the target range. Methadone dosing simulations highlight the importance of considering genotype in addition to obesity status when possible, as cytochrome P450 (CYP)2B6*6/*6 virtual children with obesity required half the dose to match the exposure of wildtype children without obesity. This physiologically‐based pharmacokinetic modeling approach can be applied to explore dosing of other critical drugs in children with obesity.

Application of a Physiologically Based Pharmacokinetic Model to Predict Cefazolin and Cefuroxime Disposition in Obese Pregnant Women Undergoing Caesarean Section

Intravenous (IV) cefuroxime and cefazolin are used prophylactically in caesarean sections (CS). Currently, there are concerns regarding sub-optimal dosing in obese pregnant women compared to lean pregnant women prior to CS. The current study used a physiologically based pharmacokinetic (PBPK) approach to predict cefazolin and cefuroxime pharmacokinetics in obese pregnant women at the time of CS as well as the duration that these drug concentrations remain above a target concentration (2, 4 or 8 µg/mL or µg/g) in plasma or adipose tissue. Cefazolin and cefuroxime PBPK models were first built using clinical data in lean and in obese non–pregnant populations. Models were then used to predict cefazolin and cefuroxime pharmacokinetics data in lean and obese pregnant populations. Both cefazolin and cefuroxime models sufficiently described their total and free levels in the plasma and in the adipose interstitial fluid (ISF) in non–pregnant and pregnant populations. The obese pregnant cefazolin model predicted adipose exposure adequately at different reference time points and indicated that an IV dose of 2000 mg can maintain unbound plasma and adipose ISF concentration above 8 µg/mL for 3.5 h post dose. Predictions indicated that an IV 1500 mg cefuroxime dose can achieve unbound plasma and unbound ISF cefuroxime concentration of ≥8 µg/mL up to 2 h post dose in obese pregnant women. Re-dosing should be considered if CS was not completed within 2 h post cefuroxime administration for both lean or obese pregnant if cefuroxime concentrations of ≥8 µg/mL is required. A clinical study to measure cefuroxime adipose concentration in pregnant and obese pregnant women is warranted.

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.

Characterizing Pharmacokinetics in Children With Obesity-Physiological, Drug, Patient, and Methodological Considerations

Childhood obesity is an alarming public health problem. The pediatric obesity rate has quadrupled in the past 30 years, and currently nearly 20% of United States children and 9% of children worldwide are classified as obese. Drug distribution and elimination processes, which determine drug exposure (and thus dosing), can vary significantly between patients with and without obesity. Obesity-related physiological changes, such as increased tissue volume and perfusion, altered blood protein concentrations, and tissue composition can greatly affect a drug's volume of distribution, which might necessitate adjustment in loading doses. Obesity-related changes in the drug eliminating organs, such as altered enzyme activity in the liver and glomerular filtration rate, can affect the rate of drug elimination, which may warrant an adjustment in the maintenance dosing rate. Although weight-based dosing (i.e., in mg/kg) is commonly practiced in pediatrics, choice of the right body size metric (e.g., total body weight, lean body weight, body surface area, etc.) for dosing children with obesity still remains a question. To address this gap, the interplay between obesity-related physiological changes (e.g., altered organ size, composition, and function), and drug-specific properties (e.g., lipophilicity and elimination pathway) needs to be characterized in a quantitative framework. Additionally, methodological considerations, such as adequate sample size and optimal sampling scheme, should also be considered to ensure accurate and precise top-down covariate selection, particularly when designing opportunistic studies in pediatric drug development. Further factors affecting dosing, including existing dosing recommendations, target therapeutic ranges, dose capping, and formulations constraints, are also important to consider when undergoing dose selection for children with obesity. Opportunities to bridge the dosing knowledge gap in children with obesity include modeling and simulating techniques (i.e., population pharmacokinetic and physiologically-based pharmacokinetic [PBPK] modeling), opportunistic clinical data, and real world data. In this review, key considerations related to physiology, drug parameters, patient factors, and methodology that need to be accounted for while studying the influence of obesity on pharmacokinetics in children are highlighted and discussed. Future studies will need to leverage these modeling opportunities to better describe drug exposure in children with obesity as the childhood obesity epidemic continues.

