STTR Phase I: Advancing DNA Testing with a Novel Platform for Processing Touch Biological Evidence

STTR 第一阶段：利用处理触摸生物证据的新型平台推进 DNA 检测

• 批准号: 2243209
• 负责人: Martha Philpott
• 金额: $ 27.06万
• 依托单位: RAPID FORENSIC CELL TYPING, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2243209&HistoricalAwards=false
• 关键词: STTR; Phase; Advancing; DNA; Testing

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project addresses two societal issues in the justice system: an individual's constitutional right to a speedy trial, and inherent human biases in law enforcement when gathering and processing evidence. Backlogs in processing DNA evidence can lead to extended jail time for defendants unable to post bail and may violate their rights, particularly for crimes they did not commit. Rapid analysis of evidence samples can free up court dockets and save money for institutions holding people awaiting trials due to testing backlogs. In addition, the number of people exonerated by the re-analysis of forensic evidence after serving years in prison rises every year, underscoring the potential impact that testing decisions can have for individuals, families, and society at large. This technology reduces the number of samples tested and the potential for sample selection bias by rapidly identifying which samples may be probative to the investigation and thus warrant DNA testing. The proposed project will develop a new technology that utilizes flow cytometry to analyze non-genetic attributes of cell populations within forensic evidence. This technology will allow forensic laboratories to rapidly determine the probative value of samples before DNA profiling. Machine learning algorithms will compare morphological measurements and autofluorescence properties of individual cells recovered from ‘touch’ epidermal cells to identify features that vary with attributes of the person who deposited the cells (e.g., chronological age, biological sex, and/or ancestry). This technology will enable forensic laboratories to rapidly identify which samples have biological material that is probative to the case and which samples have biological material that is unrelated. This will allow labs to prioritize samples for DNA testing more precisely and potentially provide key contextual information for the sample. By allocating resources more efficiently, this innovation will reduce costs, speed up results and reporting, and reduce delays in DNA testing turn-around times. The solution will also prevent undue delays in the legal system, improve the accuracy of case analysis, and ultimately improve the quality and reliability of forensic analysis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这一小型企业技术转移（STTR）项目的更广泛的影响/商业潜力解决了司法系统中的两个社会问题：个人的快速审判宪法权利，并在收集和处理证据时继承了执法人员的人类偏见。在处理DNA证据方面的积压会导致延长入狱时间，因为被告无法公布保释并可能侵犯其权利，特别是对于他们没有犯下的罪行。对证据样本的快速分析可以释放法院码头，并为由于测试积压而等待审判的人的机构节省资金。此外，每年入狱数年后，通过重新分析法医证据而被免除的人数强调了测试决策可能对个人，家庭和整个社会产生的潜在影响。该技术通过快速识别哪些样品可能对投资有问题，从而保证DNA测试，从而减少了测试样品的数量和样品选择偏见的潜力。拟议的项目将开发一种新技术，该技术利用流式细胞仪来分析法医证据中细胞群体的非遗传属性。这项技术将使法医实验室能够在DNA分析之前迅速确定样品的问题值。机器学习算法将比较从“触摸”表皮细胞中回收的单个细胞的形态测量和自动荧光性能，以识别随着沉积细胞的属性而变化的特征（例如，年代年龄，生物学性别，生物学性别和/或祖先）。这项技术将使法医实验室能够快速确定哪些样品具有对病例有问题的生物学材料，哪些样品具有无关的生物学材料。这将使实验室可以更精确地对样本进行优先级，并可能为样本提供关键的上下文信息。通过更有效地分配资源，这项创新将降低成本，加快结果和报告，并减少DNA测试转机时间的延迟。该解决方案还将防止法律体系中的延误，提高案例分析的准确性，并最终提高法医分析的质量和可靠性。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子的优点和更广泛的影响来审查标准，被认为是通过评估来获得的支持。