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Yang R, Ding Q, Ding J, Zhu L, Pei Q. Physiologically based pharmacokinetic modeling in obesity: applications and challenges. Expert Opin Drug Metab Toxicol 2024:1-12. [PMID: 39101366 DOI: 10.1080/17425255.2024.2388690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 07/11/2024] [Accepted: 08/01/2024] [Indexed: 08/06/2024]
Abstract
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.
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Affiliation(s)
- Ruwei Yang
- Department of Pharmacy, The Third XiangyHospital, Central South University, Changsha, Hunan, China
| | - Qin Ding
- Department of Pharmacy, The Third XiangyHospital, Central South University, Changsha, Hunan, China
| | - Junjie Ding
- Center for Tropical Medicine and Global Health, Oxford Medical School, Oxford, UK
| | - Liyong Zhu
- Department of Gastrointestinal Surgery, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Qi Pei
- Department of Pharmacy, The Third XiangyHospital, Central South University, Changsha, Hunan, China
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Kinoshita K, Moore G, Murakami M. Body Weight as a Preferred Method for Normalizing the Computed Tomography-Derived Liver Volume in Dogs without Hepatic Disease. Vet Sci 2024; 11:153. [PMID: 38668420 PMCID: PMC11054289 DOI: 10.3390/vetsci11040153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 03/13/2024] [Accepted: 03/25/2024] [Indexed: 04/29/2024] Open
Abstract
The assessment of liver size is usually performed using radiography in dogs. However, due to wide variations in patients' sizes and body conformations, accurate diagnosis of hepatomegaly or microhepatia is difficult. Computed tomographic (CT) volumetry can quantitatively and accurately measure liver volume. However, a reliable method for the standardization or normalization of volume in dogs without hepatic disease using CT has not yet been established. The purpose of this study was to assess seven different anatomic measures for normalizing liver volume in dogs and determine the tentative range of liver volume in dogs without hepatic disease. We retrospectively searched medical records from 1 January 2017 through to 1 June 2020 and included dogs with abdominal computed tomography without hepatic disease. The liver volume, lengths of four vertebrae (T11, T12, L2, L3), diameter of the abdominal aorta, body weight, and body condition scores (BCSs) of the dogs were recorded. Forty-one client-owned dogs without evidence of hepatic disease were included. The CT-derived liver volume was 813.8 ± 326.5 cm3 (mean ± SD). Body weight was determined to be the most reliable single-variable method for normalizing liver volume, with a raw CT-derived liver-volume-to-body-weight ratio of 22.1 cm3/kg (95% CI: 12.9-31.3 cm3/kg) and regression prediction model of volume = 19 × BWkg + 97. However, a better normalizing factor would likely be provided by the fat-free mass if it can be accurately measured.
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Affiliation(s)
- Kosuke Kinoshita
- Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA
| | - George Moore
- Department of Veterinary Administration, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA
| | - Masahiro Murakami
- Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN 47907, USA
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Machado TR, Honorio T, Souza Domingos TF, Candido de Paula DDS, Cabral LM, Rodrigues CR, Abrahim-Vieira BA, Teles de Souza AM. Physiologically based pharmacokinetic modelling of semaglutide in children and adolescents with healthy and obese body weights. Br J Clin Pharmacol 2023; 89:3175-3194. [PMID: 37293836 DOI: 10.1111/bcp.15816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 04/23/2023] [Accepted: 05/31/2023] [Indexed: 06/10/2023] Open
Abstract
AIMS To develop paediatric physiologically based pharmacokinetic modelling (PBPK) models of semaglutide to estimate the pharmacokinetic profile for subcutaneous injections in children and adolescents with healthy and obese body weights. METHODS Pharmacokinetic modelling and simulations of semaglutide subcutaneous injections were performed using the Transdermal Compartmental Absorption & Transit model implemented in GastroPlus v.9.5 modules. A PBPK model of semaglutide was developed and verified in the adult population, by comparing the simulated plasma exposure with the observed data, and further scaled to the paediatric populations with normal and obese body weight. RESULTS The semaglutide PBPK model was successfully developed in adults and scaled to the paediatric population. Our paediatric PBPK simulations indicated a significant increase in maximum plasma concentrations for the 10-14 years' paediatric population with healthy body weights, which was higher than the observed values in adults at the reference dose. Since gastrointestinal adverse events are related to increased semaglutide concentrations, peak concentrations outside the target range may represent a safety risk for this paediatric age group. Besides, paediatric PBPK models indicated that body weight was inversely related to semaglutide maximum plasma concentration, corroborating the consensus on the influence of body weight on semaglutide PK in adults. CONCLUSION Paediatric PBPK was successfully achieved using a top-down approach and drug-related parameters. The development of unprecedented PBPK models will support paediatric clinical therapy for applying aid-safe dosing regimens for the paediatric population in diabetes treatment.