Physiologically Based Pharmacokinetic Modeling of Metformin in Children and Adolescents with Obesity

Childhood obesity continues to rise in the United States, and with it the off-label use of metformin for weight loss. The influence of age and obesity on the drug's disposition and exposure has not previously been studied using a mechanistic framework. Here, an adult physiologically based pharmacokinetic (PBPK) model of metformin was scaled to pediatric populations without obesity, with overweight / obesity, and with severe obesity; a published virtual population of children and adolescents with obesity was leveraged during model evaluation. When the pediatric model was simulated in groups 10 - 18 y of age, oral clearance (CL/F) following 1,000 mg of metformin was higher (∼1200 mL/min) in those with obesity and severe obesity compared to the groups without and with overweight (∼1000 mL/min). In addition, simulated AUC in older children and adolescents with obesity and severe obesity was comparable to that in adults with a similar dose-exposure relationship. Overall, simulations using the pediatric PBPK model support the use of adult doses of metformin in older children and adolescents with obesity. Moreover, the virtual population of children and adolescents with obesity offers a valuable tool to facilitate development of pediatric PBPK models for studying populations with obesity and, in turn, contribute information to inform drug labeling in this special population. This article is protected by copyright. All rights reserved.

Development and Evaluation of a Virtual Population of Children with Obesity for Physiologically Based Pharmacokinetic Modeling

BACKGROUND AND OBJECTIVE

While one in five children in the USA are now obese, and more than three-quarters receive at least one drug during childhood, there is limited dosing guidance for this vulnerable patient population. Physiologically based pharmacokinetic modeling can bridge the gap in the understanding of how pharmacokinetics, including drug distribution and clearance, changes with obesity by incorporating known obesity-related physiological changes in children. The objective of this study was to develop a virtual population of children with obesity to enable physiologically based pharmacokinetic modeling, then use the novel virtual population in conjunction with previously developed models of clindamycin and trimethoprim/sulfamethoxazole to better understand dosing of these drugs in children with obesity.

METHODS

To enable physiologically based pharmacokinetic modeling, a virtual population of children with obesity was developed using national survey, electronic health record, and clinical trial data, as well as data extracted from the literature. The virtual population accounts for key obesity-related changes in physiology relevant to pharmacokinetics, including increased body size, body composition, organ size and blood flow, plasma protein concentrations, and glomerular filtration rate. The virtual population was then used to predict the pharmacokinetics of clindamycin and trimethoprim/sulfamethoxazole in children with obesity using previously developed physiologically based pharmacokinetic models.

RESULTS

Model simulations predicted observed concentrations well, with an overall average fold error of 1.09, 1.24, and 1.53 for clindamycin, trimethoprim, and sulfamethoxazole, respectively. Relative to children without obesity, children with obesity experienced decreased clindamycin and trimethoprim/sulfamethoxazole weight-normalized clearance and volume of distribution, and higher absolute doses under recommended pediatric weight-based dosing regimens.

CONCLUSIONS

Model simulations support current recommended weight-based dosing in children with obesity for clindamycin and trimethoprim/sulfamethoxazole, as they met target exposure despite these changes in clearance and volume of distribution.

Pooled Analysis of Gastric Emptying in Patients With Obesity: Implications for Oral Absorption Projection

PURPOSE

Gastric emptying time is one of limiting factors that determines the pharmacokinetic properties of drugs administered by mouth. Despite the high prevalence of obesity worldwide, modifications in gastric emptying time have not been systematically addressed in this set of patients. The current analysis aims to quantitatively address obesity-related changes in gastric emptying time of solids, semisolids, and liquids compared with lean individuals, highlighting the relevant pharmacokinetic implications of oral drug absorption in patients with obesity.

METHODS

We searched the Cochrane Library, PubMed, Web of Science, and Embase for all relevant articles published until November 1, 2020. Differences in gastrointestinal variables in relation to gastric emptying between obese and lean individuals were quantified by weighted mean difference (WMD) and ratio of means (RoM). Robustness of the analyses was evaluated by subgroup analysis and publication bias test.

FINDINGS

A total of 17 studies with 906 participants were included. The gastric half-emptying time of solids (WMD, -10.4 minutes; P = 0.001; RoM, 0.90; P = 0.01) and liquids (WMD, -6.14 minutes; P < 0.001; RoM, 0.83, P = 0.03) was significantly shorter in individuals with obesity compared with lean individuals. These findings were confirmed by the subgroup analyses and publication bias tests.

