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D’Ambrosio A, Itaj F, Cacace F, Piemonte V. Mathematical Modeling of the Gastrointestinal System for Preliminary Drug Absorption Assessment. Bioengineering (Basel) 2024; 11:813. [PMID: 39199771 PMCID: PMC11352181 DOI: 10.3390/bioengineering11080813] [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: 06/01/2024] [Revised: 07/31/2024] [Accepted: 08/05/2024] [Indexed: 09/01/2024] Open
Abstract
The objective of this study is to demonstrate the potential of a multicompartmental mathematical model to simulate the activity of the gastrointestinal system after the intake of drugs, with a limited number of parameters. The gastrointestinal system is divided into five compartments, modeled as both continuous systems with discrete events (stomach and duodenum) and systems with delay (jejunum, ileum, and colon). The dissolution of the drug tablet occurs in the stomach and is described through the Noyes-Whitney equation, with pH dependence expressed through the Henderson-Hasselbach relationship. The boluses resulting from duodenal activity enter the jejunum, ileum, and colon compartments, where drug absorption takes place as blood flows countercurrent. The model includes only three parameters with assigned physiological meanings. It was tested and validated using data from in vivo experiments. Specifically, the model was tested with the concentration profiles of nine different drugs and validated using data from two drugs with varying initial concentrations. Overall, the outputs of the model are in good agreement with experimental data, particularly with regard to the time of peak concentration. The primary sources of discrepancy were identified in the concentration decay. The model's main strength is its relatively low computational cost, making it a potentially excellent tool for in silico assessment and prediction of drug adsorption in the intestine.
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Affiliation(s)
- Antonio D’Ambrosio
- Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Science and Technology for Sustainable Development and One Health, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy; (F.I.); (V.P.)
| | - Fatjon Itaj
- Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Science and Technology for Sustainable Development and One Health, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy; (F.I.); (V.P.)
| | - Filippo Cacace
- Research Unit of Computer Systems and Bioinformatics, Department of Engineering, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy;
| | - Vincenzo Piemonte
- Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Science and Technology for Sustainable Development and One Health, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy; (F.I.); (V.P.)
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Cao X, Li K, Wang J, Xie X, Sun L. PBPK model of pegylated liposomal doxorubicin to simultaneously predict the concentration-time profile of encapsulated and free doxorubicin in tissues. Drug Deliv Transl Res 2024:10.1007/s13346-024-01680-0. [PMID: 39103592 DOI: 10.1007/s13346-024-01680-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/20/2024] [Indexed: 08/07/2024]
Abstract
The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict the concentrations of encapsulated and free doxorubicin in plasma and tissues in mice after intravenous injection of PEGylated liposomes (Doxil®). The PBPK model used in this study contains liposomes and free doxorubicin disposition components. The free doxorubicin disposition component was used to simulate the disposition of free doxorubicin produced by mononuclear phagocyte system (MPS)-degrading liposomes. The liver, spleen, kidneys, and lungs contain an additional MPS subcompartment. These compartments are interconnected through blood and lymphatic circulation. The model was validated strictly by four doses of external observed plasma and tissue concentration-time profiles. The fold error (FE) values were almost all within threefold. The sensitivity analysis revealed that the MPS-related parameters greatly influenced the model. The predicted in vivo distribution characteristics of the doxorubicin liposomes and doxorubicin solution were consistent with the observed values. The PBPK model was established based on the physiological mechanism and parameters of practical significance that can be measured in vitro. Thus, it can be used to study the pharmacokinetic properties of liposomes. This study also provides a reference for the establishment of liposome PBPK model.
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Affiliation(s)
- Xuewei Cao
- Department of Pharmaceutics, School of Pharmacy, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, China
| | - Kejun Li
- China Medical University-The Queen's University of Belfast Joint College, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, China
| | - Jingyu Wang
- Department of Pharmaceutics, School of Pharmacy, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, China
| | - Xiaoqian Xie
- Department of Pharmaceutics, School of Pharmacy, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, China
| | - Le Sun
- Department of Pharmaceutics, School of Pharmacy, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, China.
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Thépaut E, Bisson M, Brochot C, Personne S, Appenzeller BMR, Zaros C, Chardon K, Zeman F. PBPK modeling to support risk assessment of pyrethroid exposure in French pregnant women. ENVIRONMENTAL RESEARCH 2024; 251:118606. [PMID: 38460660 DOI: 10.1016/j.envres.2024.118606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 03/11/2024]
Abstract
BACKGROUND Pyrethroids are widely used pesticides and are suspected to affect children's neurodevelopment. The characterization of pyrethroid exposure during critical windows of development, such as fetal development and prenatal life, is essential to ensure a better understanding of pyrethroids potential effects within the concept of Developmental Origins of Health and Disease. OBJECTIVE The aim of this study was to estimate maternal exposure of French pregnant women from biomonitoring data and simulate maternal and fetal internal concentrations of 3 pyrethroids (permethrin, cypermethrin and deltamethrin) using a multi-substance pregnancy-PBPK (physiologically based pharmacokinetics) model. The estimated maternal exposures were compared to newly proposed toxicological reference values (TRV) children specific also called draft child-specific reference value to assess pyrethroid exposure risk during pregnancy i.e. during the in utero exposure period. METHODS A pregnancy-PBPK model was developed based on an existing adult pyrethroids model. The maternal exposure to each parent compound of pregnant women of the Elfe (French Longitudinal Study since Childhood) cohort was estimated by reverse dosimetry based on urinary biomonitoring data. To identify permethrin and cypermethrin contribution to their common urinary biomarkers of exposure, an exposure ratio based on biomarkers in hair was tested. Finally, exposure estimates were compared to current and draft child-specific reference values derived from rodent prenatal and postnatal exposure studies. RESULTS The main contributor to maternal pyrethroid diet intake is cis-permethrin. In blood, total internal concentrations main contributor is deltamethrin. In brain, the major contributors to internal pyrethroid exposure are deltamethrin for fetuses and cis-permethrin for mothers. Risk is identified only for permethrin when referring to the draft child-specific reference value. 2.5% of the population exceeded permethrin draft child-specific reference value. CONCLUSIONS A new reverse dosimetry approach using PBPK model combined with human biomonitoring data in urine and hair was proposed to estimate Elfe pregnant population exposure to a pyrethroids mixture with common metabolites.
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Affiliation(s)
- Elisa Thépaut
- Unité Toxicologie ExpérimentAle et Modélisation / Péritox (UMR_I 01), INERIS/UPJV, Institut National de l'Environnement Industriel et des Risques, 60550, Verneuil-en-Halatte, France
| | - Michèle Bisson
- Unité Expertise en Toxicologie / écotoxicologie des Substances Chimiques, INERIS, Institut National de l'Environnement Industriel et des Risques, 60550, Verneuil-en-Halatte, France
| | - Céline Brochot
- Unité Toxicologie ExpérimentAle et Modélisation / Péritox (UMR_I 01), INERIS/UPJV, Institut National de l'Environnement Industriel et des Risques, 60550, Verneuil-en-Halatte, France; Current affiliation: Certara UK Ltd, Simcyp Division, Sheffield, UK
| | - Stéphane Personne
- Péritox (UMR_I 01), UPJV/INERIS, Université de Picardie Jules Verne, 80025, Amiens, France
| | - Brice M R Appenzeller
- Human Biomonitoring Research Unit, Department of Precision Health, Luxembourg Institute of Health, 1 A-B rue Thomas Edison, L-1445, Strassen, Luxembourg
| | - Cécile Zaros
- UMS Elfe, INED French Institute for Demographic Studies, 93322, Aubervilliers CEDEX, France
| | - Karen Chardon
- Péritox (UMR_I 01), UPJV/INERIS, Université de Picardie Jules Verne, 80025, Amiens, France
| | - Florence Zeman
- Unité Toxicologie ExpérimentAle et Modélisation / Péritox (UMR_I 01), INERIS/UPJV, Institut National de l'Environnement Industriel et des Risques, 60550, Verneuil-en-Halatte, France.
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Huang H, Zhao W, Qin N, Duan X. Recent Progress on Physiologically Based Pharmacokinetic (PBPK) Model: A Review Based on Bibliometrics. TOXICS 2024; 12:433. [PMID: 38922113 PMCID: PMC11209072 DOI: 10.3390/toxics12060433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 06/04/2024] [Accepted: 06/13/2024] [Indexed: 06/27/2024]
Abstract
Physiologically based pharmacokinetic/toxicokinetic (PBPK/PBTK) models are designed to elucidate the mechanism of chemical compound action in organisms based on the physiological, biochemical, anatomical, and thermodynamic properties of organisms. After nearly a century of research and practice, good results have been achieved in the fields of medicine, environmental science, and ecology. However, there is currently a lack of a more systematic review of progress in the main research directions of PBPK models, especially a more comprehensive understanding of the application in aquatic environmental research. In this review, a total of 3974 articles related to PBPK models from 1996 to 24 March 2024 were collected. Then, the main research areas of the PBPK model were categorized based on the keyword co-occurrence maps and cluster maps obtained by CiteSpace. The results showed that research related to medicine is the main application area of PBPK. Four major research directions included in the medical field were "drug assessment", "cross-species prediction", "drug-drug interactions", and "pediatrics and pregnancy drug development", in which "drug assessment" accounted for 55% of the total publication volume. In addition, bibliometric analyses indicated a rapid growth trend in the application in the field of environmental research, especially in predicting the residual levels in organisms and revealing the relationship between internal and external exposure. Despite facing the limitation of insufficient species-specific parameters, the PBPK model is still an effective tool for improving the understanding of chemical-biological effectiveness and will provide a theoretical basis for accurately assessing potential risks to ecosystems and human health. The combination with the quantitative structure-activity relationship model, Bayesian method, and machine learning technology are potential solutions to the previous research gaps.
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Affiliation(s)
| | | | - Ning Qin
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China; (H.H.); (W.Z.)
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China; (H.H.); (W.Z.)
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Chao FC, Manaia EB, Ponchel G, Hsieh CM. A physiologically-based pharmacokinetic model for predicting doxorubicin disposition in multiple tissue levels and quantitative toxicity assessment. Biomed Pharmacother 2023; 168:115636. [PMID: 37826938 DOI: 10.1016/j.biopha.2023.115636] [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: 07/20/2023] [Revised: 09/22/2023] [Accepted: 10/03/2023] [Indexed: 10/14/2023] Open
Abstract
Doxorubicin is a widely-used chemotherapeutic drug, however its high toxicity poses a significant challenge for its clinical use. To address this issue, a physiologically-based pharmacokinetic (PBPK) model was implemented to quantitatively assess doxorubicin toxicity at cellular scale. Due to its unique pharmacokinetic behavior (e.g. high volume of distribution and affinity to extra-plasma tissue compartments), we proposed a modified PBPK model structure and developed the model with multispecies extrapolation to compensate for the limitation of obtaining clinical tissue data. Our model predicted the disposition of doxorubicin in multiple tissues including clinical tissue data with an overall absolute average fold error (AAFE) of 2.12. The model's performance was further validated with 8 clinical datasets in combined with intracellular doxorubicin concentration with an average AAFE of 1.98. To assess the potential cellular toxicity, toxicity levels and area under curve (AUC) were defined for different dosing regimens in toxic and non-toxic scenarios. The cellular concentrations of doxorubicin in multiple organ sites associated with commonly observed adverse effects (AEs) were simulated and calculated the AUC for quantitative assessments. Our findings supported the clinical dosing regimen of 75 mg/m2 with a 21-day interval and suggest that slow infusion and separated single high doses may lower the risk of developing AEs from a cellular level, providing valuable insights for the risk assessment of doxorubicin chemotherapy. In conclusion, our work highlights the potential of PBPK modelling to provide quantitative assessments of cellular toxicity and supports the use of clinical dosing regimens to mitigate the risk of adverse effects.
