Overview of in vitro-in vivo extrapolation approaches for the risk assessment of nanomaterial toxicity

被引:0
|
作者
Azizah, Rahmasari Nur [1 ,2 ]
Verheyen, Geert R. [1 ]
Shkedy, Ziv [2 ]
Van Miert, Sabine [1 ]
机构
[1] Thomas More Univ Appl Sci, Geel, Belgium
[2] Hasselt Univ, Data Sci Inst, CenStat, I BioStat, Diepenbeek, Belgium
关键词
Nanomaterial; IVIVE; Risk assessment; In vitro; in vivo; TITANIUM-DIOXIDE NANOPARTICLES; PHARMACOKINETIC MODEL; GENOTOXICITY ASSESSMENT; INFLAMMATORY RESPONSE; METAL NANOPARTICLES; GOLD NANOPARTICLES; PROTEIN CORONA; SILVER; DOSIMETRY; EXPOSURE;
D O I
10.1016/j.impact.2024.100524
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Nanomaterials are increasingly used in many applications due to their enhanced properties. To ensure their safety for humans and the environment, nanomaterials need to be evaluated for their potential risk. The risk assessment analysis on the nanomaterials based on animal or in vivo studies is accompanied by several concerns, including animal welfare, time and cost needed for the studies. Therefore, incorporating in vitro studies in the risk assessment process is increasingly considered. To be able to analyze the potential risk of nanomaterial to human health, there are factors to take into account. Utilizing in vitro data in the risk assessment analysis requires methods that can be used to translate in vitro data to predict in vivo phenomena (in vitro-in vivo extrapolation (IVIVE) methods) to be incorporated, to obtain a more accurate result. Apart from the experiments and species conversion (for example, translation between the cell culture, animal and human), the challenge also includes the unique properties of nanomaterials that might cause them to behave differently compared to the same materials in a bulk form. This overview presents the IVIVE techniques that are developed to extrapolate pharmacokinetics data or doses. A brief example of the IVIVE methods for chemicals is provided, followed by a more detailed summary of available IVIVE methods applied to nanomaterials. The IVIVE techniques discussed include the comparison between in vitro and in vivo studies, methods to rene the dose metric or the in vitro models, allometric approach, mechanistic modeling, Multiple-Path Particle Dosimetry (MPPD), methods using organ burden data and also approaches that are currently being developed.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Application of Model-Based Approaches to Evaluate Hepatic Transporter-Mediated Drug Clearance: In vitro, In vivo, and In vitro-In vivo Extrapolation
    Liu, Zhihao
    Liu, Kexin
    CURRENT DRUG METABOLISM, 2016, 17 (05) : 456 - 468
  • [22] Prediction of Unbound Fractions for in Vitro-in Vivo Extrapolation of Biotransformation Data
    Krause, Sophia
    Goss, Kai-Uwe
    CHEMICAL RESEARCH IN TOXICOLOGY, 2021, 34 (01) : 7 - 11
  • [23] In Vitro-In Vivo Extrapolation and Hepatic Clearance-Dependent Underprediction
    Bowman, Christine M.
    Benet, Leslie Z.
    JOURNAL OF PHARMACEUTICAL SCIENCES, 2019, 108 (07) : 2500 - 2504
  • [24] Prediction of hepatic and intestinal glucuronidation using in vitro-in vivo extrapolation
    Naritomi, Yoichi
    Nakamori, Fumihiro
    Furukawa, Takako
    Tabata, Kenji
    DRUG METABOLISM AND PHARMACOKINETICS, 2015, 30 (01) : 21 - 29
  • [25] Comparative assessment of In Vitro-In Vivo extrapolation methods used for predicting hepatic metabolic clearance of drugs
    Poulin, Patrick
    Hop, Cornelis E. C. A.
    Ho, Quynh
    Halladay, Jason S.
    Haddad, Sami
    Kenny, Jane R.
    JOURNAL OF PHARMACEUTICAL SCIENCES, 2012, 101 (11) : 4308 - 4326
  • [26] Development of Mechanistic In Vitro-In Vivo Extrapolation to Support Bioequivalence Assessment of Long-Acting Injectables
    Silva, Daniela Amaral
    Le Merdy, Maxime
    Alam, Khondoker Dedarul
    Wang, Yan
    Bao, Quanying
    Malavia, Nilesh
    Burgess, Diane
    Lukacova, Viera
    PHARMACEUTICS, 2024, 16 (04)
  • [27] In Vitro to In Vivo Extrapolation (IVIVE) for human health risk assessment
    Conolly, R.
    McMullin, T.
    Hines, R. N.
    Sheets, L. P.
    Cohen, S. M.
    TOXICOLOGY LETTERS, 2013, 221 : S14 - S14
  • [28] Evaluation of Various Static In Vitro-In Vivo Extrapolation Models for Risk Assessment of the CYP3A Inhibition Potential of an Investigational Drug
    Vieiral, Md L. T.
    Kirby, B.
    Ragueneau-Majlessi, I.
    Galetin, A.
    Chien, J. Y. L.
    Einolf, H. J.
    Fahmi, O. A.
    Fischer, V.
    Fretland, A.
    Grime, K.
    Hall, S. D.
    Higgs, R.
    Plowchalk, D.
    Riley, R.
    Seibert, E.
    Skordos, K.
    Snoeys, J.
    Venkatakrishnan, K.
    Waterhouse, T.
    Obach, R. S.
    Berglund, E. G.
    Zhang, L.
    Zhao, P.
    Reynolds, K. S.
    Huang, S-M
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2014, 95 (02) : 189 - 198
  • [29] In Vitro-In Vivo Extrapolation Method to Predict Human Renal Clearance of Drugs
    Kunze, Annett
    Huwyler, Joerg
    Poller, Birk
    Gutmann, Heike
    Camenisch, Gian
    JOURNAL OF PHARMACEUTICAL SCIENCES, 2014, 103 (03) : 994 - 1001
  • [30] Bioconcentration Assessment in Fish Based on In Vitro Intrinsic Clearance: Predictivity of an Empirical Model Compared to In Vitro-In Vivo Extrapolation Models
    Laue, Heike
    Hostettler, Lu
    Jenner, Karen J.
    Sanders, Gordon
    Natsch, Andreas
    ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2023, 57 (36) : 13325 - 13335