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Ozbek O, Genc DE, O. Ulgen K. Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling of Nanomaterials. ACS Pharmacol Transl Sci 2024; 7:2251-2279. [PMID: 39144562 PMCID: PMC11320736 DOI: 10.1021/acsptsci.4c00250] [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: 04/29/2024] [Revised: 06/21/2024] [Accepted: 06/26/2024] [Indexed: 08/16/2024]
Abstract
Nanoparticles (NPs) have been widely used to improve the pharmacokinetic properties and tissue distribution of small molecules such as targeting to a specific tissue of interest, enhancing their systemic circulation, and enlarging their therapeutic properties. NPs have unique and complicated in vivo disposition properties compared to small molecule drugs due to their complex multifunctionality. Physiologically based pharmacokinetic (PBPK) modeling has been a powerful tool in the simulation of the absorption, distribution, metabolism, and elimination (ADME) characteristics of the materials, and it can be used in the characterization and prediction of the systemic disposition, toxicity, efficacy, and target exposure of various types of nanoparticles. In this review, recent advances in PBPK model applications related to the nanoparticles with unique properties, and dispositional features in the biological systems, ADME characteristics, the description of transport processes of nanoparticles in the PBPK model, and the challenges in PBPK model development of nanoparticles are delineated and juxtaposed with those encountered in small molecule models. Nanoparticle related, non-nanoparticle-related, and interspecies-scaling methods applied in PBPK modeling are reviewed. In vitro to in vivo extrapolation (IVIVE) methods being a promising computational tool to provide in vivo predictions from the results of in vitro and in silico studies are discussed. Finally, as a recent advancement ML/AI-based approaches and challenges in PBPK modeling in the estimation of ADME parameters and pharmacokinetic (PK) analysis results are introduced.
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Affiliation(s)
- Ozlem Ozbek
- Chemical Engineering Department, Bogazici University, Bebek 34342 Istanbul, Turkey
| | - Destina Ekingen Genc
- Chemical Engineering Department, Bogazici University, Bebek 34342 Istanbul, Turkey
| | - Kutlu O. Ulgen
- Chemical Engineering Department, Bogazici University, Bebek 34342 Istanbul, Turkey
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2
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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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Lin Z, Aryal S, Cheng YH, Gesquiere AJ. Integration of In Vitro and In Vivo Models to Predict Cellular and Tissue Dosimetry of Nanomaterials Using Physiologically Based Pharmacokinetic Modeling. ACS NANO 2022; 16:19722-19754. [PMID: 36520546 PMCID: PMC9798869 DOI: 10.1021/acsnano.2c07312] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Nanomaterials (NMs) have been increasingly used in a number of areas, including consumer products and nanomedicine. Target tissue dosimetry is important in the evaluation of safety, efficacy, and potential toxicity of NMs. Current evaluation of NM efficacy and safety involves the time-consuming collection of pharmacokinetic and toxicity data in animals and is usually completed one material at a time. This traditional approach no longer meets the demand of the explosive growth of NM-based products. There is an emerging need to develop methods that can help design safe and effective NMs in an efficient manner. In this review article, we critically evaluate existing studies on in vivo pharmacokinetic properties, in vitro cellular uptake and release and kinetic modeling, and whole-body physiologically based pharmacokinetic (PBPK) modeling studies of different NMs. Methods on how to simulate in vitro cellular uptake and release kinetics and how to extrapolate cellular and tissue dosimetry of NMs from in vitro to in vivo via PBPK modeling are discussed. We also share our perspectives on the current challenges and future directions of in vivo pharmacokinetic studies, in vitro cellular uptake and kinetic modeling, and whole-body PBPK modeling studies for NMs. Finally, we propose a nanomaterial in vitro to in vivo extrapolation via physiologically based pharmacokinetic modeling (Nano-IVIVE-PBPK) framework for high-throughput screening of target cellular and tissue dosimetry as well as potential toxicity of different NMs in order to meet the demand of efficient evaluation of the safety, efficacy, and potential toxicity of a rapidly increasing number of NM-based products.