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Affiliation(s)
- Fang-Ching Chao
- CNRS UMR 8612, Institut Galien Paris-Saclay, Université Paris-Saclay, Orsay 91400, France
| | - Eloísa Berbel Manaia
- CNRS UMR 8612, Institut Galien Paris-Saclay, Université Paris-Saclay, Orsay 91400, France
| | - Gilles Ponchel
- CNRS UMR 8612, Institut Galien Paris-Saclay, Université Paris-Saclay, Orsay 91400, France.
| | - Chien-Ming Hsieh
- School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan; Ph.D. Program in Drug Discovery and Development Industry, College of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan.
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Chen M, Du R, Zhang T, Li C, Bao W, Xin F, Hou S, Yang Q, Chen L, Wang Q, Zhu A. The Application of a Physiologically Based Toxicokinetic Model in Health Risk Assessment. TOXICS 2023; 11:874. [PMID: 37888724 PMCID: PMC10611306 DOI: 10.3390/toxics11100874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/17/2023] [Accepted: 10/19/2023] [Indexed: 10/28/2023]
Abstract
Toxicokinetics plays a crucial role in the health risk assessments of xenobiotics. Classical compartmental models are limited in their ability to determine chemical concentrations in specific organs or tissues, particularly target organs or tissues, and their limited interspecific and exposure route extrapolation hinders satisfactory health risk assessment. In contrast, physiologically based toxicokinetic (PBTK) models quantitatively describe the absorption, distribution, metabolism, and excretion of chemicals across various exposure routes and doses in organisms, establishing correlations with toxic effects. Consequently, PBTK models serve as potent tools for extrapolation and provide a theoretical foundation for health risk assessment and management. This review outlines the construction and application of PBTK models in health risk assessment while analyzing their limitations and future perspectives.
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Affiliation(s)
- Mengting Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Ruihu Du
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
| | - Tao Zhang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
| | - Chutao Li
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Wenqiang Bao
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Fan Xin
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Shaozhang Hou
- Department of Pathology, School of Basic Medical Sciences, Ningxia Medical University, Yinchuan 750004, China
| | - Qiaomei Yang
- Department of Gynecology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou 350001, China
| | - Li Chen
- Department of Gynecology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou 350001, China
| | - Qi Wang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
- Key Laboratory of State Administration of Traditional Chinese Medicine for Compatibility Toxicology, Beijing 100191, China
- Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, China
| | - An Zhu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
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Witzany C, Rolff J, Regoes RR, Igler C. The pharmacokinetic-pharmacodynamic modelling framework as a tool to predict drug resistance evolution. MICROBIOLOGY (READING, ENGLAND) 2023; 169:001368. [PMID: 37522891 PMCID: PMC10433423 DOI: 10.1099/mic.0.001368] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 07/12/2023] [Indexed: 08/01/2023]
Abstract
Pharmacokinetic-pharmacodynamic (PKPD) models, which describe how drug concentrations change over time and how that affects pathogen growth, have proven highly valuable in designing optimal drug treatments aimed at bacterial eradication. However, the fast rise of antimicrobial resistance calls for increased focus on an additional treatment optimization criterion: avoidance of resistance evolution. We demonstrate here how coupling PKPD and population genetics models can be used to determine treatment regimens that minimize the potential for antimicrobial resistance evolution. Importantly, the resulting modelling framework enables the assessment of resistance evolution in response to dynamic selection pressures, including changes in antimicrobial concentration and the emergence of adaptive phenotypes. Using antibiotics and antimicrobial peptides as an example, we discuss the empirical evidence and intuition behind individual model parameters. We further suggest several extensions of this framework that allow a more comprehensive and realistic prediction of bacterial escape from antimicrobials through various phenotypic and genetic mechanisms.
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Affiliation(s)
| | - Jens Rolff
- Evolutionary Biology, Institute for Biology, Freie Universität Berlin, Berlin, Germany
| | - Roland R. Regoes
- Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland
| | - Claudia Igler
- Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland
- School of Biological Sciences, University of Manchester, Manchester, UK
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Parmar KR, Lukka PB, Wagh S, Temrikar ZH, Liu J, Lee RE, Braunstein M, Hickey AJ, Robertson GT, Gonzalez-Juarrero M, Edginton A, Meibohm B. Development of a Minimalistic Physiologically Based Pharmacokinetic (mPBPK) Model for the Preclinical Development of Spectinamide Antibiotics. Pharmaceutics 2023; 15:1759. [PMID: 37376207 DOI: 10.3390/pharmaceutics15061759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/11/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
Spectinamides 1599 and 1810 are lead spectinamide compounds currently under preclinical development to treat multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis. These compounds have previously been tested at various combinations of dose level, dosing frequency, and route of administration in mouse models of Mycobacterium tuberculosis (Mtb) infection and in healthy animals. Physiologically based pharmacokinetic (PBPK) modeling allows the prediction of the pharmacokinetics of candidate drugs in organs/tissues of interest and extrapolation of their disposition across different species. Here, we have built, qualified, and refined a minimalistic PBPK model that can describe and predict the pharmacokinetics of spectinamides in various tissues, especially those relevant to Mtb infection. The model was expanded and qualified for multiple dose levels, dosing regimens, routes of administration, and various species. The model predictions in mice (healthy and infected) and rats were in reasonable agreement with experimental data, and all predicted AUCs in plasma and tissues met the two-fold acceptance criteria relative to observations. To further explore the distribution of spectinamide 1599 within granuloma substructures as encountered in tuberculosis, we utilized the Simcyp granuloma model combined with model predictions in our PBPK model. Simulation results suggest substantial exposure in all lesion substructures, with particularly high exposure in the rim area and macrophages. The developed model may be leveraged as an effective tool in identifying optimal dose levels and dosing regimens of spectinamides for further preclinical and clinical development.
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Affiliation(s)
- Keyur R Parmar
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Pradeep B Lukka
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Santosh Wagh
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Zaid H Temrikar
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Jiuyu Liu
- Department of Chemical Biology, St. Jude Children's Hospital, Memphis, TN 38105, USA
| | - Richard E Lee
- Department of Chemical Biology, St. Jude Children's Hospital, Memphis, TN 38105, USA
| | - Miriam Braunstein
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Anthony J Hickey
- Technology Advancement and Commercialization, RTI International, Durham, NC 27709, USA
| | - Gregory T Robertson
- Mycobacteria Research Laboratories, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO 80523, USA
| | - Mercedes Gonzalez-Juarrero
- Mycobacteria Research Laboratories, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO 80523, USA
| | - Andrea Edginton
- School of Pharmacy, University of Waterloo, Waterloo, ON N2G 1C5, Canada
| | - Bernd Meibohm
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN 38163, USA
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Saeheng T, Na-Bangchang K. Simulation of optimal dose regimens of photoactivated curcumin for antimicrobial resistance pneumonia in COVID-19 patients: A modeling approach. Infect Dis Model 2023; 8:S2468-0427(23)00046-5. [PMID: 37361409 PMCID: PMC10239661 DOI: 10.1016/j.idm.2023.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 04/07/2023] [Accepted: 05/30/2023] [Indexed: 06/28/2023] Open
Abstract
Background Secondary antimicrobial resistance bacterial (AMR) pneumonia could lead to an increase in mortality in COVID-19 patients, particularly of geriatric patients with underlying diseases. The comedication of current medicines for AMR pneumonia with corticosteroids may lead to suboptimal treatment or toxicities due to drug-drug interactions (DDIs). Objective This study aimed to propose new promising dosage regimens of photoactivated curcumin when co-administered with corticosteroids for the treatment of antimicrobial resistance (AMR) pneumonia in COVID-19 patients. Methods A whole-body physiologically-based pharmacokinetic (PBPK) with the simplified lung compartments model was built and verified following standard model verification (absolute average-folding error or AAFEs). The pharmacokinetic properties of photoactivated were assumed to be similar to curcumin due to minor changes in physiochemical properties of compound by photoactivation. The acceptable AAFEs values were within 2-fold. The verified model was used to simulate new regimens for different formulations of photoactivated curcumin. Results The AAFEs was 1.12-fold. Original formulation (120 mg once-daily dose) or new intramuscular nano-formulation (100 mg with a release rate of 10/h given every 7 days) is suitable for outpatients with MRSA pneumonia to improve patient adherence. New intravenous formulation (2000 mg twice-daily doses) is for hospitalized patients with both MRSA and VRSA pneumonia. Conclusion The PBPK models, in conjunction with MIC and applied physiological changes in COVID-19 patients, is a potential tool to predict optimal dosage regimens of photoactivated curcumin for the treatment of co-infected AMR pneumonia in COVID-19 patients. Each formulation is appropriate for different patient conditions and pathogens.
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Affiliation(s)
- Teerachat Saeheng
- Centre of Excellence in Pharmacology and Molecular Biology of Malaria and Cholangiocarcinoma, Chulabhorn International College, 99 Moo 18, Phaholyothin Road, Thammasat University (Rangsit Campus), Klongneung, Klongluang District, Pathumthani, 12121, Thailand
| | - Kesara Na-Bangchang
- Centre of Excellence in Pharmacology and Molecular Biology of Malaria and Cholangiocarcinoma, Chulabhorn International College, 99 Moo 18, Phaholyothin Road, Thammasat University (Rangsit Campus), Klongneung, Klongluang District, Pathumthani, 12121, Thailand
- Drug Discovery and Development Centre, Office of Advanced Science and Technology, 99 Moo 18, Phaholyothin Road, Thammasat University (Rangsit Campus), Klongneung, Klongluang, Pathumthani, 12121, Thailand
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Grañana-Castillo S, Montanha MC, Bearon R, Khoo S, Siccardi M. Evaluation of drug-drug interaction between rilpivirine and rifapentine using PBPK modelling. Front Pharmacol 2022; 13:1076266. [PMID: 36588698 PMCID: PMC9797969 DOI: 10.3389/fphar.2022.1076266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Tuberculosis remains the leading cause of death among people living with HIV. Rifapentine is increasingly used to treat active disease or prevent reactivation, in both cases given either as weekly or daily therapy. However, rifapentine is an inducer of CYP3A4, potentially interacting with antiretrovirals like rilpivirine. This in silico study investigates the drug-drug interaction (DDI) magnitude between daily oral rilpivirine 25 mg with either daily 600 mg or weekly 900 mg rifapentine. A physiologically based pharmacokinetic (PBPK) model was built in Simbiology (Matlab R2018a) to simulate the drug-drug interaction. The simulated PK parameters from the PBPK model were verified against reported clinical data for rilpivirine and rifapentine separately, daily rifapentine with midazolam, and weekly rifapentine with doravirine. The simulations of concomitant administration of rifapentine with rilpivirine at steady-state lead to a maximum decrease on AUC0-24 and Ctrough by 83% and 92% on day 5 for the daily rifapentine regimen and 68% and 92% for the weekly regimen on day 3. In the weekly regimen, prior to the following dose, AUC0-24 and Ctrough were still reduced by 47% and 53%. In both simulations, the induction effect ceased 2 weeks after the interruption of rifapentine's treatment. A daily double dose of rilpivirine after initiating rifapentine 900 mg weekly was simulated but failed to compensate the drug-drug interaction. The drug-drug interaction model suggested a significant decrease on rilpivirine exposure which is unlikely to be corrected by dose increment, thus coadministration should be avoided.