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Affiliation(s)
- Thayná Rocco Machado
- Laboratory of Molecular Modeling & QSAR (ModMolQSAR), Faculty of Pharmacy, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Thiago Honorio
- Laboratory of Molecular Modeling & QSAR (ModMolQSAR), Faculty of Pharmacy, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Dailane da Silva Candido de Paula
- Laboratory of Molecular Modeling & QSAR (ModMolQSAR), Faculty of Pharmacy, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Lucio Mendes Cabral
- Laboratory of Molecular Modeling & QSAR (ModMolQSAR), Faculty of Pharmacy, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Carlos R Rodrigues
- Laboratory of Molecular Modeling & QSAR (ModMolQSAR), Faculty of Pharmacy, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Bárbara A Abrahim-Vieira
- Laboratory of Molecular Modeling & QSAR (ModMolQSAR), Faculty of Pharmacy, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Alessandra Mendonça Teles de Souza
- Laboratory of Molecular Modeling & QSAR (ModMolQSAR), Faculty of Pharmacy, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
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Rower JE, McKnite A, Hong B, Daly KP, Hope KD, Cabrera AG, Molina KM. External assessment and refinement of a population pharmacokinetic model to guide tacrolimus dosing in pediatric heart transplant. Pharmacotherapy 2023; 43:650-658. [PMID: 37328271 PMCID: PMC10527671 DOI: 10.1002/phar.2836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 05/03/2023] [Accepted: 05/03/2023] [Indexed: 06/18/2023]
Abstract
STUDY OBJECTIVE The immunosuppressant tacrolimus is a first-line agent to prevent graft rejection following pediatric heart transplant; however, it suffers from extensive inter-patient variability and a narrow therapeutic window. Personalized tacrolimus dosing may improve transplant outcomes by more efficiently achieving and maintaining therapeutic tacrolimus concentrations. We sought to externally validate a previously published population pharmacokinetic (PK) model that was constructed with data from a single site. DATA SOURCE Data were collected from Seattle, Texas, and Boston Children's Hospitals, and assessed using standard population PK modeling techniques in NONMEMv7.2. MAIN RESULTS While the model was not successfully validated for use with external data, further covariate searching identified weight (p < 0.0001 on both volume and elimination rate) as a model-significant covariate. This refined model acceptably predicted future tacrolimus concentrations when guided by as few as three concentrations (median prediction error = 7%; median absolute prediction error = 27%). CONCLUSION These findings support the potential clinical utility of a population PK model to provide personalized tacrolimus dosing guidance.
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Affiliation(s)
- Joseph E. Rower
- Department of Pharmacology and Toxicology, University of Utah College of Pharmacy, Salt Lake City, Utah, USA
- Center for Human Toxicology, University of Utah College of Pharmacy, Salt Lake City, Utah, USA
| | - Autumn McKnite
- Department of Pharmacology and Toxicology, University of Utah College of Pharmacy, Salt Lake City, Utah, USA
| | - Borah Hong
- Division of Pediatric Cardiology, University of Washington and Seattle Children’s Hospital, Seattle, Washington, USA
| | - Kevin P. Daly
- Department of Pediatric Cardiology, Harvard Medical School/Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Kyle D. Hope
- Lillie Frank Abercrombie Division of Pediatric Cardiology, Department of Pediatrics, Texas Children’s Hospital, Baylor College of Medicine, Houston, Texas, USA
| | - Antonio G. Cabrera
- Lillie Frank Abercrombie Division of Pediatric Cardiology, Department of Pediatrics, Texas Children’s Hospital, Baylor College of Medicine, Houston, Texas, USA
- Division of Pediatric Cardiology, University of Utah/Intermountain Primary Children’s Hospital, Salt Lake City, Utah, USA
| | - Kimberly M. Molina
- Division of Pediatric Cardiology, University of Utah/Intermountain Primary Children’s Hospital, Salt Lake City, Utah, USA
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Guerra Valero YC, Dorofaeff T, Coulthard MG, Sparkes L, Lipman J, Wallis SC, Roberts JA, Parker SL. Optimal dosing of cefotaxime and desacetylcefotaxime for critically ill paediatric patients. Can we use microsampling? J Antimicrob Chemother 2022; 77:2227-2237. [PMID: 35678266 PMCID: PMC9333413 DOI: 10.1093/jac/dkac168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 04/25/2022] [Indexed: 11/30/2022] Open
Abstract
Objectives To describe the population pharmacokinetics of cefotaxime and desacetylcefotaxime in critically ill paediatric patients and provide dosing recommendations. We also sought to evaluate the use of capillary microsampling to facilitate data-rich blood sampling. Methods Patients were recruited into a pharmacokinetic study, with cefotaxime and desacetylcefotaxime concentrations from plasma samples collected at 0, 0.5, 2, 4 and 6 h used to develop a population pharmacokinetic model using Pmetrics. Monte Carlo dosing simulations were tested using a range of estimated glomerular filtration rates (60, 100, 170 and 200 mL/min/1.73 m2) and body weights (4, 10, 15, 20 and 40 kg) to achieve pharmacokinetic/pharmacodynamic (PK/PD) targets, including 100% ƒT>MIC with an MIC breakpoint of 1 mg/L. Results Thirty-six patients (0.2–12 years) provided 160 conventional samples for inclusion in the model. The pharmacokinetics of cefotaxime and desacetylcefotaxime were best described using one-compartmental model with first-order elimination. The clearance and volume of distribution for cefotaxime were 12.8 L/h and 39.4 L, respectively. The clearance for desacetylcefotaxime was 10.5 L/h. Standard dosing of 50 mg/kg q6h was only able to achieve the PK/PD target of 100% ƒT>MIC in patients >10 kg and with impaired renal function or patients of 40 kg with normal renal function. Conclusions Dosing recommendations support the use of extended or continuous infusion to achieve cefotaxime exposure suitable for bacterial killing in critically ill paediatric patients, including those with severe or deep-seated infection. An external validation of capillary microsampling demonstrated skin-prick sampling can facilitate data-rich pharmacokinetic studies.
