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

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.