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Affiliation(s)
- Sandra Grañana-Castillo
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, United Kingdom,*Correspondence: Sandra Grañana-Castillo,
| | - Maiara Camotti Montanha
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, United Kingdom
| | - Rachel Bearon
- Department of Mathematical Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Saye Khoo
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, United Kingdom
| | - Marco Siccardi
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, United Kingdom
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[11C]glyburide PET imaging for quantitative determination of the importance of Organic Anion-Transporting Polypeptide transporter function in the human liver and whole-body. Biomed Pharmacother 2022; 156:113994. [DOI: 10.1016/j.biopha.2022.113994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 11/07/2022] [Accepted: 11/07/2022] [Indexed: 11/10/2022] Open
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Methamphetamine detection using nanoparticle-based biosensors: A comprehensive review. SENSING AND BIO-SENSING RESEARCH 2022. [DOI: 10.1016/j.sbsr.2022.100538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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Flexner C, Siccardi M, Bunglawala F, Owen A. The LEAP Process: Streamlining the Development of Long-Acting Products and Formulations for Infectious Diseases. Clin Infect Dis 2022; 75:S502-S509. [PMID: 36410389 PMCID: PMC10200316 DOI: 10.1093/cid/ciac750] [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] [Indexed: 11/22/2022] Open
Abstract
Developing long-acting products and formulations for infectious diseases is a nontrivial undertaking that is frequently classified as high risk and low reward by the pharmaceutical industry. The Long-Acting/Extended Release Antiretroviral Research Resource Program (LEAP) was founded in 2015 with the support of the National Institutes of Health to encourage, promote, and accelerate the development of such products. Assessment methodology for any new proposal brought to this group is part of a framework-the LEAP Process-that includes a landscape analysis of what is currently available in the public domain. This is followed by in silico modeling and simulation offered as a service to the relevant scientific community. A variety of preclinical and clinical outcome metrics are applied to each new agent as part of a continuous feedback loop to improve product characteristics. This allows us to catalog knowledge gaps and barriers that can be addressed by engaged stakeholders. Results are communicated in scientific articles, reviews, and position papers. This undertaking serves to de-risk discovery, development, and implementation by bridging the gaps between academic, regulatory, and industrial investigators, and by engaging those in the community who will be the eventual users of these medicines. The LEAP Process has supported formulations now approved for human immunodeficiency virus, as well as products in clinical and preclinical development for tuberculosis and hepatitis viruses B and C.
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Affiliation(s)
- Charles Flexner
- Divisions of Clinical Pharmacology and Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Marco Siccardi
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, United Kingdom
| | - Fazila Bunglawala
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, United Kingdom
| | - Andrew Owen
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, United Kingdom
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Zhang W, Xiang Y, Wang L, Wang F, Li G, Zhuang X. Translational pharmacokinetics of a novel bispecific antibody against Ebola virus (MBS77E) from animal to human by PBPK modeling & simulation. Int J Pharm 2022; 626:122160. [PMID: 36089211 DOI: 10.1016/j.ijpharm.2022.122160] [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: 06/28/2022] [Revised: 08/11/2022] [Accepted: 08/28/2022] [Indexed: 11/17/2022]
Abstract
The goal of this study was to construct a PBPK model to accelerate the translation of MBS77E, a humanized bispecific antibody against the Ebola virus. In-depth nonclinical pharmacokinetic studies in rats, monkeys, wild-type mice and transgenic mice were conducted. The pH-dependent affinities (KD) of MBS77E to recombinant FcRn of different species were determined by surface plasmon resonance analysis. A mechanistic whole-body PBPK model of MBS77E was developed and validated in the assessment of PK profiles and tissue distributions in preclinical models. This PBPK model was finally used to predict human PK behaviors of MBS77E. Simulations from the PBPK model with measured and fitted parameters were able to yield good predictions of the serum and tissue pharmacokinetic parameters of MBS77E within 2-fold errors. The predicted serum concentration in humans was able to maintain a sufficiently high level for more than 14 days after 50 mg/kg i.v. administrating. This achievement unlocks that PBPK modeling is a powerful tool to gain insights into the properties of antibody drugs. It guided experimental efforts to obtain necessary information before entry into humans.
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Affiliation(s)
- Wenpeng Zhang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, China
| | - Yanan Xiang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, China
| | - Lingchao Wang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, China
| | - Furun Wang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, China
| | - Guanglu Li
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, China
| | - Xiaomei Zhuang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, China.
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Yuan Y, He Q, Zhang S, Li M, Tang Z, Zhu X, Jiao Z, Cai W, Xiang X. Application of Physiologically Based Pharmacokinetic Modeling in Preclinical Studies: A Feasible Strategy to Practice the Principles of 3Rs. Front Pharmacol 2022; 13:895556. [PMID: 35645843 PMCID: PMC9133488 DOI: 10.3389/fphar.2022.895556] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 04/14/2022] [Indexed: 11/18/2022] Open
Abstract
Pharmacokinetic characterization plays a vital role in drug discovery and development. Although involving numerous laboratory animals with error-prone, labor-intensive, and time-consuming procedures, pharmacokinetic profiling is still irreplaceable in preclinical studies. With physiologically based pharmacokinetic (PBPK) modeling, the in vivo profiles of drug absorption, distribution, metabolism, and excretion can be predicted. To evaluate the application of such an approach in preclinical investigations, the plasma pharmacokinetic profiles of seven commonly used probe substrates of microsomal enzymes, including phenacetin, tolbutamide, omeprazole, metoprolol, chlorzoxazone, nifedipine, and baicalein, were predicted in rats using bottom-up PBPK models built with in vitro data alone. The prediction's reliability was assessed by comparison with in vivo pharmacokinetic data reported in the literature. The overall predicted accuracy of PBPK models was good with most fold errors within 2, and the coefficient of determination (R2) between the predicted concentration data and the observed ones was more than 0.8. Moreover, most of the observation dots were within the prediction span of the sensitivity analysis. We conclude that PBPK modeling with acceptable accuracy may be incorporated into preclinical studies to refine in vivo investigations, and PBPK modeling is a feasible strategy to practice the principles of 3Rs.
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Affiliation(s)
- Yawen Yuan
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
- Department of Pharmacy, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qingfeng He
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
| | - Shunguo Zhang
- Department of Pharmacy, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Min Li
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
| | - Zhijia Tang
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
| | - Xiao Zhu
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Weimin Cai
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
| | - Xiaoqiang Xiang
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
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16
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Zazo H, Colino CI, Gutiérrez-Millán C, Cordero AA, Bartneck M, Lanao JM. Physiologically Based Pharmacokinetic (PBPK) Model of Gold Nanoparticle-Based Drug Delivery System for Stavudine Biodistribution. Pharmaceutics 2022; 14:pharmaceutics14020406. [PMID: 35214138 PMCID: PMC8875329 DOI: 10.3390/pharmaceutics14020406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 02/10/2022] [Accepted: 02/11/2022] [Indexed: 11/16/2022] Open
Abstract
Computational modelling has gained attention for evaluating nanoparticle-based drug delivery systems. Physiologically based pharmacokinetic (PBPK) modelling provides a mechanistic approach for evaluating drug biodistribution. The aim of this work is to develop a specific PBPK model to simulate stavudine biodistribution after the administration of a 40 nm gold nanoparticle-based drug delivery system in rats. The model parameters used have been obtained from literature, in vitro and in vivo studies, and computer optimization. Based on these, the PBPK model was built, and the compartments included were considered as permeability rate-limited tissues. In comparison with stavudine solution, a higher biodistribution of stavudine into HIV reservoirs and the modification of pharmacokinetic parameters such as the mean residence time (MRT) have been observed. These changes are particularly noteworthy in the liver, which presents a higher partition coefficient (from 0.27 to 0.55) and higher MRT (from 1.28 to 5.67 h). Simulated stavudine concentrations successfully describe these changes in the in vivo study results. The average fold error of predicted concentrations after the administration of stavudine-gold nanoparticles was within the 0.5–2-fold error in all of the tissues. Thus, this PBPK model approach may help with the pre-clinical extrapolation to other administration routes or the species of stavudine gold nanoparticles.
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Affiliation(s)
- Hinojal Zazo
- Area of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Avda Lcdo Méndez Nieto, 37007 Salamanca, Spain; (H.Z.); (C.G.-M.); (A.A.C.)
- Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Clara I. Colino
- Area of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Avda Lcdo Méndez Nieto, 37007 Salamanca, Spain; (H.Z.); (C.G.-M.); (A.A.C.)
- Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
- Correspondence: (C.I.C.); (J.M.L.); Tel.: +34-923-294-536 (C.I.C.)
| | - Carmen Gutiérrez-Millán
- Area of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Avda Lcdo Méndez Nieto, 37007 Salamanca, Spain; (H.Z.); (C.G.-M.); (A.A.C.)
- Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Andres A. Cordero
- Area of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Avda Lcdo Méndez Nieto, 37007 Salamanca, Spain; (H.Z.); (C.G.-M.); (A.A.C.)
| | - Matthias Bartneck
- Department of Medicine III, Medical Faculty, RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany;
| | - José M. Lanao
- Area of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Avda Lcdo Méndez Nieto, 37007 Salamanca, Spain; (H.Z.); (C.G.-M.); (A.A.C.)
- Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
- Correspondence: (C.I.C.); (J.M.L.); Tel.: +34-923-294-536 (C.I.C.)
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Wilson CG, Aarons L, Augustijns P, Brouwers J, Darwich AS, De Waal T, Garbacz G, Hansmann S, Hoc D, Ivanova A, Koziolek M, Reppas C, Schick P, Vertzoni M, García-Horsman JA. Integration of advanced methods and models to study drug absorption and related processes: An UNGAP perspective. Eur J Pharm Sci 2021; 172:106100. [PMID: 34936937 DOI: 10.1016/j.ejps.2021.106100] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 12/14/2021] [Accepted: 12/16/2021] [Indexed: 01/09/2023]
Abstract
This collection of contributions from the European Network on Understanding Gastrointestinal Absorption-related Processes (UNGAP) community assembly aims to provide information on some of the current and newer methods employed to study the behaviour of medicines. It is the product of interactions in the immediate pre-Covid period when UNGAP members were able to meet and set up workshops and to discuss progress across the disciplines. UNGAP activities are divided into work packages that cover special treatment populations, absorption processes in different regions of the gut, the development of advanced formulations and the integration of food and pharmaceutical scientists in the food-drug interface. This involves both new and established technical approaches in which we have attempted to define best practice and highlight areas where further research is needed. Over the last months we have been able to reflect on some of the key innovative approaches which we were tasked with mapping, including theoretical, in silico, in vitro, in vivo and ex vivo, preclinical and clinical approaches. This is the product of some of us in a snapshot of where UNGAP has travelled and what aspects of innovative technologies are important. It is not a comprehensive review of all methods used in research to study drug dissolution and absorption, but provides an ample panorama of current and advanced methods generally and potentially useful in this area. This collection starts from a consideration of advances in a priori approaches: an understanding of the molecular properties of the compound to predict biological characteristics relevant to absorption. The next four sections discuss a major activity in the UNGAP initiative, the pursuit of more representative conditions to study lumenal dissolution of drug formulations developed independently by academic teams. They are important because they illustrate examples of in vitro simulation systems that have begun to provide a useful understanding of formulation behaviour in the upper GI tract for industry. The Leuven team highlights the importance of the physiology of the digestive tract, as they describe the relevance of gastric and intestinal fluids on the behaviour of drugs along the tract. This provides the introduction to microdosing as an early tool to study drug disposition. Microdosing in oncology is starting to use gamma-emitting tracers, which provides a link through SPECT to the next section on nuclear medicine. The last two papers link the modelling approaches used by the pharmaceutical industry, in silico to Pop-PK linking to Darwich and Aarons, who provide discussion on pharmacometric modelling, completing the loop of molecule to man.
