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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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Huang X, Li J, Yang Y, Wang ZL, Yang XZ, Lu ZD, Xu CF. Lipid-assisted PEG- b-PLA nanoparticles with ultrahigh SN38 loading capability for efficient cancer therapy. Biomater Sci 2023; 11:7445-7457. [PMID: 37819252 DOI: 10.1039/d3bm01469j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
The topoisomerase I inhibitor, 7-ethyl-10-hydroxycamptothecin (SN38), has demonstrated potent anticancer activity. However, its clinical application is hindered by its low solubility and high crystallization propensity, which further complicates its encapsulation into nanoparticles for systemic delivery. Herein, we explore the utilization of lipid-assisted poly(ethylene glycol)-block-poly(D,L-lactide) (PEG-b-PLA) nanoparticles to achieve ultrahigh loading capability for SN38. Through the introduction of cationic, anionic, or neutral lipids, the SN38 loading efficiency and loading capacity is elevated to >90% and >10% respectively. These lipids efficiently attenuate the intermolecular π-π stacking of SN38, thereby disrupting its crystalline structure. Moreover, we assess the therapeutic activity of SN38-loaded formulations in various tumor models and identify an anionic lipid 1,2-dioleoyl-sn-glycero-3-phospho-(1'-rac-glycerol) sodium salt (DOPG)-assisted formulation that exhibits the highest anticancer activity and has favorable biosafety. Overall, our findings present a simple and robust strategy to achieve ultrahigh loading efficiency of SN38 using commonly employed PEG-b-PLA nanoparticles, opening up a new avenue for the systemic delivery of SN38.
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Affiliation(s)
- Xiaoyi Huang
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, P.R. China.
| | - Jieyi Li
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, P.R. China.
| | - Yanfang Yang
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, P.R. China.
| | - Zi-Lu Wang
- School of Medicine, South China University of Technology, Guangzhou 510006, P.R. China.
| | - Xian-Zhu Yang
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, P.R. China.
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou 510006, P.R. China
- Guangdong Provincial Key Laboratory of Biomedical Engineering, South China University of Technology, Guangzhou 510006, P.R. China
| | - Zi-Dong Lu
- School of Medicine, South China University of Technology, Guangzhou 510006, P.R. China.
| | - Cong-Fei Xu
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, P.R. China.
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou 510006, P.R. China
- Key Laboratory of Biomedical Materials and Engineering of the Ministry of Education, South China University of Technology, Guangzhou 510006, P.R. China
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Han DG, Kwak J, Choi E, Seo SW, Vasileva EA, Mishchenko NP, Fedoreyev SA, Stonik VA, Kim HK, Han J, Byun JH, Jung IH, Yun H, Yoon IS. Physicochemical characterization and phase II metabolic profiling of echinochrome A, a bioactive constituent from sea urchin, and its physiologically based pharmacokinetic modeling in rats and humans. Biomed Pharmacother 2023; 162:114589. [PMID: 37004327 DOI: 10.1016/j.biopha.2023.114589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/18/2023] [Accepted: 03/21/2023] [Indexed: 04/03/2023] Open
Abstract
Echinochrome A, a natural naphthoquinone pigment found in sea urchins, is increasingly being investigated for its nutritional and therapeutic value associated with antioxidant, anticancer, antiviral, antidiabetic, and cardioprotective activities. Although several studies have demonstrated the biological effects and therapeutic potential of echinochrome A, little is known regarding its biopharmaceutical behaviors. Here, we aimed to investigate the physicochemical properties and metabolic profiles of echinochrome A and establish a physiologically-based pharmacokinetic (PBPK) model as a useful tool to support its clinical applications. We found that the lipophilicity, color variability, ultraviolet/visible spectrometry, and stability of echinochrome A were markedly affected by pH conditions. Moreover, metabolic and pharmacokinetic profiling studies demonstrated that echinochrome A is eliminated primarily by hepatic metabolism and that four possible metabolites, i.e., two glucuronidated and two methylated conjugates, are formed in rat and human liver preparations. A whole-body PBPK model incorporating the newly identified hepatic phase II metabolic process was constructed and optimized with respect to chemical-specific parameters. Furthermore, model simulations suggested that echinochrome A could exhibit linear disposition profiles without systemic and local tissue accumulation in clinical settings. Our proposed PBPK model of echinochrome A could be a valuable tool for predicting drug interactions in previously unexplored scenarios and for optimizing dosage regimens and drug formulations.
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Zambonino MC, Quizhpe EM, Mouheb L, Rahman A, Agathos SN, Dahoumane SA. Biogenic Selenium Nanoparticles in Biomedical Sciences: Properties, Current Trends, Novel Opportunities and Emerging Challenges in Theranostic Nanomedicine. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:424. [PMID: 36770385 PMCID: PMC9921003 DOI: 10.3390/nano13030424] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 01/15/2023] [Accepted: 01/17/2023] [Indexed: 06/18/2023]
Abstract
Selenium is an important dietary supplement and an essential trace element incorporated into selenoproteins with growth-modulating properties and cytotoxic mechanisms of action. However, different compounds of selenium usually possess a narrow nutritional or therapeutic window with a low degree of absorption and delicate safety margins, depending on the dose and the chemical form in which they are provided to the organism. Hence, selenium nanoparticles (SeNPs) are emerging as a novel therapeutic and diagnostic platform with decreased toxicity and the capacity to enhance the biological properties of Se-based compounds. Consistent with the exciting possibilities offered by nanotechnology in the diagnosis, treatment, and prevention of diseases, SeNPs are useful tools in current biomedical research with exceptional benefits as potential therapeutics, with enhanced bioavailability, improved targeting, and effectiveness against oxidative stress and inflammation-mediated disorders. In view of the need for developing eco-friendly, inexpensive, simple, and high-throughput biomedical agents that can also ally with theranostic purposes and exhibit negligible side effects, biogenic SeNPs are receiving special attention. The present manuscript aims to be a reference in its kind by providing the readership with a thorough and comprehensive review that emphasizes the current, yet expanding, possibilities offered by biogenic SeNPs in the biomedical field and the promise they hold among selenium-derived products to, eventually, elicit future developments. First, the present review recalls the physiological importance of selenium as an oligo-element and introduces the unique biological, physicochemical, optoelectronic, and catalytic properties of Se nanomaterials. Then, it addresses the significance of nanosizing on pharmacological activity (pharmacokinetics and pharmacodynamics) and cellular interactions of SeNPs. Importantly, it discusses in detail the role of biosynthesized SeNPs as innovative theranostic agents for personalized nanomedicine-based therapies. Finally, this review explores the role of biogenic SeNPs in the ongoing context of the SARS-CoV-2 pandemic and presents key prospects in translational nanomedicine.