IMPLICATIONS

Our pooled analysis systemically quantifies the differences in gastric half-emptying time between individuals with obesity and lean individuals, facilitating better understanding and prediction of drug absorption in individuals with obesity through physiologically based pharmacokinetic approaches. Obesity is associated with a faster transit of both solids and liquids through the stomach.

Effect of obesity on gastrointestinal transit, pressure and pH using a wireless motility capsule

BACKGROUND

Despite the increasing prevalence and medical burden of obesity, the understanding of gastrointestinal physiology in obesity is scarce, which hampers drug development.

AIM

To investigate the effect of obesity and food intake on gastrointestinal transit, pressure and pH.

MATERIAL AND METHODS

An exploratory cross-sectional study using a wireless motility capsule (SmartPill©) was performed in 11 participants with obesity and 11 age- and gender-matched participants with normal weight (group) in fasted and fed state (visit). During the first visit, the capsule was ingested after an overnight fast. During a second visit, the capsule was ingested after a nutritional drink to simulate fed state. Linear mixed models were constructed to compare segmental gastrointestinal transit, pressure and pH between groups (obesity or control) and within every group (fasted or fed).

RESULTS

Food intake slowed gastric emptying in both groups (both P < 0.0001), though food-induced gastric contractility was higher in participants with obesity compared to controls (P = 0.02). In the small intestine, a higher contractility (P = 0.001), shorter transit (P = 0.04) and lower median pH (P = 0.002) was observed in participants with obesity compared to controls. No differences were observed for colonic measurements.

CONCLUSION

Obesity has a profound impact on gastrointestinal physiology, which should be taken into account for drug development.

Low metformin dose and its therapeutic serum concentration in prediabetes

This prospective study aimed to analyze whether the patients with pre-diabetes (pre-DM) reach the TC (therapeutic concentration) of the metformin during repeated, low, constant drug dose. The guidelines do not recommend any metformin dose for this group of patients. Based on the previous study after a dose of 1700 mg/day the patients seem to reach the therapeutic drug concentration, which guarantees the glycemic effect. Twenty patients with new-diagnosed pre-DM were treated with a 1500 mg/day regimen of the metformin for 15 weeks. The serum concentration of the drug was assessed by liquid chromatography-mass spectrometry technique at 6 and 15 week of the treatment. The correlation of the serum metformin concentration with BMI (body mass index) and patients' weight was also performed. The mean metformin concentration was: 4.65 μmol/L (± 2.41) and 5.41 μmol/L (± 3.44) (p = 0.27) after 6 and 15 weeks of the treatment respectively. There was a positive correlation between the serum concentration of the metformin and body weight (but not BMI) in the 15th week of the therapy (p = 0.04)- the higher body weight the higher concentration of the metformin. Patients with pre-diabetes can be successfully treated with a low dose of metformin, to reach the drug's therapeutic concentration. Body weight can impact the metformin serum concentration during long-term treatment what should be taken into consideration when choosing the dose because of its pleiotropic effect e.g. on the cardiovascular system via reduction of the oxidative stress and would be not connected with the drug's hypoglycemic effect.ClinicalTrials.gov number: NCT03398356; date of first registration: 01/07/2018.

Pediatric Drug-Drug Interaction Evaluation: Drug, Patient Population, and Methodological Considerations

Hospitalized pediatric patients and those with complex or chronic conditions treated on an outpatient basis are commonly prescribed multiple drugs, resulting in increased risk for drug-drug interactions (DDIs). Although dedicated DDI evaluations are routinely performed in healthy adult volunteers during drug development, they are rarely performed in pediatric patients because of ethical, logistical, and methodological challenges. In the absence of pediatric DDI evaluations, adult DDI data are often extrapolated to pediatric patients. However, the magnitude of a DDI in pediatric patients may differ from adults because of age-dependent physiological changes that can impact drug disposition or response and because of other factors related to the drug (eg, dose, formulation) and the patient population (eg, disease state, obesity). Therefore, the DDI magnitude needs to be assessed in children separately from adults, although a lack of clinical DDI data in pediatric populations makes this evaluation challenging. As a result, pediatric DDI assessment relies on the predictive performance of the pharmacometric approaches used, such as population and physiologically based pharmacokinetic modeling. Therefore, careful consideration needs to be given to adequately account for the age-dependent physiological changes in these models to build high confidence for such untested DDI scenarios. This review article summarizes the key considerations related to the drug, patient population, and methodology, and how they can impact DDI evaluation in the pediatric population.