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Affiliation(s)
- Clive G Wilson
- Strathclyde Institute of Pharmacy & Biomedical Sciences, Glasgow, U.K.
| | | | | | | | | | | | | | | | | | | | - Mirko Koziolek
- NCE Formulation Sciences, Abbvie Deutschland GmbH & Co. KG, Germany
| | | | - Philipp Schick
- Department of Biopharmaceutics and Pharmaceutical Technology, Center of Drug Absorption and Transport, University of Greifswald, Germany
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van Os W, Zeitlinger M. Predicting Antimicrobial Activity at the Target Site: Pharmacokinetic/Pharmacodynamic Indices versus Time-Kill Approaches. Antibiotics (Basel) 2021; 10:antibiotics10121485. [PMID: 34943697 PMCID: PMC8698708 DOI: 10.3390/antibiotics10121485] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 12/21/2022] Open
Abstract
Antibiotic dosing strategies are generally based on systemic drug concentrations. However, drug concentrations at the infection site drive antimicrobial effect, and efficacy predictions and dosing strategies should be based on these concentrations. We set out to review different translational pharmacokinetic-pharmacodynamic (PK/PD) approaches from a target site perspective. The most common approach involves calculating the probability of attaining animal-derived PK/PD index targets, which link PK parameters to antimicrobial susceptibility measures. This approach is time efficient but ignores some aspects of the shape of the PK profile and inter-species differences in drug clearance and distribution, and provides no information on the PD time-course. Time–kill curves, in contrast, depict bacterial response over time. In vitro dynamic time–kill setups allow for the evaluation of bacterial response to clinical PK profiles, but are not representative of the infection site environment. The translational value of in vivo time–kill experiments, conversely, is limited from a PK perspective. Computational PK/PD models, especially when developed using both in vitro and in vivo data and coupled to target site PK models, can bridge translational gaps in both PK and PD. Ultimately, clinical PK and experimental and computational tools should be combined to tailor antibiotic treatment strategies to the site of infection.
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19
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PBPK Modeling and Simulation and Therapeutic Drug Monitoring: Possible Ways for Antibiotic Dose Adjustment. Processes (Basel) 2021. [DOI: 10.3390/pr9112087] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Pharmacokinetics (PK) is a branch of pharmacology present and of vital importance for the research and development (R&D) of new drugs, post-market monitoring, and continued optimizations in clinical contexts. Ultimately, pharmacokinetics can contribute to improving patients’ clinical outcomes, helping enhance the efficacy of treatments, and reducing possible adverse side effects while also contributing to precision medicine. This article discusses the methods used to predict and study human pharmacokinetics and their evolution to the current physiologically based pharmacokinetic (PBPK) modeling and simulation methods. The importance of therapeutic drug monitoring (TDM) and PBPK as valuable tools for Model-Informed Precision Dosing (MIPD) are highlighted, with particular emphasis on antibiotic therapy since dosage adjustment of antibiotics can be vital to ensure successful clinical outcomes and to prevent the spread of resistant bacterial strains.
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20
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Liu XI, Green DJ, van den Anker JN, Rakhmanina NY, Ahmadzia HK, Momper JD, Park K, Burckart GJ, Dallmann A. Mechanistic Modeling of Placental Drug Transfer in Humans: How Do Differences in Maternal/Fetal Fraction of Unbound Drug and Placental Influx/Efflux Transfer Rates Affect Fetal Pharmacokinetics? Front Pediatr 2021; 9:723006. [PMID: 34733804 PMCID: PMC8559552 DOI: 10.3389/fped.2021.723006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 09/13/2021] [Indexed: 01/16/2023] Open
Abstract
Background: While physiologically based pharmacokinetic (PBPK) models generally predict pharmacokinetics in pregnant women successfully, the confidence in predicting fetal pharmacokinetics is limited because many parameters affecting placental drug transfer have not been mechanistically accounted for. Objectives: The objectives of this study were to implement different maternal and fetal unbound drug fractions in a PBPK framework; to predict fetal pharmacokinetics of eight drugs in the third trimester; and to quantitatively investigate how alterations in various model parameters affect predicted fetal pharmacokinetics. Methods: The ordinary differential equations of previously developed pregnancy PBPK models for eight drugs (acyclovir, cefuroxime, diazepam, dolutegravir, emtricitabine, metronidazole, ondansetron, and raltegravir) were amended to account for different unbound drug fractions in mother and fetus. Local sensitivity analyses were conducted for various parameters relevant to placental drug transfer, including influx/efflux transfer clearances across the apical and basolateral membrane of the trophoblasts. Results: For the highly-protein bound drugs diazepam, dolutegravir and ondansetron, the lower fraction unbound in the fetus vs. mother affected predicted pharmacokinetics in the umbilical vein by ≥10%. Metronidazole displayed blood flow-limited distribution across the placenta. For all drugs, umbilical vein concentrations were highly sensitive to changes in the apical influx/efflux transfer clearance ratio. Additionally, transfer clearance across the basolateral membrane was a critical parameter for cefuroxime and ondansetron. Conclusion: In healthy pregnancies, differential protein binding characteristics in mother and fetus give rise to minor differences in maternal-fetal drug exposure. Further studies are needed to differentiate passive and active transfer processes across the apical and basolateral trophoblast membrane.
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Affiliation(s)
- Xiaomei I. Liu
- Division of Clinical Pharmacology, Children's National Hospital, Washington, DC, United States
| | - Dionna J. Green
- Office of Pediatric Therapeutics, Office of the Commissioner, US Food and Drug Administration, Silver Spring, MD, United States
| | - John N. van den Anker
- Division of Clinical Pharmacology, Children's National Hospital, Washington, DC, United States
| | - Natella Y. Rakhmanina
- Division of Infectious Diseases, Children's National Hospital, Washington, DC, United States
- Technical Strategies and Innovation, Elizabeth Glaser Pediatric AIDS Foundation, Washington, DC, United States
| | - Homa K. Ahmadzia
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, School of Medicine and Health Sciences, The George Washington University, Washington, DC, United States
| | - Jeremiah D. Momper
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, United States
| | - Kyunghun Park
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, United States
| | - Gilbert J. Burckart
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, United States
| | - André Dallmann
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
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21
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Mahmood I, Tegenge MA. Spreadsheet-Based Minimal Physiological Models for the Prediction of Clearance of Therapeutic Proteins in Pediatric Patients. J Clin Pharmacol 2021; 61 Suppl 1:S108-S116. [PMID: 34185903 DOI: 10.1002/jcph.1846] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Accepted: 02/19/2021] [Indexed: 12/15/2022]
Abstract
There is a growing interest in the use of physiologically based pharmacokinetic (PBPK) models as clinical pharmacology drug development tools. In PBPK modeling, not every organ or physiological parameter is required, leading to the development of a minimal PBPK (mPBPK) model, which is simple and efficient. The objective of this study was to streamline mPBPK modeling approaches and enable straightforward prediction of clearance of protein-based products in children. Four mPBPK models for scaling clearance from adult to children were developed and evaluated on Excel spreadsheets using (1) liver and kidneys; (2) liver, kidneys, and skin; (3) liver, kidneys, skin, and lymph; and (4) interstitial, lymph, and plasma volume. There were 35 therapeutic proteins with a total of 113 observations across different age groups (premature neonates to adolescents). For monoclonal and polyclonal antibodies, more than 90% of observations were within a 0.5- to 2-fold prediction error for all 4 methods. For nonantibodies, 79% to 100% of observations were within the 0.5- to 2-fold prediction error for the 4 different methods. Methods 1 and 4 provided the best results, >90% of the total observations were within the 0.5- to 2-fold prediction error for all 3 classes of protein-based products across a wide age range. The precision of clearance prediction was comparatively lower in children ≤2 years of age vs older children (>2 years of age) with methods 1 and 4 predicting 80% to 100% and 75% to 90% of observations within the 0.5- to 2-fold prediction error, respectively. The results of the study indicated that mPBPK models can be developed on spreadsheets, with acceptable performance for prediction of clearance.
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Affiliation(s)
- Iftekhar Mahmood
- Mahmood Clinical Pharmacology Consultancy, Rockville, Maryland, USA
| | - Million A Tegenge
- Division of Clinical Evaluation and Pharmacology/Toxicology, Center for Biologics Evaluation and Research (CBER), Office of Tissues and Advanced Therapies (OTAT), Food and Drug Administration (FDA), Silver Spring, Maryland, USA
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22
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Bunglawala F, Rajoli RKR, Mirochnick M, Owen A, Siccardi M. Prediction of dolutegravir pharmacokinetics and dose optimization in neonates via physiologically based pharmacokinetic (PBPK) modelling. J Antimicrob Chemother 2021; 75:640-647. [PMID: 31860112 DOI: 10.1093/jac/dkz506] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 10/23/2019] [Accepted: 11/05/2019] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Only a few antiretroviral drugs (ARVs) are recommended for use during the neonatal period and there is a need for more to be approved to increase treatment and prophylaxis strategies. Dolutegravir, a selective integrase inhibitor, has potential for treatment of HIV infection and prophylaxis of transmission in neonates. OBJECTIVES To model the pharmacokinetics of dolutegravir in neonates and to simulate a theoretical optimal dosing regimen. METHODS The physiologically based pharmacokinetic (PBPK) model was built incorporating the age-related changes observed in neonates. Virtual neonates between 0 and 28 days were simulated. The model was validated against observed clinical data for raltegravir and midazolam in neonates, prior to the prediction of dolutegravir pharmacokinetics. RESULTS Both raltegravir and midazolam passed the criteria for model qualification, with simulated data within 1.8-fold of clinical data. The qualified model predicted the pharmacokinetics for several multidose regimens of dolutegravir. Regimen 6 involved 5 mg doses with a 48 h interval from Day 1-20, increasing to 5 mg once daily on Week 3, yielding AUC and Ctrough values of 37.2 mg·h/L and 1.3 mg/L, respectively. These exposures are consistent with those observed in paediatric patients receiving dolutegravir. CONCLUSIONS Dolutegravir pharmacokinetics were successfully simulated in the neonatal PBPK model. The predictions suggest that during the first 3 weeks of life a 5 mg dose administered every 48 h may achieve plasma exposures needed for therapy and prophylaxis.
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Affiliation(s)
- Fazila Bunglawala
- Department of Molecular and Clinical Pharmacology, University of Liverpool, 70 Pembroke Place, Liverpool L69 3GF, UK
| | - Rajith K R Rajoli
- Department of Molecular and Clinical Pharmacology, University of Liverpool, 70 Pembroke Place, Liverpool L69 3GF, UK
| | | | - Andrew Owen
- Department of Molecular and Clinical Pharmacology, University of Liverpool, 70 Pembroke Place, Liverpool L69 3GF, UK
| | - Marco Siccardi
- Department of Molecular and Clinical Pharmacology, University of Liverpool, 70 Pembroke Place, Liverpool L69 3GF, UK
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Palombo G, Merone M, Altomare A, Gori M, Terradura C, Bacco L, Del Chierico F, Putignani L, Cicala M, Guarino MPL, Piemonte V. The impact of the intestinal microbiota and the mucosal permeability on three different antibiotic drugs. Eur J Pharm Sci 2021; 164:105869. [PMID: 34020000 DOI: 10.1016/j.ejps.2021.105869] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 03/19/2021] [Accepted: 04/25/2021] [Indexed: 01/15/2023]
Abstract
BackgroundThe totality of bacteria, protozoa, viruses and fungi that lives in the human body is called microbiota. Human microbiota specifically colonizes the skin, the respiratory and urinary tract, the urogenital tract and the gastrointestinal system. This study focuses on the intestinal microbiota to explore the drug-microbiota relationship and, therefore, how the drug bioavailability changes in relation to the microbiota biodiversity to identify more personalized therapies, with the minimum risk of side effects. MethodsTo achieve this goal, we developed a new mathematical model with two compartments, the intestine and the blood, which takes into account the colonic mucosal permeability variation - measured by Ussing chamber system on human colonic mucosal biopsies - and the fecal microbiota composition, determined through microbiota 16S rRNA sequencing analysis. Both of the clinical parameters were evaluated in a group of Irritable Bowel Syndrome patients compared to a group of healthy controls. Key ResultsThe results show that plasma drug concentration increases as bacterial concentration decreases, while it decreases as intestinal length decreases too. ConclusionsThe study provides interesting data since in literature there are not yet mathematical models with these features, in which the importance of intestinal microbiota, the "forgotten organ", is considered both for the subject health state and in the nutrients and drugs metabolism.