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Affiliation(s)
| | - Tavey Dorofaeff
- UQ Centre for Clinical Research, The University of Queensland, Brisbane, Australia.,Paediatric Intensive Care, Queensland Children's Hospital, Brisbane, Australia
| | - Mark G Coulthard
- Paediatric Intensive Care, Queensland Children's Hospital, Brisbane, Australia.,Mayne Academy of Paediatrics, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Louise Sparkes
- Paediatric Intensive Care, Queensland Children's Hospital, Brisbane, Australia
| | - Jeffrey Lipman
- UQ Centre for Clinical Research, The University of Queensland, Brisbane, Australia.,Department of Intensive Care Medicine, Royal Brisbane & Women's Hospital, Brisbane, Australia.,Jamieson Trauma Institute, Royal Brisbane & Women's Hospital, Herston, QLD 4029, Australia
| | - Steven C Wallis
- UQ Centre for Clinical Research, The University of Queensland, Brisbane, Australia
| | - Jason A Roberts
- UQ Centre for Clinical Research, The University of Queensland, Brisbane, Australia.,Department of Intensive Care Medicine, Royal Brisbane & Women's Hospital, Brisbane, Australia.,Department of Pharmacy, Royal Brisbane & Women's Hospital, Brisbane, Australia
| | - Suzanne L Parker
- UQ Centre for Clinical Research, The University of Queensland, Brisbane, Australia
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Hosey CM, Halpin K, Shakhnovich V, Bi C, Sweeney B, Yan Y, Leeder JS. Pediatric growth patterns in youth-onset type 2 diabetes mellitus: Implications for physiologically-based pharmacokinetic models. Clin Transl Sci 2022; 15:912-922. [PMID: 35297172 PMCID: PMC9010268 DOI: 10.1111/cts.13207] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 11/04/2021] [Accepted: 11/10/2021] [Indexed: 11/27/2022] Open
Abstract
An accurate understanding of the changes in height and weight of children with age is critical to the development of models predicting drug concentrations in children (i.e., physiologically‐based pharmacokinetic models). However, curves describing the growth of a typical population of children may not accurately characterize growth of children with various conditions, such as obesity. Therefore, to develop height and weight versus age growth curves for youth who were diagnosed with type 2 diabetes, we extracted data from electronic medical records. Robust nonlinear models were parameterized to the equations describing height and weight versus age as defined by the Centers for Disease Control and Prevention (CDC). CDC z‐scores were calculated using an internal program. The growth curves and z‐scores were compared to CDC norms. Youth with type 2 diabetes were increasingly heavier than CDC norms from early childhood. Except for a period around puberty, youth with type 2 diabetes were, on average, shorter than CDC norms, resulting in shorter average adult height. Deviations in growth were apparent in youth who develop type 2 diabetes; such deviations may be expected for other conditions as well, and disease‐specific growth curves should be considered during development of model‐informed drug development for pediatric conditions.
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Affiliation(s)
| | - Kelsee Halpin
- Children's Mercy Kansas City, Kansas City, Missouri, USA.,University of Missouri-Kansas City School of Medicine, Kansas City, Missouri, USA
| | - Valentina Shakhnovich
- Children's Mercy Kansas City, Kansas City, Missouri, USA.,University of Missouri-Kansas City School of Medicine, Kansas City, Missouri, USA.,University of Kansas Medical Center, Kansas City, Kansas, USA.,Center for Children's Healthy Lifestyles & Nutrition, Kansas City, Missouri, USA
| | - Chengpeng Bi
- Children's Mercy Kansas City, Kansas City, Missouri, USA
| | - Brooke Sweeney
- Children's Mercy Kansas City, Kansas City, Missouri, USA.,University of Missouri-Kansas City School of Medicine, Kansas City, Missouri, USA.,Center for Children's Healthy Lifestyles & Nutrition, Kansas City, Missouri, USA
| | - Yun Yan
- Children's Mercy Kansas City, Kansas City, Missouri, USA.,University of Missouri-Kansas City School of Medicine, Kansas City, Missouri, USA
| | - J Steven Leeder
- Children's Mercy Kansas City, Kansas City, Missouri, USA.,University of Missouri-Kansas City School of Medicine, Kansas City, Missouri, USA.,University of Kansas Medical Center, Kansas City, Kansas, USA
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