Physiologically-Based Pharmacokinetic Model of Morphine and Morphine-3-Glucuronide in Nonalcoholic Steatohepatitis

Nonalcoholic steatohepatitis (NASH), the progressive form of nonalcoholic fatty liver disease, is increasing in prevalence. NASH-related alterations in hepatic protein expression (e.g., transporters) and in overall physiology may affect drug exposure by altering drug disposition and elimination. The aim of this study was to build a physiologically-based pharmacokinetic (PBPK) model to predict drug exposure in NASH by incorporating NASH-related changes in hepatic transporters. Morphine and morphine-3-glucuronide (M3G) were used as model compounds. A PBPK model of morphine with permeability-limited hepatic disposition was extended to include M3G disposition and enterohepatic recycling (EHR). The model captured the area under the plasma concentration-time curve (AUC) of morphine and M3G after intravenous morphine administration within 0.82-fold and 1.94-fold of observed values from 3 independent clinical studies for healthy adult subjects (6, 10, and 14 individuals). When NASH-related changes in multidrug resistance-associated protein 2 (MRP2) and MRP3 were incorporated into the model, the predicted M3G mean AUC in NASH was 1.34-fold higher compared to healthy subjects, which is slightly lower than the observed value (1.63-fold). Exploratory simulations on other physiological changes occurring in NASH (e.g., moderate decreases in glomerular filtration rate and portal vein blood flow) revealed that the effect of transporter changes was most prominent. Additionally, NASH-related transporter changes resulted in decreased morphine EHR, which could be important for drugs with extensive EHR. This study is an important first step to predict drug disposition in complex diseases such as NASH using PBPK modeling.

Drug Dosing Recommendations for All Patients: A Roadmap for Change

Most drug labels do not contain dosing recommendations for a significant portion of real‐world patients for whom the drug is prescribed. Current label recommendations predominately reflect the population studied in pivotal trials that typically exclude patients who are very young or old, emaciated or morbidly obese, pregnant, or have multiple characteristics likely to influence dosing. As a result, physicians may need to guess the correct dose and regimen for these patients. It is now feasible to provide dose and regimen recommendations for these patients by integrating available scientific knowledge and by utilizing or modifying current regulatory agency‐industry practices. The purpose of this commentary is to explore several factors that should be considered in creating a process that will provide more effective, safe, and timely drug dosing recommendations for most, if not all, patients. These factors include the availability of real‐world data, development of predictive models, experience with the US Food and Drug Administration (FDA)’s pediatric exclusivity program, development of clinical decision software, funding mechanisms like the Prescription Drug Users Fee Act (PDUFA), and harmonization of global regulatory policies. From an examination of these factors, we recommend a relatively simple, efficient expansion of current practices designed to predict, confirm, and continuously improve drug dosing for more patients. We believe implementing these recommendations will benefit patients, payers, industry, and regulatory agencies.

Evaluating Lean Liver Volume as a Potential Scaler for In Vitro-In Vivo Extrapolation of Drug Clearance in Obesity Using the Model Drug Antipyrine

BACKGROUND

In vitro-in vivo extrapolation (IVIVE) of hepatic drug clearance (CL) involves the scaling of hepatic intrinsic clearance (CL_int,uH) by functional liver size, which is approximated by total liver volume (LV) as per the convention. However, in most overweight and obese patients, LV includes abnormal liver fat, which is not thought to contribute to drug elimination, thus overestimating drug CL. Therefore, lean liver volume (LLV) might be a more appropriate scaler of CL_int,uH.

OBJECTIVE

The objective of this work was to assess the application of LLV in CL extrapolation in overweight and obese patients (BMI >25 kg/m2) using a model drug antipyrine.

METHODS

Recently, a model to predict LLV from patient sex, weight, and height was developed and evaluated. In order to assess the LLV model's use in IVIVE, a correlation-based analysis was conducted using antipyrine as an example drug.