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Affiliation(s)
- Giovanni Palombo
- Istituto di Analisi dei Sistemi ed Informatica "A. Ruberti", IASI-CNR (National Research Council of Italy), Rome, Italy; SYSBIO/ISBE.IT, Centre of System Biology, Rome, Italy
| | - Mario Merone
- Computer Systems and Bioinformatics Laboratory, Department of Engineering, University Campus Bio-Medico of Rome, Italy.
| | | | - Manuele Gori
- Unit of Gastroenterology Campus Bio-Medico University, Rome, Italy; Institute of Biochemistry and Cell Biology (IBBC) - National Research Council (CNR), Monterotondo Scalo, Rome, Italy
| | - Carlotta Terradura
- Unit of Chemical-physics Fundamentals in Chemical Engineering, Department of Engineering, University Campus Bio-Medico of Rome, Italy
| | - Luca Bacco
- Computer Systems and Bioinformatics Laboratory, Department of Engineering, University Campus Bio-Medico of Rome, Italy; Istituto di Linguistica Computazionale "Antonio Zampolli" (IL-CNR), ItaliaNLP Lab, Pisa, Italy
| | - Federica Del Chierico
- Multimodal Laboratory Medicine Research Area, Unit of Human Microbiome, Bambino Gesú Children's Hospital, IRCCS, Rome, Italy
| | - Lorenza Putignani
- Department of Diagnostic and Laboratory Medicine, Unit of Parasitology and Multimodal Laboratory Medicine Research Area, Unit of Human Microbiome, Bambino Gesú Children's Hospital, IRCCS, Rome, Italy
| | - Michele Cicala
- Unit of Gastroenterology Campus Bio-Medico University, Rome, Italy
| | | | - Vincenzo Piemonte
- Unit of Chemical-physics Fundamentals in Chemical Engineering, Department of Engineering, University Campus Bio-Medico of Rome, Italy
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Methaneethorn J, Poomsaidorn C, Naosang K, Kaewworasut P, Lohitnavy M. A Δ 9-Tetrahydrocannabinol Physiologically-Based Pharmacokinetic Model Development in Humans. Eur J Drug Metab Pharmacokinet 2021; 45:495-511. [PMID: 32266676 DOI: 10.1007/s13318-020-00617-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND AND OBJECTIVE ∆9-Tetrahydrocannabinol (THC) exhibits several therapeutic effects, such as analgesics, anti-emetic, antispastic, and muscle relaxation properties. Knowledge concerning THC disposition in target organs is crucial for THC therapy. The objective of this study was to develop a physiologically-based pharmacokinetic (PBPK) model of THC in humans to characterize tissue-specific pharmacokinetics of THC in organs of interest. METHODS The model was extrapolated from the previously developed PBPK model conducted in mice, rats, and pigs. The model consisted of seven compartments: brain, lungs, liver, kidneys, fat, and rapidly perfused and slowly perfused tissues. P-glycoprotein was included in the brain compartment to characterize an efflux of THC from the brain. Physiologic, biochemical, and physicochemical parameters were determined and acquired from the literature. Model validation was performed by comparisons of the predicted and observed THC concentrations acquired from published studies. RESULTS The developed PBPK model resulted in good agreement between the predicted and observed THC concentrations across several studies conducted following IV bolus, IV infusion, oral, and smoking and inhalation, with the coefficient of determination (R2) ranging from 0.54 to 0.95. CONCLUSIONS A PBPK model of THC in humans was developed. The model could describe THC concentration-time profiles in several dosing scenarios (i.e., IV bolus, IV infusion, oral administration and inhalation).
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Affiliation(s)
- Janthima Methaneethorn
- Pharmacokinetic Research Unit, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand.,Faculty of Pharmaceutical Sciences, Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, 65000, Thailand.,Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand
| | - Chomkanang Poomsaidorn
- Pharmacokinetic Research Unit, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand.,Faculty of Pharmaceutical Sciences, Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, 65000, Thailand
| | - Kanyamas Naosang
- Pharmacokinetic Research Unit, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand.,Faculty of Pharmaceutical Sciences, Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, 65000, Thailand
| | - Parichart Kaewworasut
- Pharmacokinetic Research Unit, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand.,Faculty of Pharmaceutical Sciences, Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, 65000, Thailand
| | - Manupat Lohitnavy
- Pharmacokinetic Research Unit, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand. .,Faculty of Pharmaceutical Sciences, Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, 65000, Thailand. .,Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand.
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Miura T, Kamiya Y, Uehara S, Murayama N, Shimizu M, Suemizu H, Yamazaki H. Hepatotoxicological potential of P-toluic acid in humanised-liver mice investigated using simplified physiologically based pharmacokinetic models. Xenobiotica 2021; 51:636-642. [PMID: 33781181 DOI: 10.1080/00498254.2021.1908643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
p-Toluic acid, a metabolite of organic solvent xylene, has a high reported no-observed-effect level (NOEL, 1000 mg/kg) in rats, possibly because of direct glycine conjugation to methylhippuric acid. In this study, plasma levels of p-toluic acid and its glycine conjugate in mice and humanised-liver mice were evaluated after oral administrations.Although rapid conversion of p-toluic acid to its glycine conjugate was evident from mouse plasma concentrations, the biotransformation of p-toluic acid was slower in humanised-liver mice. The input parameters for physiologically based pharmacokinetic (PBPK) models were determined using fitting procedures to create PBPK-generated plasma concentration curves.The PBPK-modelled hepatic concentrations of p-toluic acid in humanised-liver mice were higher than those observed in plasma. PBPK-modelled hepatic and plasma concentrations of p-toluic acid also indicated slow elimination in humans.These results suggest that rapid conjugations of p-toluic acid reportedly observed in rats could result in overestimation of NOELs for conjugatable chemicals when extrapolated to humanised-liver mice or humans.
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Affiliation(s)
- Tomonori Miura
- Laboratory of Drug Metabolism and Pharmacokinetics, Showa Pharmaceutical University, Machida, Japan
| | - Yusuke Kamiya
- Laboratory of Drug Metabolism and Pharmacokinetics, Showa Pharmaceutical University, Machida, Japan
| | - Shotaro Uehara
- Laboratory Animal Research Department, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Norie Murayama
- Laboratory of Drug Metabolism and Pharmacokinetics, Showa Pharmaceutical University, Machida, Japan
| | - Makiko Shimizu
- Laboratory of Drug Metabolism and Pharmacokinetics, Showa Pharmaceutical University, Machida, Japan
| | - Hiroshi Suemizu
- Laboratory Animal Research Department, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Hiroshi Yamazaki
- Laboratory of Drug Metabolism and Pharmacokinetics, Showa Pharmaceutical University, Machida, Japan
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Sung JH. Multi-organ-on-a-chip for pharmacokinetics and toxicokinetic study of drugs. Expert Opin Drug Metab Toxicol 2021; 17:969-986. [PMID: 33764248 DOI: 10.1080/17425255.2021.1908996] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction: Accurate prediction of pharmacokinetic (PK) and toxicokinetics (TK) of drugs is imperative for successful development of new pharmaceutics. Although conventional in vitro methods for predicting the PK and TK of drugs are well established, limitations still exist and more advanced chip-based in vitro platforms combined with mathematical models can help researchers overcome the limitations. Areas covered: We will review recent progress in the development of multi-organ-on-a-chip platforms for predicting PK and TK of drugs, as well as mathematical approaches that can be combined with these platforms for experiment design, data analysis and in vitro-in vivo extrapolation (IVIVE) for application to humans. Expert opinion: Although there remain some challenges to be addressed, the remarkable progress in the area of multi-organ-on-a-chip in recent years indicate that we will see tangible outcomes that can be utilized in the pharmaceutical industry in near future.
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Affiliation(s)
- Jong Hwan Sung
- Department of Chemical Engineering, Hongik University, Seoul, sejong, Republic of Korea
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Abstract
Accurate estimation of in vivo clearance in human is pivotal to determine the dose and dosing regimen for drug development. In vitro-in vivo extrapolation (IVIVE) has been performed to predict drug clearance using empirical and physiological scalars. Multiple in vitro systems and mathematical modeling techniques have been employed to estimate in vivo clearance. The models for predicting clearance have significantly improved and have evolved to become more complex by integrating multiple processes such as drug metabolism and transport as well as passive diffusion. This chapter covers the use of conventional as well as recently developed methods to predict metabolic and transporter-mediated clearance along with the advantages and disadvantages of using these methods and the associated experimental considerations. The general approaches to improve IVIVE by use of appropriate scalars, incorporation of extrahepatic metabolism and transport and application of physiologically based pharmacokinetic (PBPK) models with proteomics data are also discussed. The chapter also provides an overview of the advantages of using such dynamic mechanistic models over static models for clearance predictions to improve IVIVE.
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Lang J, Vincent L, Chenel M, Ogungbenro K, Galetin A. Impact of Hepatic CYP3A4 Ontogeny Functions on Drug–Drug Interaction Risk in Pediatric Physiologically‐Based Pharmacokinetic/Pharmacodynamic Modeling: Critical Literature Review and Ivabradine Case Study. Clin Pharmacol Ther 2020; 109:1618-1630. [DOI: 10.1002/cpt.2134] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 11/21/2020] [Indexed: 12/14/2022]
Affiliation(s)
- Jennifer Lang
- Centre for Applied Pharmacokinetic Research Division of Pharmacy and Optometry, School of Health Sciences Faculty of Biology, Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester UK
| | - Ludwig Vincent
- Centre de Pharmacocinétique et Métabolisme Technologie Servier Orléans France
| | - Marylore Chenel
- Clinical Pharmacokinetics and Pharmacometrics Institut de Recherches Internationales Servier Suresnes France
| | - Kayode Ogungbenro
- Centre for Applied Pharmacokinetic Research Division of Pharmacy and Optometry, School of Health Sciences Faculty of Biology, Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester UK
| | - Aleksandra Galetin
- Centre for Applied Pharmacokinetic Research Division of Pharmacy and Optometry, School of Health Sciences Faculty of Biology, Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester UK
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A GFR-Based Method to Predict the Effect of Renal Impairment on the Exposure or Clearance of Renally Excreted Drugs: A Comparative Study Between a Simple GFR Method and a Physiologically Based Pharmacokinetic Model. Drugs R D 2020; 20:377-387. [PMID: 33150526 PMCID: PMC7641486 DOI: 10.1007/s40268-020-00327-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/15/2020] [Indexed: 12/19/2022] Open
Abstract
Objective The objective of this study was to compare the predictive performances of a glomerular filtration rate (GFR) model with a physiologically based pharmacokinetic (PBPK) model to predict total or renal clearance or area under the curve of renally excreted drugs in subjects with varying degrees of renal impairment. Methods From the literature, 11 studies were randomly selected in which total or renal clearance or area under the curve of drugs in subjects with different degrees of renal impairment were predicted by PBPK models. In these published studies, drugs were given to subjects intravenously or orally. The PBPK model was generally a whole-body model whereas the GFR model was as follows: Predicted total clearance (CLT) = CLT in healthy subjects × (GFR in RI/GFR in H), Predicted AUC = AUC in healthy subjects × (GFR in H/GFR in RI), where H is the healthy subjects and RI is renal impairment. The predicted clearance or area under the curve values using PBPK and GFR models were compared with the observed (experimental pharmacokinetic) values. The acceptable prediction error was within the 0.5- to 2-fold or 0.5- to 1.5-fold prediction error. Results There were 33 drugs with a total number of 101 observations (area under the curve, total and renal clearance in subjects with mild, moderate, and severe renal impairment). From PBPK and GFR models, out of 101 observations, 94 (93.1%) and 96 (95.0%) observations were within the 0.5- to 2-fold prediction error, respectively. Conclusions This study indicates that the predictive power of a simple GFR model is similar to a PBPK model for the prediction of clearance or area under the curve in subjects with renal impairment. The GFR method is simple, robust, and reliable and can replace complex empirical PBPK models.
