DuPont Haskell Global Centers for Health and Environmental Sciences, 1090 Elkton Road, Newark, DE 19711, USA.
Regul Toxicol Pharmacol. 2013 Mar;65(2):259-68. doi: 10.1016/j.yrtph.2012.12.008. Epub 2013 Jan 3.
Advances in high throughput and high content (HT/HC) methods such as those used in the fields of toxicogenomics, bioinformatics, and computational toxicology have the potential to improve both the efficiency and effectiveness of toxicity evaluations and risk assessments. However, prior to use, scientific confidence in these methods should be formally established. Traditional validation approaches that define relevance, reliability, sensitivity and specificity may not be readily applicable. HT/HC methods are not exact replacements for in vivo testing, and although run individually, these assays are likely to be used as a group or battery for decision making and use robotics, which may be unique in each laboratory setting. Building on the frameworks developed in the 2010 Institute of Medicine Report on Biomarkers and the OECD 2007 Report on (Q)SAR Validation, we present constructs that can be adapted to address the validation challenges of HT/HC methods. These are flexible, transparent, and require explicit specification of context and purpose of use such that scientific confidence (validation) can be defined to meet different regulatory applications. Using these constructs, we discuss how anchoring the assays and their prediction models to Adverse Outcome Pathways (AOPs) could facilitate the interpretation of results and support scientifically defensible fit-for-purpose applications.
高通量和高内涵 (HT/HC) 方法的进展,如毒理基因组学、生物信息学和计算毒理学领域中使用的方法,有可能提高毒性评估和风险评估的效率和效果。然而,在使用之前,应该正式确立对这些方法的科学信心。传统的验证方法,如定义相关性、可靠性、灵敏度和特异性,可能不容易适用。HT/HC 方法不能完全替代体内测试,虽然可以单独进行,但这些检测可能会作为一组或一组电池用于决策,并使用机器人,这在每个实验室环境中可能是独特的。在 2010 年美国医学研究所关于生物标志物的报告和经合组织 2007 年关于 (Q)SAR 验证的报告中制定的框架的基础上,我们提出了可以适应 HT/HC 方法验证挑战的结构。这些结构灵活、透明,并需要明确指定使用的上下文和目的,以便能够定义科学信心(验证),以满足不同的监管应用。使用这些结构,我们讨论了如何将检测及其预测模型锚定到不良结局途径 (AOP),以促进结果的解释,并支持具有科学依据的、适合特定用途的应用。