Differential Analysis on Changes in Medical Device Software

医疗器械软件变化差异分析

• 批准号: 1160603
• 负责人: Laurie Williams
• 金额: $ 6万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2014-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1160603&HistoricalAwards=false
• 关键词: Differential; Analysis; Changes; Medical; Device

This project is a collaboration under the NSF-FDA Scholar-In-Residence (SIR) program. Software increasingly is used in safety-critical medical devices. Given the safety-critical nature of software controlling medical devices, regulatory agencies are endowed by the government with authority to allow only software meeting with high standards of quality to be put into use. For example, the US Food and Drug Administration (FDA) prohibits a medical device from being marketed unless it can be reasonably trusted as safe and effective. Moreover, if a device on the market is reported to fail and cause health consequences to patients, the FDA has the right to take corrective actions, such as post-market reviews of the device to find the root cause of the failure. As medical device technology evolves, so does the software upon which the technology often relies. Changes in device software, after it has been approved or cleared by the FDA, may compromise the safety of that device. Assessing the safety of such changes presents special challenges to regulators at the FDA. To address these challenges in the context of regulation at the FDA, the research develops differential analysis techniques using the technology of dynamic symbolic execution to assess the effects of software changes on device safety. The research explores new techniques for addressing unique requirements and challenges posed by differential analysis in the context of FDA regulation. These techniques also advance the fundamental state of the art in differential analysis. Among the broader impacts of the project includes integration of the research into education programs and enhancement of teaching and research infrastructure.

该项目是NSF-FDA常驻学者(SIR)计划下的一项合作。软件越来越多地被用于安全关键的医疗设备。鉴于控制医疗设备的软件具有安全关键性质，政府赋予监管机构权力，只允许符合高标准质量的软件投入使用。例如，美国食品和药物管理局(FDA)禁止销售一种医疗设备，除非它被合理地信任为安全有效。此外，如果市场上的一种设备被报告出现故障并对患者造成健康后果，FDA有权采取纠正措施，例如对该设备进行上市后审查，以找到故障的根本原因。随着医疗设备技术的发展，该技术经常依赖的软件也在发展。在FDA批准或批准之后，设备软件的更改可能会危及该设备的安全性。评估这些变化的安全性给FDA的监管机构带来了特殊的挑战。为了在FDA监管的背景下应对这些挑战，该研究开发了使用动态符号执行技术的差异分析技术，以评估软件更改对设备安全的影响。这项研究探索了在FDA法规的背景下解决差异分析提出的独特要求和挑战的新技术。这些技术也提高了差分分析的基本技术水平。该项目的更广泛影响包括将研究纳入教育方案以及加强教学和研究基础设施。