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Lang J, Vincent L, Chenel M, Ogungbenro K, Galetin A. Simultaneous Ivabradine Parent-Metabolite PBPK/PD Modelling Using a Bayesian Estimation Method. AAPS JOURNAL 2020; 22:129. [DOI: 10.1208/s12248-020-00502-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Accepted: 08/18/2020] [Indexed: 12/14/2022]
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Wu F, Zhou Y, Li L, Shen X, Chen G, Wang X, Liang X, Tan M, Huang Z. Computational Approaches in Preclinical Studies on Drug Discovery and Development. Front Chem 2020; 8:726. [PMID: 33062633 PMCID: PMC7517894 DOI: 10.3389/fchem.2020.00726] [Citation(s) in RCA: 106] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Accepted: 07/14/2020] [Indexed: 12/11/2022] Open
Abstract
Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.
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Affiliation(s)
- Fengxu Wu
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Dongguan, China
- Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan, China
| | - Yuquan Zhou
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Dongguan, China
- The Second School of Clinical Medicine, Guangdong Medical University, Dongguan, China
| | - Langhui Li
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Dongguan, China
- Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan, China
| | - Xianhuan Shen
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Dongguan, China
- Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan, China
| | - Ganying Chen
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Dongguan, China
- The Second School of Clinical Medicine, Guangdong Medical University, Dongguan, China
| | - Xiaoqing Wang
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Dongguan, China
- Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan, China
| | - Xianyang Liang
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Dongguan, China
- The Second School of Clinical Medicine, Guangdong Medical University, Dongguan, China
| | - Mengyuan Tan
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Dongguan, China
- Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan, China
| | - Zunnan Huang
- Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Dongguan, China
- Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan, China
- Marine Biomedical Research Institute of Guangdong Zhanjiang, Zhanjiang, China
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Martins FS, Zhu P, Heinrichs MT, Sy SKB. Physiologically based pharmacokinetic-pharmacodynamic evaluation of meropenem plus fosfomycin in paediatrics. Br J Clin Pharmacol 2020; 87:1012-1023. [PMID: 32638408 DOI: 10.1111/bcp.14456] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 05/26/2020] [Accepted: 06/25/2020] [Indexed: 12/15/2022] Open
Abstract
AIMS The objective of the current study was to evaluate paediatric dosing regimens for meropenem plus fosfomycin that generate sufficient coverage against multidrug-resistant bacteria. METHODS The physiologically based pharmacokinetic (PBPK) models of meropenem and fosfomycin were developed from previously published pharmacokinetic studies in five populations: healthy subjects of Japanese origin, and healthy adults, geriatric, paediatric and renally impaired of primarily Caucasian origins. Pharmacodynamic (PD) analyses were carried out by evaluating dosing regimens that achieved a ≥90% joint probability of target attainment (PTA), which was defined as the minimum of the marginal probabilities to achieve the target PD index of each antibiotic. For meropenem, the percentage of time over a 24-hour period wherein the free drug concentration was above the minimum inhibitory concentration (fT > MIC) of at least 40% was its PD target. The fosfomycin PD index was described by fAUC/MIC of at least 40.8. RESULTS For coadministration consisting of 20 mg/kg meropenem q8h as a 3-hour infusion and 35 mg/kg fosfomycin q8h also as a 3-hour infusion in a virtual paediatric population between 1 month and 12 years of age with normal renal function and a corresponding body weight between 3 and 50 kg, a joint PTA ≥ 90% is achieved at MICs of 16 and 64 mg/L for meropenem and fosfomycin coadministration, respectively, against Klebsiella pneumoniae and Pseudomonas aeruginosa. CONCLUSION The current study identified potentially effective paediatric dosing regimens for meropenem plus fosfomycin coadministration against multidrug-resistant bacteria.
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Affiliation(s)
- Frederico S Martins
- Faculty of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Peijuan Zhu
- Clinical Pharmacology & Pharmacometrics, Janssen Research & Development LLC, Raritan, NJ, USA
| | - M Tobias Heinrichs
- Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Sherwin K B Sy
- Department of Statistics, State University of Maringá, Paraná, Brazil
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Predicting Pharmacokinetics of a Tenofovir Alafenamide Subcutaneous Implant Using Physiologically Based Pharmacokinetic Modelling. Antimicrob Agents Chemother 2020; 64:AAC.00155-20. [PMID: 32423957 DOI: 10.1128/aac.00155-20] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 05/09/2020] [Indexed: 02/06/2023] Open
Abstract
Long-acting (LA) administration using a subcutaneous (s.c.) implant presents opportunities to simplify administration of antiretroviral drugs, improve pharmacological profiles, and overcome suboptimal adherence associated with daily oral formulations. Tenofovir alafenamide (TAF) is a highly potent nucleoside reverse transcriptase inhibitor (NRTI) and an attractive agent for LA delivery, with a high potency and long intracellular half-life. The aim of this study was to predict minimum TAF doses required to achieve concentrations effective for HIV preexposure prophylaxis (PrEP). Daily drug release requirements were then ascertained by averaging across the dosing interval. A TAF physiologically based pharmacokinetic (PBPK) model was developed and partially qualified against available oral single- and multiple-dose pharmacokinetics. The models were assumed to be qualified when simulated values were within 2-fold of the observed mean. TAF s.c. implants were simulated in five hundred individuals, reporting predicted TAF plasma and tenofovir (TFV) plasma concentrations for various release rates. Intracellular TFV diphosphate (TFV-DP) concentrations were also simulated in peripheral blood cells and cervical and rectal tissues. The minimum dose predicted to achieve intracellular TFV-DP levels above a target concentration of 48 fmol/106 cells for a month was identified. TAF, TFV, and TFV-DP concentrations for release rates between 1.0 and 1.6 mg/day were simulated. The PBPK model indicated that a minimum release of 1.4 mg/day TAF is necessary to achieve TFV-DP concentrations above the identified target in peripheral blood mononuclear cells (PBMCs). TFV-DP cervical and rectal tissue concentrations were predicted to be between 1.5 and 2.0 fmol/106 cells and 0.9 and 1.1 fmol/106 cells, respectively, for release rates between 1.3 and 1.6 mg/day. These simulations provide target minimum doses for LA TAF PrEP in humans. Based on the generated results, multiple implants delivering a total of 1.4 mg/day of TAF subcutaneously could provide protection levels for approximately 6 months to 1 year. This modeling may inform future design of s.c. implants to mitigate adherence issues for effective PrEP applications.
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Methaneethorn J, Naosang K, Kaewworasut P, Poomsaidorn C, Lohitnavy M. Development of a Physiologically-Based Pharmacokinetic Model of Δ9-Tetrahydrocannabinol in Mice, Rats, and Pigs. Eur J Drug Metab Pharmacokinet 2020; 45:487-494. [DOI: 10.1007/s13318-020-00616-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Bahia M, Hecke M, Mercuri E, Pinheiro M. A bone remodeling model governed by cellular micromechanics and physiologically based pharmacokinetics. J Mech Behav Biomed Mater 2020; 104:103657. [DOI: 10.1016/j.jmbbm.2020.103657] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 01/11/2020] [Accepted: 01/23/2020] [Indexed: 11/29/2022]
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Rajoli RKR, Curley P, Chiong J, Back D, Flexner C, Owen A, Siccardi M. Predicting Drug-Drug Interactions Between Rifampicin and Long-Acting Cabotegravir and Rilpivirine Using Physiologically Based Pharmacokinetic Modeling. J Infect Dis 2020; 219:1735-1742. [PMID: 30566691 DOI: 10.1093/infdis/jiy726] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Accepted: 12/17/2018] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Cabotegravir and rilpivirine are 2 long-acting (LA) antiretrovirals that can be administered intramuscularly; their interaction with rifampicin, a first-line antituberculosis agent, has not been investigated. The aim of this study was to simulate and predict drug-drug interactions (DDIs) between these LA antiretroviral agents and rifampicin using physiologically based pharmacokinetic (PBPK) modeling. METHODS The designed PBPK models were qualified (according to European Medicines Agency guidelines) against observed data for oral formulations of cabotegravir, rilpivirine, and rifampicin. Induction potential of rifampicin was also qualified by comparing the DDI between oral cabotegravir and oral rilpivirine with rifampicin. Qualified PBPK models were utilized for pharmacokinetic prediction of DDIs. RESULTS PBPK models predicted a reduction in both area under the curve (AUC0-28 days) and trough concentration (Ctrough, 28th day) of LA cabotegravir of 41%-46% for the first maintenance dose coadministered with 600 mg once-daily oral rifampicin. Rilpivirine concentrations were predicted to decrease by 82% for both AUC0-28 days and Ctrough, 28th day following the first maintenance dose when coadministered with rifampicin. CONCLUSIONS The developed PBPK models predicted the theoretical effect of rifampicin on cabotegravir and rilpivirine LA intramuscular formulations. According to these simulations, it is likely that coadministration of rifampicin with these LA formulations will result in subtherapeutic concentrations of both drugs.
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Affiliation(s)
- Rajith K R Rajoli
- Department of Molecular and Clinical Pharmacology, University of Liverpool, United Kingdom
| | - Paul Curley
- Department of Molecular and Clinical Pharmacology, University of Liverpool, United Kingdom
| | - Justin Chiong
- Department of Molecular and Clinical Pharmacology, University of Liverpool, United Kingdom
| | - David Back
- Department of Molecular and Clinical Pharmacology, University of Liverpool, United Kingdom
| | - Charles Flexner
- Johns Hopkins University School of Medicine and Bloomberg School of Public Health, Baltimore, Maryland
| | - Andrew Owen
- Department of Molecular and Clinical Pharmacology, University of Liverpool, United Kingdom
| | - Marco Siccardi
- Department of Molecular and Clinical Pharmacology, University of Liverpool, United Kingdom
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Recent advances in physiologically based pharmacokinetic and pharmacodynamic models for anticancer nanomedicines. Arch Pharm Res 2020; 43:80-99. [PMID: 31975317 DOI: 10.1007/s12272-020-01209-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 01/09/2020] [Indexed: 02/07/2023]
Abstract
Nanoparticles (NPs) have distinct pharmacokinetic (PK) properties and can potentially improve the absorption, distribution, metabolism, and elimination (ADME) of small-molecule drugs loaded therein. Owing to the unwanted toxicities of anticancer agents in healthy organs and tissues, their precise delivery to the tumor is an essential requirement. There have been numerous advancements in the development of nanomedicines for cancer therapy. Physiologically based PK (PBPK) models serve as excellent tools for describing and predicting the ADME properties and the efficacy and toxicity of drugs, in combination with pharmacodynamic (PD) models. The recent preliminary application of these modeling approaches to NPs demonstrated their potential benefits in research and development processes relevant to the ADME and pharmacodynamics of NPs and nanomedicines. Here, we comprehensively review the pharmacokinetics of NPs, the developed PBPK models for anticancer NPs, and the developed PD model for anticancer agents.