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Affiliation(s)
- Zhoumeng Lin
- Department
of Environmental and Global Health, College of Public Health and Health
Professions, University of Florida, Gainesville, Florida 32610, United States
- Center
for
Environmental and Human Toxicology, University
of Florida, Gainesville, Florida 32608, United
States
| | - Santosh Aryal
- Department
of Pharmaceutical Sciences and Health Outcomes, The Ben and Maytee
Fisch College of Pharmacy, The University
of Texas at Tyler, Tyler, Texas 75799, United States
| | - Yi-Hsien Cheng
- Department
of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas 66506, United States
- Institute
of Computational Comparative Medicine, Kansas
State University, Manhattan, Kansas 66506, United States
| | - Andre J. Gesquiere
- Department
of Chemistry, College of Sciences, University
of Central Florida, Orlando, Florida 32816, United States
- NanoScience
Technology Center, University of Central
Florida, Orlando, Florida 32826, United States
- Department
of Materials Science and Engineering, College of Engineering,, University of Central Florida, Orlando, Florida 32816, United States
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Klapproth AP, Shevtsov M, Stangl S, Li WB, Multhoff G. A New Pharmacokinetic Model Describing the Biodistribution of Intravenously and Intratumorally Administered Superparamagnetic Iron Oxide Nanoparticles (SPIONs) in a GL261 Xenograft Glioblastoma Model. Int J Nanomedicine 2020; 15:4677-4689. [PMID: 32669844 PMCID: PMC7335747 DOI: 10.2147/ijn.s254745] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 05/21/2020] [Indexed: 12/22/2022] Open
Abstract
Background Superparamagnetic iron oxide nanoparticles (SPIONs) have displayed multifunctional applications in cancer theranostics following systemic delivery. In an effort to increase the therapeutic potential of local therapies (including focal hyperthermia), nanoparticles can also be administered intratumorally. Therefore, the development of a reliable pharmacokinetic model for the prediction of nanoparticle distribution for both clinically relevant routes of delivery is of high importance. Materials and Methods The biodistribution of SPIONs (of two different sizes – 130 nm and 60 nm) radiolabeled with zirconium-89 or technetium-99m following intratumoral or intravenous injection was investigated in C57/Bl6 mice bearing subcutaneous GL261 glioblastomas. Based on PET/CT biodistribution data, a novel pharmacokinetic model was established for a better understanding of the pharmacokinetics of the SPIONs after both administration routes. Results The PET image analysis of the nanoparticles (confirmed by histology) demonstrated the presence of radiolabeled nanoparticles within the glioma site (with low amounts in the liver and spleen) at all investigated time points following intratumoral injection. The mathematical model confirmed the dynamic nanoparticle redistribution in the organism over a period of 72 h with an equilibrium reached after 100 h. Intravenous injection of nanoparticles demonstrated a different distribution pattern with a rapid particle retention in all organs (particularly in liver and spleen) and a subsequent slow release rate. Conclusion The mathematical model demonstrated good agreement with experimental data derived from tumor mouse models suggesting the value of this tool to predict the real-time pharmacokinetic features of SPIONs in vivo. In the future, it is planned to adapt our model to other nanoparticle formulations to more precisely describe their biodistribution in in vivo model systems.
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Affiliation(s)
- Alexander P Klapproth
- Center for Translational Cancer Research Technische Universität München (TranslaTUM), Klinikum Rechts Der Isar, Munich, Germany.,Institute of Radiation Medicine, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
| | - Maxim Shevtsov
- Center for Translational Cancer Research Technische Universität München (TranslaTUM), Klinikum Rechts Der Isar, Munich, Germany.,Institute of Cytology of the Russian Academy of Sciences (RAS), St. Petersburg, Russia.,Department of Biotechnology, First Pavlov State Medical University of St. Petersburg, St. Petersburg, Russia.,Almazov National Medical Research Centre, Russian Polenov Neurosurgical Institute, St. Petersburg, Russia.,National Center for Neurosurgery, Nur-Sultan, Kazakhstan.,Department of Biomedical Cell Technologies, Far Eastern Federal University, Vladivostok, Russia
| | - Stefan Stangl
- Center for Translational Cancer Research Technische Universität München (TranslaTUM), Klinikum Rechts Der Isar, Munich, Germany
| | - Wei Bo Li
- Institute of Radiation Medicine, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
| | - Gabriele Multhoff
- Center for Translational Cancer Research Technische Universität München (TranslaTUM), Klinikum Rechts Der Isar, Munich, Germany
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Utembe W, Clewell H, Sanabria N, Doganis P, Gulumian M. Current Approaches and Techniques in Physiologically Based Pharmacokinetic (PBPK) Modelling of Nanomaterials. NANOMATERIALS 2020; 10:nano10071267. [PMID: 32610468 PMCID: PMC7407857 DOI: 10.3390/nano10071267] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 06/03/2020] [Accepted: 06/13/2020] [Indexed: 02/08/2023]
Abstract
There have been efforts to develop physiologically based pharmacokinetic (PBPK) models for nanomaterials (NMs). Since NMs have quite different kinetic behaviors, the applicability of the approaches and techniques that are utilized in current PBPK models for NMs is warranted. Most PBPK models simulate a size-independent endocytosis from tissues or blood. In the lungs, dosimetry and the air-liquid interface (ALI) models have sometimes been used to estimate NM deposition and translocation into the circulatory system. In the gastrointestinal (GI) tract, kinetics data are needed for mechanistic understanding of NM behavior as well as their absorption through GI mucus and their subsequent hepatobiliary excretion into feces. Following absorption, permeability (Pt) and partition coefficients (PCs) are needed to simulate partitioning from the circulatory system into various organs. Furthermore, mechanistic modelling of organ- and species-specific NM corona formation is in its infancy. More recently, some PBPK models have included the mononuclear phagocyte system (MPS). Most notably, dissolution, a key elimination process for NMs, is only empirically added in some PBPK models. Nevertheless, despite the many challenges still present, there have been great advances in the development and application of PBPK models for hazard assessment and risk assessment of NMs.