RESULTS

In the overweight group (BMI >25 kg/m2), LLV could describe 36% of the variation in antipyrine CL (R² = 0.36), which was >2-fold higher than that was explained by LV (R² = 0.17). In the normal-weight group (BMI ≤25 kg/m2), the coefficients of determination were 58% (R² = 0.58) and 43% (R²= 0.43) for LLV and LV, respectively.

CONCLUSION

The analysis indicates that LLV is potentially a more appropriate descriptor of functional liver size than LV, particularly in overweight individuals. Therefore, LLV has a potential application in IVIVE of CL in obesity.

Dosing of Continuous Fentanyl Infusions in Obese Children: A Population Pharmacokinetic Analysis

Differences in fentanyl pharmacokinetics (PK) between obese and nonobese adults have previously been reported; however, the impact of childhood obesity on fentanyl PK is relatively unknown. We developed a population pharmacokinetic (PopPK) model using opportunistically collected samples from a cohort of predominately obese children receiving fentanyl per the standard of care. Using a probability-based approach, we evaluated the ability of different continuous infusion strategies to provide steady-state concentrations (Css ) within an analgesic concentration range (1-3 ng/mL). Fifty-three samples from 32 children were used for PopPK model development. Median (range) age and body weight of study participants were 13 years (2-19 years) and 52 kg (16-164 kg), respectively. The majority of children (94%) were obese. A 2-compartment model allometrically scaled by total body weight provided an appropriate fit to the data. Estimated typical clearance was 32.5 L/h (scaled to 70 kg). A fixed dose rate infusion of 1 µg/kg/h was associated with probabilities between 49% and 58% for achieving Css within target; however, the risk of achieving Css > 3 ng/mL increased with increasing body weight (15% at 16 kg vs 43% at 164 kg). A proposed model-based infusion strategy maintained consistent probabilities across the examined weight range for achieving Css within (58%) and above (20%) target. Use of an allometric relationship between weight and clearance was appropriate for describing the PK of intravenous fentanyl in our cohort of predominately obese children. Our proposed model-derived continuous infusion strategy maximized the probability of achieving target Css in children of varying weights.

Physiologically-Based Pharmacokinetic Model on the Oral Drug Absorption in Roux-en-Y Gastric Bypass Bariatric Patients: Amoxicillin Tablet and Suspension

The potential of a physiologically-based pharmacokinetic (PBPK) model to predict oral amoxicillin bioavailability, by considering the physiological changes after "Roux-en-Y gastric bypass" (RYGB) surgery in bariatric patients, was evaluated. A middle-out approach for parameter estimations was undertaken using in vitro, in situ, and in vivo data. The observed versus predicted plasma concentrations and the model sensitivity of the simulated parameters of AUC_0-inf and C_max of amoxicillin (AMX) were used to confirm the reliability of the estimation. The model considers that a drug-transporter (Transp) in the initial segments of the normal intestine plays a significant role in the AMX absorption. A lower fraction absorbed (F_abs) was observed in RYGB patients (54.43% for suspension and 45.21% for tablets) compared to healthy subjects (77.48% capsule). Furthermore, the tablet formulation presented a lower dissolved fraction (F_d) and F_abs compared to the suspension formulation of AMX in RYGB patients (91.70% and 45.21% versus 99.92% and 54.43%, respectively). The AUC_0-inf and C_max were sensitive to changes in R_tintestine, Peff_AMX, and Transp for both healthy and RYGB models. Additionally, AUC_0-inf and C_max were also sensitive to changes in the t_lag parameter for tablet formulation in RYGB patients. The PBPK model showed a reduction in AMX bioavailability as a consequence of reduced intestinal length after RYGB surgery. Additionally, the difference in the predicted F_d and F_abs between suspension and tablet suggests that liquid formulations are preferable in postbariatric patients.

Drug Dose Selection in Pediatric Obesity: Available Information for the Most Commonly Prescribed Drugs to Children

Obesity rates continue to rise in children, and little guidance exists regarding the need for adjustment away from total body weight-based doses for those prescribing drugs to this population of children. A majority of drugs prescribed to children with obesity result in either sub-therapeutic or supra-therapeutic concentrations, placing these children at risk for treatment failure and drug toxicities. In this review, we highlight available obesity-specific pharmacokinetic and dosing information for the most frequently prescribed drugs to children in the inpatient and outpatient clinical settings. We also comment on available dosing recommendations for drugs prescribed to treat common pediatric obesity-related comorbidities. This review highlights that there is no safe or proven 'rule of thumb,' for dosing drugs for children with obesity, and a striking lack of pharmacokinetic data to support the creation of dosing guidelines for children with obesity for the most commonly prescribed drugs. It is important that those prescribing for children with obesity are aware of these gaps in knowledge and of potential drug treatment failure or adverse events related to drug toxicity as a result of these knowledge gaps. Until more data are available, we recommend close monitoring of drug response and adverse events in children with obesity receiving commonly prescribed drugs.