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Prediction of the pharmacokinetics and pharmacodynamics of topiroxostat in humans by integrating the physiologically based pharmacokinetic model with the drug-target residence time model. Biomed Pharmacother 2020; 121:109660. [DOI: 10.1016/j.biopha.2019.109660] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 11/03/2019] [Accepted: 11/06/2019] [Indexed: 01/12/2023] Open
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Tylutki Z, Szlęk J, Polak S. CardiacPBPK: A tool for the prediction and visualization of time-concentration profiles of drugs in heart tissue. Comput Biol Med 2019; 115:103484. [PMID: 31606584 DOI: 10.1016/j.compbiomed.2019.103484] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 10/03/2019] [Accepted: 10/04/2019] [Indexed: 11/18/2022]
Abstract
BACKGROUND AND OBJECTIVE Prediction of drug concentration in heart tissue is important in terms of drug safety and efficacy. This work presents the Open-Source CardiacPBPK platform for the prediction of the time-concentration profile of drugs, which could potentially reduce the risk of drug development failure due to cardiotoxicity. The objective of the CardiacPBPK development is to accelerate and simplify the in-silico toxicological assessment of new drugs, and to provide supportive material for the research community to use. METHODS The CardiacPBPK software provides a modular implementation of the PBPK model of heart tissue. It can be easily accessed via the Internet or installed locally. The graphical user interface and tabular design are easy to configure and use. RESULTS CardiacPBPK is a tool designed to predict and visualize the time-concentration profiles of a parent compound, and one metabolite, in venous plasma and heart tissue after oral or intravenous drug administration. CardiacPBPK is built on the R-environment framework and supports shiny application features such as interactive visualization of the results, and web applications interface by default. A shiny application refers to a computer program created with the use of shiny package in R. The application is freely available at https://github.com/jszlek/CardiacPBPK and https://sourceforge.net/projects/cardiacpbpk/. This open-source application runs on all platforms supporting R-environment (Linux, Windows, Mac OS X, Solaris). CONCLUSIONS We demonstrate the application of CardiacPBPK by simulating the study of amitriptyline intoxication in the case of CYP2D6 genetic polymorphism.
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Affiliation(s)
- Zofia Tylutki
- Unit of Pharmacoepidemiology and Pharmacoeconomics, Department of Social Pharmacy, Faculty of Pharmacy, Jagiellonian University Medical College, Krakow, Poland; Certara UK - Simcyp Division, Sheffield, UK
| | - Jakub Szlęk
- Department of Pharmaceutical Technology and Biopharmaceutics, Jagiellonian University Medical College, Krakow, Poland.
| | - Sebastian Polak
- Unit of Pharmacoepidemiology and Pharmacoeconomics, Department of Social Pharmacy, Faculty of Pharmacy, Jagiellonian University Medical College, Krakow, Poland; Certara UK - Simcyp Division, Sheffield, UK
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Rajoli RKR, Flexner C, Chiong J, Owen A, Donnelly RF, Larrañeta E, Siccardi M. Modelling the intradermal delivery of microneedle array patches for long-acting antiretrovirals using PBPK. Eur J Pharm Biopharm 2019; 144:101-109. [PMID: 31525446 DOI: 10.1016/j.ejpb.2019.09.011] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 08/01/2019] [Accepted: 09/12/2019] [Indexed: 01/10/2023]
Abstract
INTRODUCTION Existing HIV therapy using oral antiretrovirals (ARVs) can result in pill fatigue and sub-optimal adherence. Microneedle array patches (MAPs) offer non-invasive, blood-free and painless drug delivery, and may improve patient adherence. The objective of this study was to develop a novel physiologically-based pharmacokinetic (PBPK) model to simulate the systemic pharmacokinetics of cabotegravir and rilpivirine MAPs using the intradermal route. METHODS The developed PBPK models were qualified against observed pharmacokinetic data after intramuscular (IM) and intradermal administration of long-acting nanoformulated rilpivirine to rats, and for IM administration of both drugs to healthy adults. Qualified models were then utilised to estimate suitable MAP characteristics (e.g. nanoformulation dose and release rates) and inform dosing strategies to maintain plasma concentrations above target trough concentrations for the designated dosing interval. RESULTS PBPK models simulated q4-weekly loading and maintenance doses of 360 mg and 180 mg for long-acting formulated cabotegravir between the release rates of 1 × 10-3-3 × 10-3h-1 and 1 × 10-3-1.5 × 10-3h-1 respectively, for a 70 kg adult. Estimated patch size was 60 cm2 for a 360 mg dose of cabotegravir. For q4-weekly dosing, rilpivirine required a 1080 mg loading dose and a 540 mg maintenance dose with release rates of 1.5 × 10-3-2.5 × 10-3h-1 and 5 × 10-4-1 × 10-3h-1, respectively. Weekly dosing was also evaluated to assess the potential application from a smaller patch size. The ability to self-administer via a patch that is only left in place for a short duration makes longer durations less important than for some other long-acting approaches. Weekly cabotegravir required 60 mg between release rates 7 × 10-3-9 × 10-3h-1 and rilpivirine required 270 mg and 180 mg respectively between release rates of 7 × 10-3-9 × 10-3h-1. DISCUSSION This model estimated optimal dose and release rates for cabotegravir and rilpivirine MAPs. Our approach provides a computational platform to support rational development of intradermal administration strategies to tackle problems associated with chronic oral ARV administration.
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Affiliation(s)
- Rajith K R Rajoli
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK.
| | - Charles Flexner
- Johns Hopkins University School of Medicine and Bloomberg School of Public Health, Baltimore, MD, USA
| | - Justin Chiong
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Andrew Owen
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Ryan F Donnelly
- School of Pharmacy, Queen's University Belfast, Medical Biology Centre, Belfast, UK
| | - Eneko Larrañeta
- School of Pharmacy, Queen's University Belfast, Medical Biology Centre, Belfast, UK
| | - Marco Siccardi
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK.
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Tsiros P, Bois FY, Dokoumetzidis A, Tsiliki G, Sarimveis H. Population pharmacokinetic reanalysis of a Diazepam PBPK model: a comparison of Stan and GNU MCSim. J Pharmacokinet Pharmacodyn 2019; 46:173-192. [PMID: 30949914 DOI: 10.1007/s10928-019-09630-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Accepted: 03/25/2019] [Indexed: 11/29/2022]
Abstract
The aim of this study is to benchmark two Bayesian software tools, namely Stan and GNU MCSim, that use different Markov chain Monte Carlo (MCMC) methods for the estimation of physiologically based pharmacokinetic (PBPK) model parameters. The software tools were applied and compared on the problem of updating the parameters of a Diazepam PBPK model, using time-concentration human data. Both tools produced very good fits at the individual and population levels, despite the fact that GNU MCSim is not able to consider multivariate distributions. Stan outperformed GNU MCSim in sampling efficiency, due to its almost uncorrelated sampling. However, GNU MCSim exhibited much faster convergence and performed better in terms of effective samples produced per unit of time.
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Affiliation(s)
- Periklis Tsiros
- School of Chemical Engineering, National Technical University of Athens, 9 Heroon Polytechneiou Street, Zografou Campus, 15780, Athens, Greece
| | - Frederic Y Bois
- Unit Modles pour l'Ecotoxicologie et la Toxicologie (METO), Institut National de l'Environnement Industriel et des Risques (INERIS), Parc ALATA BP2, 60550, Verneuil en Halatte, France
| | - Aristides Dokoumetzidis
- Department of Pharmacy, University of Athens, Panepistimiopolis Zografou, 15784, Athens, Greece
| | - Georgia Tsiliki
- ATHENA Research and Innovation Centre, Artemidos 6 & Epidavrou, Marousi, Athens, 15125, Greece
| | - Haralambos Sarimveis
- School of Chemical Engineering, National Technical University of Athens, 9 Heroon Polytechneiou Street, Zografou Campus, 15780, Athens, Greece.
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Pierrillas PB, Henin E, Ball K, Ogier J, Amiel M, Kraus-Berthier L, Chenel M, Bouzom F, Tod M. Prediction of Human Nonlinear Pharmacokinetics of a New Bcl-2 Inhibitor Using PBPK Modeling and Interspecies Extrapolation Strategy. Drug Metab Dispos 2019; 47:648-656. [PMID: 30940629 DOI: 10.1124/dmd.118.085605] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Accepted: 03/26/2019] [Indexed: 01/05/2023] Open
Abstract
S 55746 ((S)-N-(4-hydroxyphenyl)-3-(6-(3-(morpholinomethyl)-1,2,3,4-tetrahydroisoquinoline-2-carbonyl)benzo[d][1,3]dioxol-5-yl)-N-phenyl-5,6,7,8-tetrahydroindolizine-1-carboxamide) is a new selective Bcl-2 (B-cell lymphoma 2) inhibitor developed by Servier Laboratories and used to restore apoptosis functions in cancer patients. The aim of this work was to develop a translational approach using physiologically based (PB) pharmacokinetic (PK) modeling for interspecies extrapolation to anticipate the nonlinear PK behavior of this new compound in patients. A PBPK mouse model was first built using a hybrid approach, defining scaling factors (determined from in vitro data) to correct in vitro clearance parameters and predicted Kp (partition coefficient) values. The qualification of the hybrid model using these empirically determined scaling factors was satisfactorily completed with rat and dog data, allowing extrapolation of the PBPK model to humans. Human PBPK simulations were then compared with clinical trial data from a phase 1 trial in which the drug was given orally and daily to cancer patients. Human PBPK predictions were within the 95% prediction interval for the eight dose levels, taking into account both the nonlinear dose and time dependencies occurring in S 55746 kinetics. Thus, the proposed PK interspecies extrapolation strategy, based on preclinical and in vitro information and physiologic assumptions, could be a useful tool for predicting human plasma concentrations at the early stage of drug development.
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Affiliation(s)
- Philippe B Pierrillas
- Equipe mixte de recherche 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, Oullins, France (P.P., E.H., M.T.); Pharmacie Hôpital de la Croix Rousse, Hospices Civils de Lyon, Lyon, France (M.T.); Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France (P.P., F.B.); Clinical Pharmacokinetics and Pharmacometrics Division, Servier, Suresnes, France (K.B., J.O., M.A., M.C.); and Institut de Recherches Internationales Servier, Oncology R&D Unit, Suresnes, France (L.K-B.)
| | - Emilie Henin
- Equipe mixte de recherche 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, Oullins, France (P.P., E.H., M.T.); Pharmacie Hôpital de la Croix Rousse, Hospices Civils de Lyon, Lyon, France (M.T.); Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France (P.P., F.B.); Clinical Pharmacokinetics and Pharmacometrics Division, Servier, Suresnes, France (K.B., J.O., M.A., M.C.); and Institut de Recherches Internationales Servier, Oncology R&D Unit, Suresnes, France (L.K-B.)
| | - Kathryn Ball
- Equipe mixte de recherche 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, Oullins, France (P.P., E.H., M.T.); Pharmacie Hôpital de la Croix Rousse, Hospices Civils de Lyon, Lyon, France (M.T.); Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France (P.P., F.B.); Clinical Pharmacokinetics and Pharmacometrics Division, Servier, Suresnes, France (K.B., J.O., M.A., M.C.); and Institut de Recherches Internationales Servier, Oncology R&D Unit, Suresnes, France (L.K-B.)
| | - Julien Ogier
- Equipe mixte de recherche 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, Oullins, France (P.P., E.H., M.T.); Pharmacie Hôpital de la Croix Rousse, Hospices Civils de Lyon, Lyon, France (M.T.); Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France (P.P., F.B.); Clinical Pharmacokinetics and Pharmacometrics Division, Servier, Suresnes, France (K.B., J.O., M.A., M.C.); and Institut de Recherches Internationales Servier, Oncology R&D Unit, Suresnes, France (L.K-B.)
| | - Magali Amiel
- Equipe mixte de recherche 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, Oullins, France (P.P., E.H., M.T.); Pharmacie Hôpital de la Croix Rousse, Hospices Civils de Lyon, Lyon, France (M.T.); Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France (P.P., F.B.); Clinical Pharmacokinetics and Pharmacometrics Division, Servier, Suresnes, France (K.B., J.O., M.A., M.C.); and Institut de Recherches Internationales Servier, Oncology R&D Unit, Suresnes, France (L.K-B.)
| | - Laurence Kraus-Berthier
- Equipe mixte de recherche 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, Oullins, France (P.P., E.H., M.T.); Pharmacie Hôpital de la Croix Rousse, Hospices Civils de Lyon, Lyon, France (M.T.); Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France (P.P., F.B.); Clinical Pharmacokinetics and Pharmacometrics Division, Servier, Suresnes, France (K.B., J.O., M.A., M.C.); and Institut de Recherches Internationales Servier, Oncology R&D Unit, Suresnes, France (L.K-B.)
| | - Marylore Chenel
- Equipe mixte de recherche 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, Oullins, France (P.P., E.H., M.T.); Pharmacie Hôpital de la Croix Rousse, Hospices Civils de Lyon, Lyon, France (M.T.); Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France (P.P., F.B.); Clinical Pharmacokinetics and Pharmacometrics Division, Servier, Suresnes, France (K.B., J.O., M.A., M.C.); and Institut de Recherches Internationales Servier, Oncology R&D Unit, Suresnes, France (L.K-B.)
| | - François Bouzom
- Equipe mixte de recherche 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, Oullins, France (P.P., E.H., M.T.); Pharmacie Hôpital de la Croix Rousse, Hospices Civils de Lyon, Lyon, France (M.T.); Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France (P.P., F.B.); Clinical Pharmacokinetics and Pharmacometrics Division, Servier, Suresnes, France (K.B., J.O., M.A., M.C.); and Institut de Recherches Internationales Servier, Oncology R&D Unit, Suresnes, France (L.K-B.)
| | - Michel Tod
- Equipe mixte de recherche 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, Oullins, France (P.P., E.H., M.T.); Pharmacie Hôpital de la Croix Rousse, Hospices Civils de Lyon, Lyon, France (M.T.); Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France (P.P., F.B.); Clinical Pharmacokinetics and Pharmacometrics Division, Servier, Suresnes, France (K.B., J.O., M.A., M.C.); and Institut de Recherches Internationales Servier, Oncology R&D Unit, Suresnes, France (L.K-B.)
