A systematic review of in vitro models of drug-induced kidney injury

被引:21
作者
Irvine, Alasdair R. [1 ]
van Berlo, Damien [1 ,2 ]
Shekhani, Rawan [1 ]
Masereeuw, Rosalinde [1 ]
机构
[1] Univ Utrecht, Utrecht Inst Pharmaceut Sci UIPS, Div Pharmacol, David de Wied Bldg,Univ 99, NL-3584 CG Utrecht, Netherlands
[2] Natl Inst Publ Hlth & Environm, Antonie van Leeuwenhoeklaan 9, NL-3721 MA Bilthoven, Netherlands
基金
欧盟地平线“2020”;
关键词
In vitro models; Toxicity testing; Validation strategies; Systematic; review; Nephrotoxicity; NEPHROTOXIC COMPOUNDS; TOXICITY; LIVER; IFOSFAMIDE; BIOMARKERS; COCULTURE; HUMANS; CELLS;
D O I
10.1016/j.cotox.2021.06.001
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
Drug-induced nephrotoxicity is a major cause of kidney dysfunction with potentially fatal consequences and can hamper the research and development of new pharmaceuticals. This emphasises the need for new methods for earlier and more accurate diagnosis to avoid drug-induced kidney injury. Here, we present a systematic review of the available approaches to study drug-induced kidney injury, as one of the most common reasons for drug withdrawal, in vitro. The systematic review approach was selected to ensure that our findings are as objective and reproducible as possible. A novel study quality checklist, named validation score, was developed based on published regulatory guidance and industrial perspectives, and models returned by the search strategy were analysed as per their overall complexity and the kidney region studied. Our search strategy returned 1731 articles supplemented by 337 from secondary sources, of which 57 articles met the inclusion criteria for final analysis. Our results show that the proximal tubule dominates the field (84%), followed by the glomerulus and Bowman's capsule (7%). Of all drugs investigated, the focus was most on cisplatin (n = 29, 50.1% of final inclusions). We found that with increasing model complexity the validation score increased, reflecting the value of innovative in vitro models. Furthermore, although the highly diverse usage of cell lines and modelling approaches prevented a strong statistical verification through a meta-analysis, our findings show the downstream potential of such approaches in personalised medicine and for rare diseases where traditional trials are not feasible.
引用
收藏
页码:18 / 26
页数:9
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