A Theoretical Physiologically-Based Pharmacokinetic Approach to Ascertain Covariates Explaining the Large Interpatient Variability in Tacrolimus Disposition

Physiologically‐based pharmacokinetic (PBPK) modeling allows assessment of the covariates contributing to the large pharmacokinetic (PK) variability of tacrolimus; these include multiple physiological and biochemical differences among patients. A PBPK model of tacrolimus was developed, including a virtual population with physiological parameter distributions reflecting renal transplant patients. The ratios of predicted to observed dose‐normalized maximum plasma concentration (C_max), 0–12‐hour area under the concentration–time curve (AUC_0–12 hour), and trough plasma concentration (C_trough) ranged from 0.92‐fold to 1.15‐fold, indicating good predictive performance. The model quantitatively indicated the impact of cytochrome P450 (CYP)3A4 abundance, hematocrit, and serum albumin levels, in addition to CYP3A5 genotype status, on tacrolimus PK and associated variability. Age‐dependent change in tacrolimus trough concentration in pediatric patients was mainly attributed to the CYP3A ontogeny profile. This study demonstrates the utility of PBPK modeling as a tool for mechanistic and quantitative assessment of the impact of patient physiological differences on observed large PK variability.

Patient-factors associated with metformin steady-state levels in type 2 diabetes mellitus with therapeutic dosage

AIMS

This prospective study aimed to analyze metformin steady-state concentration in repeated constant dosage and the influencing patient-factors as well as to correlate them with glycemic control.

METHODS

The validated HPLC-UV method was used to examine metformin steady-state concentration, while FBG and glycated albumin were used as the parameters of glycemic control during metformin administration.

RESULTS

A total of 82 type-2 diabetes patients were involved with 32.1% of them having metformin Cssmin and 84.1% having Cssmax of metformin within the recommended therapeutic range. One patient had metformin Css that exceeded minimum toxic concentration despite his normal renal function and administered therapeutic dosage of metformin. Higher Cssmax was found in patients with metformin monotherapy, while patients with longer duration of metformin use had significantly higher Cssmin.

CONCLUSIONS

Along with initial hyperglycemia and eGFR, metformin Cssmin became the only parameter that influenced FBG level (P < 0.05). Duration of previous metformin use should be considered in the strategy of optimizing metformin dosage. The type-2 diabetes patients with obesity are more suggested to take shorter interval of metformin administration (or possibly with sustained-release formulation) to keep Cssmin within the therapeutic range.

Effect of obesity on biodistribution of nanoparticles

Nanoparticles have specific features (lipophilicity, surface charge, composition and size). Studies regarding the biological behavior of nanoparticles in diseases such diabetics and obesity are scarce. Here, we evaluated two nanoparticles: magnetic core mesoporous silica (MSN) (58 nm) and polycaprolactone (PCL) nanoparticle (280 nm) in obese mice. Changes in the biodistribution were observed, especially considering the mononuclear phagocyte system (MPS), and the visceral fat tissue. Nonetheless, our data corroborates the influence of size in the biodistribution in obese animals, supporting that smaller nanoparticles, may show a higher tissue deposition at spleen, due the associated splenomegaly and the complications arising from this state. Finally, our study demonstrated that, in obesity, probably due the low-grade inflammatory state associated with metabolic syndrome a difference in accumulation of nanoparticles was found, with profound impact in the tissue deposition of nanoparticles.

Physiologically Based Pharmacokinetic Model Qualification and Reporting Procedures for Regulatory Submissions: A Consortium Perspective

This work provides a perspective on the qualification and verification of physiologically based pharmacokinetic (PBPK) platforms/models intended for regulatory submission based on the collective experience of the Simcyp Consortium members. Examples of regulatory submission of PBPK analyses across various intended applications are presented and discussed. European Medicines Agency (EMA) and US Food and Drug Administration (FDA) recent draft guidelines regarding PBPK analyses and reporting are encouraging, and to advance the use and acceptability of PBPK analyses, more clarity and flexibility are warranted.