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Walker E, Leclerc M, Rey JF, Beaudouin R, Soubeyrand S, Messéan A. A Spatio-Temporal Exposure-Hazard Model for Assessing Biological Risk and Impact. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2019; 39:54-70. [PMID: 29228505 DOI: 10.1111/risa.12941] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
We developed a simulation model for quantifying the spatio-temporal distribution of contaminants (e.g., xenobiotics) and assessing the risk of exposed populations at the landscape level. The model is a spatio-temporal exposure-hazard model based on (i) tools of stochastic geometry (marked polygon and point processes) for structuring the landscape and describing the exposed individuals, (ii) a dispersal kernel describing the dissemination of contaminants from polygon sources, and (iii) an (eco)toxicological equation describing the toxicokinetics and dynamics of contaminants in affected individuals. The model was implemented in the briskaR package (biological risk assessment with R) of the R software. This article presents the model background, the use of the package in an illustrative example, namely, the effect of genetically modified maize pollen on nontarget Lepidoptera, and typical comparisons of landscape configurations that can be carried out with our model (different configurations lead to different mortality rates in the treated example). In real case studies, parameters and parametric functions encountered in the model will have to be precisely specified to obtain realistic measures of risk and impact and accurate comparisons of landscape configurations. Our modeling framework could be applied to study other risks related to agriculture, for instance, pathogen spread in crops or livestock, and could be adapted to cope with other hazards such as toxic emissions from industrial areas having health effects on surrounding populations. Moreover, the R package has the potential to help risk managers in running quantitative risk assessments and testing management strategies.
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Affiliation(s)
- Emily Walker
- BioSP, INRA, Avignon, France
- EcoInnov, INRA, Thiverval-Grignon, France
| | | | | | - Rémy Beaudouin
- INERIS, Unité Modèles pour l'Ecotoxicologie et la Toxicologie (METO), Institut National de l'Environnement Industriel et des Risques (INERIS), Verneuil en Halatte, France
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Prediction of Clearance and Dose of Midazolam in Preterm and Term Neonates: A Comparative Study Between Allometric Scaling and Physiologically Based Pharmacokinetic Modeling. Am J Ther 2019; 26:e32-e37. [DOI: 10.1097/mjt.0000000000000506] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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45
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Scherholz ML, Androulakis IP. Exploration of sexual dimorphism and inter-individual variability in multivariate parameter spaces for a pharmacokinetic compartment model. Math Biosci 2018; 308:70-80. [PMID: 30557560 DOI: 10.1016/j.mbs.2018.12.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 12/13/2018] [Accepted: 12/13/2018] [Indexed: 11/24/2022]
Abstract
Pharmacokinetic models are particularly useful to study the underlying and complex physiological mechanisms contributing to clinical differences across patient subgroups or special populations. Unfortunately, the inherent variability of biological systems and knowledge gaps in physiological data limit confidence in model predictions for special populations. Sourcing data to reflect the desired physiologies can be resource intensive, particularly for a larger model. Thus, a critical step in model development for special populations involves an in-depth analysis of model inputs, which can be guided by Monte Carlo simulations. Such an approach enables the generation of parameter values by stochastic sampling that are subsequently restricted to the combinations that describe biologically plausible or target model output. Our approach utilized a published pharmacokinetic compartmental model to demonstrate how sampling in conjunction with global sensitivity analysis can be used to explore sexual dimorphism and inter-individual variability in multivariate parameter spaces for differentiation of model input and behavior across phenotypes. Despite limiting the model output to relatively narrow ranges, male and female phenotypes were associated with wide variability in both individual parameter values and combinations of parameters. Through an integrated approach using a support vector machine, principal component analysis and global sensitivity analysis, our approach revealed that specific combinations of parameters gave rise to a certain phenotype, while individual parameters influenced the shape of plasma concentration profile. Augmenting analysis of the model input with global sensitivity analysis enabled an understanding of both sexual dimorphism and inter-individual variability in pharmacokinetics. While the current study revealed how model input could be separated by sex for a simple compartment model, the approach could be extended to other patient factors, such as age or disease, and to a more complex physiologically-based model that describes absorption, distribution, metabolism, and elimination with more detail.
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Affiliation(s)
- Megerle L Scherholz
- Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, 98 Brett Road, Piscataway, NJ 08854, United States
| | - Ioannis P Androulakis
- Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, 98 Brett Road, Piscataway, NJ 08854, United States; Department of Biomedical Engineering, Rutgers, The State University of New Jersey, 599 Taylor Road, Piscataway, NJ 08854, United States.
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Michelet R, Van Bocxlaer J, Allegaert K, Vermeulen A. The use of PBPK modeling across the pediatric age range using propofol as a case. J Pharmacokinet Pharmacodyn 2018; 45:765-785. [PMID: 30298439 DOI: 10.1007/s10928-018-9607-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Accepted: 09/25/2018] [Indexed: 12/12/2022]
Abstract
The project SAFEPEDRUG aims to provide guidelines for drug research in children, based on bottom-up and top-down approaches. Propofol, one of the studied model compounds, was selected because it is extensively metabolized in liver and kidney, with an important role for the glucuronidation pathway. Besides, being a lipophilic molecule, it is distributed into fat tissues, from where it redistributes into the systemic circulation. In the past, both bottom-up (Physiologically based pharmacokinetic, PBPK) and top-down approaches (population pharmacokinetic, popPK) were applied to describe its pharmacokinetics (PK). In this work, a combination of the two was used to check their performance to describe PK in children and neonates (both term and preterm) using propofol as a case compound. First, in vitro data was generated in human liver microsomes and recombinant enzymes and used to develop an adult PBPK model in Simcyp®. Activity adjustment factors (AAFs) were calculated to account for differences between in vitro and in vivo enzyme activity. Clinical data were analyzed using a 3-compartment model in NONMEM. These data were used to construct a retrograde PBPK model and for qualification of the PBPK models. Once an accurate in vivo clearance was obtained accounting for the contribution of the different metabolic pathways, the resulting PBPK models were challenged with new data for qualification. After that, the constructed adult PPBK model for propofol was extrapolated to the pediatric population. Both the default built-in and in vivo derived ontogeny functions were used to do so. The models were qualified by comparing their predicted PK parameters to published values, and by comparison of predicted concentration-time profiles to available clinical data. Clearance values were predicted well, especially when compared with values obtained from trials where long-term sampling was applied, whereas volume of distribution was lower compared to the most common popPK model predictions. Concentration-time profiles were predicted well up until and including the preterm neonatal population. In this work, it was thus shown that PBPK can be used to predict the PK up to and including the preterm neonatal population without the use of pediatric in vivo data. This work adds weight to the need for further development of PBPK models, especially regarding distribution modeling and the use of in vivo derived ontogeny functions.
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Affiliation(s)
- Robin Michelet
- Laboratory of Medical Biochemistry and Clinical Analysis, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium.
| | - Jan Van Bocxlaer
- Laboratory of Medical Biochemistry and Clinical Analysis, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
| | - Karel Allegaert
- Department of Development & Regeneration, KU Leuven, Leuven, Belgium.,Division of Neonatology, Department of Pediatrics, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - An Vermeulen
- Laboratory of Medical Biochemistry and Clinical Analysis, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
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Mahmood I, Tegenge MA. A Comparative Study Between Allometric Scaling and Physiologically Based Pharmacokinetic Modeling for the Prediction of Drug Clearance From Neonates to Adolescents. J Clin Pharmacol 2018; 59:189-197. [DOI: 10.1002/jcph.1310] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 08/09/2018] [Indexed: 12/20/2022]
Affiliation(s)
- Iftekhar Mahmood
- Office of Tissue & Advanced Therapies; Center for Biologics Evaluation and Research; Food & Drug Administration; Silver Spring MD USA
| | - Million A. Tegenge
- Office of Biostatistics & Epidemiology; Center for Biologics Evaluation and Research; Food & Drug Administration; Silver Spring MD USA
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Evaluation of the whole body physiologically based pharmacokinetic (WB-PBPK) modeling of drugs. J Theor Biol 2018; 451:1-9. [DOI: 10.1016/j.jtbi.2018.04.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Revised: 04/22/2018] [Accepted: 04/23/2018] [Indexed: 11/17/2022]
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Snowden TJ, van der Graaf PH, Tindall MJ. Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models. J Pharmacokinet Pharmacodyn 2018; 45:537-555. [PMID: 29582349 PMCID: PMC6061126 DOI: 10.1007/s10928-018-9584-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Accepted: 03/14/2018] [Indexed: 11/27/2022]
Abstract
In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale.
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Affiliation(s)
- Thomas J. Snowden
- Department of Mathematics and Statistics, University of Reading, Reading, RG6 6AX UK
- Certara QSP, University of Kent Innovation Centre, Canterbury, CT2 7FG UK
| | - Piet H. van der Graaf
- Certara QSP, University of Kent Innovation Centre, Canterbury, CT2 7FG UK
- Leiden Academic Centre for Drug Research, Universiteit Leiden, 2333 CC Leiden, The Netherlands
| | - Marcus J. Tindall
- Department of Mathematics and Statistics, University of Reading, Reading, RG6 6AX UK
- The Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6UR UK
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Donovan MD, Abduljalil K, Cryan JF, Boylan GB, Griffin BT. Application of a physiologically-based pharmacokinetic model for the prediction of bumetanide plasma and brain concentrations in the neonate. Biopharm Drug Dispos 2018; 39:125-134. [DOI: 10.1002/bdd.2119] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Revised: 12/06/2017] [Accepted: 12/19/2017] [Indexed: 12/30/2022]
Affiliation(s)
- Maria D. Donovan
- Pharmacodelivery Group, School of Pharmacy; University College Cork; Cork Ireland
- Department of Anatomy and Neuroscience; University College Cork; Cork Ireland
| | | | - John F. Cryan
- Department of Anatomy and Neuroscience; University College Cork; Cork Ireland
- Alimentary Pharmabiotic Centre; University College Cork; Cork Ireland
| | - Geraldine B. Boylan
- Department of Paediatrics and Child Health; University College Cork; Cork Ireland
- Irish Centre for Fetal and Neonatal Translational Research; University College Cork and Cork University Maternity Hospital; Cork Ireland
| | - Brendan T. Griffin
- Pharmacodelivery Group, School of Pharmacy; University College Cork; Cork Ireland
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