Good体外报告标准指南(GIVReSt) -供利益相关者讨论和背景文件的草案。

ALTEX Pub Date : 2025-01-01 DOI:10.14573/altex.2507041
Ronit Mohapatra, Marcel Leist, Sonja von Aulock, Thomas Hartung
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引用次数: 0

摘要

实验室间细胞培养实验的可重复性需要通过确保科学论文中更完整地报告方法来提高。这里建议的最低报告标准涵盖了各种细胞培养方法,包括单层细胞、干细胞、类器官和微生理系统(MPS)。这些标准建立在现有指南的基础上,如良好细胞培养规范(GCCP 2.0)和经合组织关于如何保证体外工作质量的测试报告指南,重点是报告的透明度和完整性。报告的关键要素包括细胞来源和鉴定、细胞质量控制和表征、使用的材料和试剂、培养条件和方案、实验设计、数据分析、数据可用性以及法律和伦理方面的全部细节。对于复杂的模型,需要提供额外的细节,如细胞比例、微环境条件、功能表征等。良好体外报告标准(GIVReSt)指南是一项更广泛的循证毒理学倡议的一部分,该倡议包括提高体外研究的质量,以进行安全评估和监管决策。总之,GIVReSt通过提供关于报告透明度和严谨性的明确标准,解决了报告不完整作为影响细胞培养实验可重复性的主要因素。人工智能(AI)的整合被设想为简化合规性检查,提供实时反馈,并通过使高质量证据更容易获得来加速科学发现。这将导致更可靠的细胞培养研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Guidance for Good In Vitro Reporting Standards (GIVReSt) - A draft for stakeholder discussion and background documentation.

Reproducibility of cell culture experiments between laboratories needs to be improved by ensuring more complete reporting of methodology in scientific papers. The minimum reporting standards sug-gested here cover various cell culture methods including monolayers, stem cells, organoids, and microphysiological systems (MPS). The standards build on existing guidance like Good Cell Culture Practice (GCCP 2.0) and OECD test reporting guidelines on how to quality-assure in vitro work, focusing on transparency and completeness of reporting. Key elements to be reported include full details of cell source and identity, cell quality control and characterization, materials and reagents used, culture conditions and protocols, experimental design, data analysis, data availability, and legal and ethical aspects. For complex models, additional details need to be provided such as cell ratios, microenvironment conditions, functional characterization, etc. The guidance for Good In Vitro Reporting Standards (GIVReSt) is part of a broader initiative of evidence-based toxicology encompassing the improvement of the quality of in vitro studies for safety assessments and regulatory decisions. In summary, GIVReSt addresses incomplete reporting as a major factor affecting repro-ducibility of cell culture experiments by providing clear standards around transparency and rigor in reporting. The integration of agentic artificial intelligence (AI) is envisioned to streamline compliance checking, providing real-time feedback and accelerating scientific discovery by making high-quality evidence more accessible. This should lead to more reliable cell culture research overall.

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