Pharmacokinetic interactions and dosing rationale for antiepileptic drugs in adults and children

AIMS

Population pharmacokinetic modelling has been widely used across many therapeutic areas to identify sources of variability, which are incorporated into models as covariate factors. Despite numerous publications on pharmacokinetic drug-drug interactions (DDIs) between antiepileptic drugs (AEDs), such data are not used to support the dose rationale for polytherapy in the treatment of epileptic seizures. Here we assess the impact of DDIs on plasma concentrations and evaluate the need for AED dose adjustment.

METHODS

Models describing the pharmacokinetics of carbamazepine, clobazam, clonazepam, lamotrigine, levetiracetam, oxcarbazepine, phenobarbital, phenytoin, topiramate, valproic acid and zonisamide in adult and paediatric patients were collected from the published literature and implemented in NONMEM v7.2. Taking current clinical practice into account, we explore simulation scenarios to characterize AED exposure in virtual patients receiving mono- and polytherapy. Steady-state, maximum and minimum concentrations were selected as parameters of interest for this analysis.

RESULTS

Our simulations show that DDIs can cause major changes in AED concentrations both in adults and children. When more than one AED is used, even larger changes are observed in the concentrations of the primary drug, leading to significant differences in steady-state concentration between mono- and polytherapy for most AEDs. These results suggest that currently recommended dosing algorithms and titration procedures do not ensure attainment of appropriate therapeutic concentrations.

CONCLUSIONS

The effect of DDIs on AED exposure cannot be overlooked. Clinical guidelines must consider such covariate effects and ensure appropriate dosing recommendations for adult and paediatric patients who require combination therapy.

Morbidity and mortality associated with obesity

Obesity and its repercussions constitute an important source of morbidity, impaired quality of life and its complications can have a major bearing on life expectancy. The present article summarizes the most important co-morbidities of obesity and their prevalence. Furthermore, it describes classification and grading systems that can be used to assess the individual and combined impact of co-morbid conditions on mortality risk. The literature was screened for assessment tools that can be deployed in the quantification of morbidity and mortality risk in individual patients. Thirteen specific domains have been identified that account for morbidity and mortality in obesity. Cardiovascular disease (CVD) and cancer account for the greatest mortality risk associated with obesity. The King's Criteria and Edmonton Obesity Staging System (EOSS) were identified as useful tools for the detection and monitoring of individual patient mortality risk in obesity care. The stark facts on the complications of obesity should be capitalized on to improve patient management and knowledge and referred to in the wider dissemination of public health messages aimed at improving primary prevention.

Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine

Personalized medicine strives to deliver the 'right drug at the right dose' by considering inter-person variability, one of the causes for therapeutic failure in specialized populations of patients. Physiologically-based pharmacokinetic (PBPK) modeling is a key tool in the advancement of personalized medicine to evaluate complex clinical scenarios, making use of physiological information as well as physicochemical data to simulate various physiological states to predict the distribution of pharmacokinetic responses. The increased dependency on PBPK models to address regulatory questions is aligned with the ability of PBPK models to minimize ethical and technical difficulties associated with pharmacokinetic and toxicology experiments for special patient populations. Subpopulation modeling can be achieved through an iterative and integrative approach using an adopt, adapt, develop, assess, amend, and deliver methodology. PBPK modeling has two valuable applications in personalized medicine: (1) determining the importance of certain subpopulations within a distribution of pharmacokinetic responses for a given drug formulation and (2) establishing the formulation design space needed to attain a targeted drug plasma concentration profile. This review article focuses on model development for physiological differences associated with sex (male vs. female), age (pediatric vs. young adults vs. elderly), disease state (healthy vs. unhealthy), and temporal variation (influence of biological rhythms), connecting them to drug product formulation development within the quality by design framework. Although PBPK modeling has come a long way, there is still a lengthy road before it can be fully accepted by pharmacologists, clinicians, and the broader industry.

