Conclusion

The scale and complexity of current forensic projects, such as large backlogs of data bank / casework samples, large-scale MFIs or MPDs, have reached a level where these projects can greatly benefit from the utilization of LIS-assisted automation technologies. The throughput and sample tracking capabilities afforded by LIS-driven automated liquid handlers will contribute to substantial reductions in backlogs and improvements in process quality, sample tracking confidence and turn-around time. Although these instruments have tremendous capacity, they address aspects of laboratory processing that tend not to limit throughput. The labor-intensive procedures of data review, data collation, enforcement of quality control standards and formatting results for submission to databases stand to benefit from the introduction of automated data review applications. Expert systems to assist with casework mixture deconvolution are emerging and will benefit from a consensus on mixture interpretation from the forensic community. Familial searching algorithms would provide investigative assistance in cases where perpetrators are not yet registered in offender data banks. The victim identification of large-scale MFIs and MPDs has greatly benefited from LIS-based large-scale comparative genotyping applications to achieve their mandates, and larger throughput capabilities are being developed. These LIS-based technologies will continue to evolve and take full advantage of the information content of available forensic genotypic data.

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