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Affiliation(s)
- Wells Utembe
- National Institute for Occupational Health, P.O. Box 4788, Johannesburg 2000, South Africa; (W.U.); (N.S.)
| | - Harvey Clewell
- Ramboll US Corporation, Research Triangle Park, NC 27709, USA;
| | - Natasha Sanabria
- National Institute for Occupational Health, P.O. Box 4788, Johannesburg 2000, South Africa; (W.U.); (N.S.)
| | - Philip Doganis
- School of Chemical Engineering, National Technical University of Athens, Zografou Campus, 15780 Athens, Greece;
| | - Mary Gulumian
- National Institute for Occupational Health, P.O. Box 4788, Johannesburg 2000, South Africa; (W.U.); (N.S.)
- Hematology and Molecular Medicine, University of the Witwatersrand, Johannesburg 2000, South Africa
- Correspondence: ; Tel.: +27-11-712-6428
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Price E, Gesquiere AJ. Animal simulations facilitate smart drug design through prediction of nanomaterial transport to individual tissue cells. SCIENCE ADVANCES 2020; 6:eaax2642. [PMID: 32076633 PMCID: PMC7002136 DOI: 10.1126/sciadv.aax2642] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Accepted: 11/25/2019] [Indexed: 05/27/2023]
Abstract
Smart drug design for antibody and nanomaterial-based therapies allows optimization of drug efficacy and more efficient early-stage preclinical trials. The ideal drug must display maximum efficacy at target tissue sites, with transport from tissue vasculature to the cellular environment being critical. Biological simulations, when coupled with in vitro approaches, can predict this exposure in a rapid and efficient manner. As a result, it becomes possible to predict drug biodistribution within single cells of live animal tissue without the need for animal studies. Here, we successfully utilized an in vitro assay and a computational fluid dynamic model to translate in vitro cell kinetics (accounting for cell-induced degradation) to whole-body simulations for multiple species as well as nanomaterial types to predict drug distribution into individual tissue cells. We expect this work to assist in refining, reducing, and replacing animal testing, while providing scientists with a new perspective during the drug development process.
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Affiliation(s)
- Edward Price
- Department of Chemistry, University of Central Florida, Orlando, FL 32816, USA
- NanoScience Technology Center, University of Central Florida, Orlando, FL 32826, USA
| | - Andre J. Gesquiere
- Department of Chemistry, University of Central Florida, Orlando, FL 32816, USA
- NanoScience Technology Center, University of Central Florida, Orlando, FL 32826, USA
- Department of Materials Science and Engineering, University of Central Florida, Orlando, FL 32816, USA
- The College of Optics and Photonics (CREOL), University of Central Florida, Orlando, FL 32816, USA
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Price E, Gesquiere AJ. An in vitro assay and artificial intelligence approach to determine rate constants of nanomaterial-cell interactions. Sci Rep 2019; 9:13943. [PMID: 31558741 PMCID: PMC6763461 DOI: 10.1038/s41598-019-50208-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Accepted: 09/05/2019] [Indexed: 12/11/2022] Open
Abstract
In vitro assays and simulation technologies are powerful methodologies that can inform scientists of nanomaterial (NM) distribution and fate in humans or pre-clinical species. For small molecules, less animal data is often needed because there are a multitude of in vitro screening tools and simulation-based approaches to quantify uptake and deliver data that makes extrapolation to in vivo studies feasible. Small molecule simulations work because these materials often diffuse quickly and partition after reaching equilibrium shortly after dosing, but this cannot be applied to NMs. NMs interact with cells through energy dependent pathways, often taking hours or days to become fully internalized within the cellular environment. In vitro screening tools must capture these phenomena so that cell simulations built on mechanism-based models can deliver relationships between exposure dose and mechanistic biology, that is biology representative of fundamental processes involved in NM transport by cells (e.g. membrane adsorption and subsequent internalization). Here, we developed, validated, and applied the FORECAST method, a combination of a calibrated fluorescence assay (CF) with an artificial intelligence-based cell simulation to quantify rates descriptive of the time-dependent mechanistic biological interactions between NMs and individual cells. This work is expected to provide a means of extrapolation to pre-clinical or human biodistribution with cellular level resolution for NMs starting only from in vitro data.
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Affiliation(s)
- Edward Price
- NanoScience Technology Center, University of Central Florida, Orlando, FL, 32826, USA
- Department of Chemistry, University of Central Florida, Orlando, FL, 32816, USA
| | - Andre J Gesquiere
- NanoScience Technology Center, University of Central Florida, Orlando, FL, 32826, USA.
- Department of Chemistry, University of Central Florida, Orlando, FL, 32816, USA.
- Department of Materials Science and Engineering, University of Central Florida, Orlando, FL, 32816, USA.
- The College of Optics and Photonics (CREOL), University of Central Florida, Orlando, FL, 32816, USA.
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