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Affiliation(s)
- Marjorie C. Zambonino
- School of Biological Sciences and Engineering, Yachay Tech University, Hacienda San José s/n, San Miguel de Urcuquí 100119, Ecuador
| | - Ernesto Mateo Quizhpe
- School of Biological Sciences and Engineering, Yachay Tech University, Hacienda San José s/n, San Miguel de Urcuquí 100119, Ecuador
| | - Lynda Mouheb
- Laboratoire de Recherche de Chimie Appliquée et de Génie Chimique, Hasnaoua I, Université Mouloud Mammeri, BP 17 RP, Tizi-Ouzou 15000, Algeria
| | - Ashiqur Rahman
- Center for Midstream Management and Science, Lamar University, 211 Redbird Ln., Beaumont, TX 77710, USA
| | - Spiros N. Agathos
- Earth and Life Institute, Catholic University of Louvain, B-1348 Louvain-la-Neuve, Belgium
| | - Si Amar Dahoumane
- Department of Chemical Engineering, Polytechnique Montréal, C.P. 6079, Succ. Centre-Ville, Montréal, QC H3C 3A7, Canada
- Department of Chemistry and Biochemistry, Université de Moncton, 18, Ave Antonine-Maillet, Moncton, NB E1A 3E9, Canada
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Lebreton V, Kaeokhamloed N, Vasylaki A, Hilairet G, Mellinger A, Béjaud J, Saulnier P, Lagarce F, Gattacceca F, Legeay S, Roger E. Pharmacokinetics of intact lipid nanocapsules using new quantitative FRET technique. J Control Release 2022; 351:681-691. [DOI: 10.1016/j.jconrel.2022.09.057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 09/07/2022] [Accepted: 09/27/2022] [Indexed: 11/15/2022]
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6
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Targeting nanoparticles to malignant tumors. Biochim Biophys Acta Rev Cancer 2022; 1877:188703. [DOI: 10.1016/j.bbcan.2022.188703] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 02/01/2022] [Accepted: 02/21/2022] [Indexed: 12/12/2022]
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7
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Shanmugam H, Rengarajan C, Nataraj S, Sharma A. Interactions of plant food bioactives‐loaded nano delivery systems at the nano‐bio interface and its pharmacokinetics: An overview. FOOD FRONTIERS 2022. [DOI: 10.1002/fft2.130] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Affiliation(s)
- Haripriya Shanmugam
- Department of Nano Science and Technology Tamil Nadu Agricultural University Tamil Nadu India
| | - Chitra Rengarajan
- Department of Nano Science and Technology Tamil Nadu Agricultural University Tamil Nadu India
| | - Swathika Nataraj
- Department of Nano Science and Technology Tamil Nadu Agricultural University Tamil Nadu India
| | - Aashima Sharma
- Department of Chemistry Panjab University Chandigarh India
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Lebreton V, Legeay S, Saulnier P, Lagarce F. Specificity of pharmacokinetic modeling of nanomedicines. Drug Discov Today 2021; 26:2259-2268. [PMID: 33892140 DOI: 10.1016/j.drudis.2021.04.017] [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: 01/25/2021] [Revised: 03/30/2021] [Accepted: 04/11/2021] [Indexed: 01/08/2023]
Abstract
Nanomedicines have been developed for more than four decades to optimize the pharmacokinetics (PK) of drugs, especially absorption, distribution, and stability in vivo. Unfortunately, only a few drug products have reached the market. One reason among others is the lack of proper PK modeling and evaluation, which impedes the optimization of these promising drug delivery systems. In this review, we discuss the specificity of nanomedicines and propose key parameters to take into account for future accurate PK evaluation of nanomedicine. We believe that this could help these innovative drug products to reach to market and change the fate of many diseases.
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Affiliation(s)
- Vincent Lebreton
- University of Angers, MINT Inserm 1066 CNRS 6021, Angers, France; CHU Angers, 4 Rue Larrey, 49033 Angers, France
| | - Samuel Legeay
- University of Angers, MINT Inserm 1066 CNRS 6021, Angers, France
| | - Patrick Saulnier
- University of Angers, MINT Inserm 1066 CNRS 6021, Angers, France; CHU Angers, 4 Rue Larrey, 49033 Angers, France
| | - Frederic Lagarce
- University of Angers, MINT Inserm 1066 CNRS 6021, Angers, France; CHU Angers, 4 Rue Larrey, 49033 Angers, France.
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Multi-layered cellulose nanocrystal system for CD44 receptor-positive tumor-targeted anticancer drug delivery. Int J Biol Macromol 2020; 162:798-809. [DOI: 10.1016/j.ijbiomac.2020.06.193] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 06/12/2020] [Accepted: 06/19/2020] [Indexed: 11/22/2022]
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10
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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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