Prediction of Drug-Drug Interactions Arising from CYP3A induction Using a Physiologically Based Dynamic Model

Using physiologically based pharmacokinetic modeling, we predicted the magnitude of drug-drug interactions (DDIs) for studies with rifampicin and seven CYP3A4 probe substrates administered i.v. (10 studies) or orally (19 studies). The results showed a tendency to underpredict the DDI magnitude when the victim drug was administered orally. Possible sources of inaccuracy were investigated systematically to determine the most appropriate model refinement. When the maximal fold induction (Ind_max) for rifampicin was increased (from 8 to 16) in both the liver and the gut, or when the Ind_max was increased in the gut but not in liver, there was a decrease in bias and increased precision compared with the base model (Ind_max = 8) [geometric mean fold error (GMFE) 2.12 vs. 1.48 and 1.77, respectively]. Induction parameters (mRNA and activity), determined for rifampicin, carbamazepine, phenytoin, and phenobarbital in hepatocytes from four donors, were then used to evaluate use of the refined rifampicin model for calibration. Calibration of mRNA and activity data for other inducers using the refined rifampicin model led to more accurate DDI predictions compared with the initial model (activity GMFE 1.49 vs. 1.68; mRNA GMFE 1.35 vs. 1.46), suggesting that robust in vivo reference values can be used to overcome interdonor and laboratory-to-laboratory variability. Use of uncalibrated data also performed well (GMFE 1.39 and 1.44 for activity and mRNA). As a result of experimental variability (i.e., in donors and protocols), it is prudent to fully characterize in vitro induction with prototypical inducers to give an understanding of how that particular system extrapolates to the in vivo situation when using an uncalibrated approach.

The Ontogeny and Population Variability of Human Hepatic NADPH Dehydrogenase Quinone Oxido-Reductase 1 (NQO1)

The NADPH dehydrogenase quinone oxido-reductase 1 (NQO1) enzyme is an antioxidant and metabolic enzyme that performs two electron reduction of quinones and other chemicals. Based on the physiologic role(s) of NQO1, we hypothesized that expression and activity of this enzyme would vary with age and other demographic variables. Cytosols from 117 archived human livers were investigated for changes in NQO1 with age, sex, obesity, and ethnicity. Protein expression but not activity of NQO1 was weakly negatively correlated with age (Spearman r = -0.2, P = 0.03). No sex differences were observed for either protein expression or activity and for ethnicity; Caucasians had greater NQO1 activity than Asians (P < 0.05). Overweight children had statistically significantly higher NQO1 activity as compared with ideal weight children (P < 0.05) although this difference was not observed in adults. These findings establish that NQO1 is approximately as active in children as adults. However, modeled NQO1 clearance (both allometric and physiologically based pharmacokinetics) predicted maturation at 23 to 26 years. This is almost certainly an overestimate, with error in the model resulting from a small sample size and inability to scale for age-related changes in hepatic cellularity and/or cytosolic protein content, and indicates a delay in reaching maximum clearance through the NQO1 pathway that is affected by physiologic development as much, or more than, biochemical development. Obesity may increase hepatic NQO1 activity in children, which is likely a protective mechanism in oxidative stress, but may also have significant implications for drug and chemical disposition in obese children.

Semiphysiologically based pharmacokinetic model for midazolam and CYP3A mediated metabolite 1-OH-midazolam in morbidly obese and weight loss surgery patients

This study aimed to describe the pharmacokinetics of midazolam and its cytochrome P450 3A (CYP3A) mediated metabolite 1‐OH‐midazolam in morbidly obese patients receiving oral and i.v. midazolam before (n = 20) and one year after weight loss surgery (n = 18), thereby providing insight into the influence of weight loss surgery on CYP3A activity in the gut wall and liver. In a semiphysiologically based pharmacokinetic (semi‐PBPK) model in which different blood flow scenarios were evaluated, intrinsic hepatic clearance of midazolam (CL_int,H) was 2 (95% CI 1.40–1.64) times higher compared to morbidly obese patients before surgery (P < 0.01). Midazolam gut wall clearance (CL_int,G) was slightly lower in patients after surgery (P > 0.05), with low values for both groups. The results of the semi‐PBPK model suggest that, in patients after weight loss surgery, CYP3A hepatic metabolizing capacity seems to recover compared to morbidly obese patients, whereas CYP3A mediated CL_int,G was low for both populations and showed large interindividual variability.