Next generation risk assessment (NGRA): Bridging in vitro points-of-departure to human safety assessment using physiologically-based kinetic (PBK) modelling ? A case study of doxorubicin with dose metrics considerations

被引:12
|
作者
Li, Hequn [1 ]
Yuan, Haitao [2 ]
Middleton, Alistair [1 ]
Li, Jin [1 ]
Nicol, Beate [1 ]
Carmichael, Paul [1 ]
Guo, Jiabin [2 ]
Peng, Shuangqing [2 ]
Zhang, Qiang [3 ]
机构
[1] Unilever Safety & Environm Assurance Ctr, Colworth Sci Pk, Sharnbrook MK44 1LQ, Beds, England
[2] Acad Mil Med Sci, Inst Dis Control & Prevent, Evaluat & Res Ctr Toxicol, Beijing 100071, Peoples R China
[3] Emory Univ, Dept Environm Hlth, Rollins Sch Publ Hlth, Atlanta, GA 30322 USA
基金
中国国家自然科学基金;
关键词
Next generation risk assessment; Physiologically-based kinetic modelling; Dose metrics; New approach methodologies; REFRACTORY MULTIPLE-MYELOMA; ALDO-KETO REDUCTASES; ADRIAMYCIN CONCENTRATIONS; INDUCED CARDIOTOXICITY; CATION TRANSPORTER; REVERSE DOSIMETRY; CONSUMER SAFETY; PHASE-I; TOXICITY; PHARMACOKINETICS;
D O I
10.1016/j.tiv.2021.105171
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
Using the chemical doxorubicin (DOX), the objective of the present study was to evaluate the impact of dose metrics selection in the new approach method of integrating physiologically-based kinetic (PBK) modelling and relevant human cell-based assays to inform a priori the point of departure for human health risk. We reviewed the literature on the clinical consequences of DOX treatment to identify dosing scenarios with no or mild cardiotoxicity observed. Key concentrations of DOX that induced cardiomyocyte toxicity in vitro were derived from studies of our own and others. A human population-based PBK model of DOX was developed and verified against pharmacokinetic data. The model was then used to predict plasma and extracellular and intracellular heart concentrations of DOX under selected clinical settings and compared with in vitro outcomes, based on several dose metrics: Cmax (maximum concentration) or AUC (area under concentration-time curve) in free or total form of DOX. We found when using in vitro assays to predict cardiotoxicity for DOX, AUC is a better indicator. Our study illustrates that when appropriate dose metrics are used, it is possible to combine PBK modelling with in vitro-derived toxicity information to define margins of safety and predict low-risk human exposure levels.
引用
收藏
页数:12
相关论文
共 5 条
  • [1] Application of physiologically based kinetic (PBK) modelling in the next generation risk assessment of dermally applied consumer products
    Moxon, Thomas E.
    Li, Hequn
    Lee, Mi-Young
    Piechota, Przemyslaw
    Nicol, Beate
    Pickles, Juliette
    Pendlington, Ruth
    Sorrell, Ian
    Baltazar, Maria Teresa
    TOXICOLOGY IN VITRO, 2020, 63
  • [2] Predicting points of departure for risk assessment based on in vitro cytotoxicity data and physiologically based kinetic (PBK) modeling: The case of kidney toxicity induced by aristolochic acid I
    Abdullah, Rozaini
    Alhusainy, Wasma
    Woutersen, Jasper
    Rietjens, Ivonne M. C. M.
    Punt, Ans
    FOOD AND CHEMICAL TOXICOLOGY, 2016, 92 : 104 - 116
  • [3] Considering developmental neurotoxicity in vitro data for human health risk assessment using physiologically-based kinetic modeling: deltamethrin case study
    Maass, Christian
    Schaller, Stephan
    Dallmann, Andre
    Bothe, Kathrin
    Mueller, Dennis
    TOXICOLOGICAL SCIENCES, 2023, 192 (01) : 59 - 70
  • [4] The GARDskin Dose-Response assay for determination of a point-of- departure (PoD) for Next Generation Risk Assessment (NGRA) of skin sensitizers: A case study using isocyclocitral
    Nahlstedt, P.
    Donthamsetty, S.
    Sterchele, P.
    Huang, X.
    Ladics, G.
    Na, M.
    Lee, I.
    Api, A. M.
    Gradin, R.
    Johansson, H.
    Forreryd, A.
    TOXICOLOGY LETTERS, 2023, 384 : S261 - S261
  • [5] Advancing PFAS risk assessment: Integrative approaches using agent-based modelling and physiologically-based kinetic for environmental and health safety
    Iulini, Martina
    Russo, Giulia
    Crispino, Elena
    Paini, Alicia
    Fragki, Styliani
    Corsini, Emanuela
    Pappalardo, Francesco
    COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2024, 23 : 2763 - 2778