Nowadays, Quality Management tools such as failure mode and effect analysis (FMEA) are widely used throughout the aeronautical, automotive, software, food services, health care and many other industries to sustain and improve quality and safety. The increasing complexity of scientific research makes it more difficult to maintain all activities under control, in order to guarantee validity and reproducibility of results. Even in non-regulated research, scientists need to be supported with management tools that maximize study performance and outcomes, while facilitating the research process. Frequently, steps that involve human intervention are the weak links in the process. Risk analysis therefore gives considerable benefit to analytical validation, assessing and avoiding failures due to human error, potential imprecision in applying protocols, uncertainty in equipment function and imperfect control of materials. This paper describes in detail how FMEA methodology can be applied as a performance improvement tool in the field of non-regulated research, specifically on a basic Life Sciences research process. We chose as “pilot process” the selection of oligonucleotide aptamers for therapeutic purposes, as an example of a complex and multi-step process, suitable for technology transfer. We applied FMEA methodology, seeking every opportunity for error and its impact on process output, and then, a set of improvement actions was generated covering most aspects of laboratory practice, such as equipment management and staff training. We also propose a useful tool supporting the risk assessment of research processes and its outputs and that we named “FMEA strip worksheet.” These tools can help scientists working in non-regulated research to approach Quality Management and to perform risk evaluation of key scientific procedures and processes with the final aim to increase and better control efficiency and efficacy of their research.

中文翻译：

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一种基于失效模式和影响分析 (FMEA) 的方法，用于对非监管研究实验室中的科学过程进行风险评估

如今，故障模式和影响分析 (FMEA) 等质量管理工具广泛应用于航空、汽车、软件、食品服务、医疗保健和许多其他行业，以维持和提高质量和安全。科学研究的日益复杂使得更难以控制所有活动，以保证结果的有效性和可重复性。即使在不受监管的研究中，科学家也需要得到管理工具的支持，以最大限度地提高研究绩效和结果，同时促进研究过程。通常，涉及人为干预的步骤是流程中的薄弱环节。因此，风险分析为分析验证、评估和避免由于人为错误、应用方案的潜在不精确性、设备功能的不确定性和材料的不完善控制。本文详细描述了如何将 FMEA 方法用作非监管研究领域的绩效改进工具，特别是在基础生命科学研究过程中。我们选择了用于治疗目的的寡核苷酸适体的选择作为“试点过程”，作为适合技术转让的复杂和多步骤过程的一个例子。我们应用 FMEA 方法，寻找每一个错误机会及其对过程输出的影响，然后，产生了一套涵盖实验室实践的大多数方面的改进措施，例如设备管理和员工培训。我们还提出了一个有用的工具来支持研究过程及其输出的风险评估，我们将其命名为“FMEA 条形工作表”。