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STRmix helps link Ted Bundy to 52-year-old cold case

an hour ago
By AI, Created 15:59 UTC, Nov 12, 2026, AGP -

A Utah forensic review using STRmix and related DNA testing tied Ted Bundy to the 1974 killing of 17-year-old Melissa Ann Smith, extending a yearslong effort to reexamine decades-old evidence. The match builds on earlier DNA work that connected Bundy to another Utah murder and shows how probabilistic DNA tools can reopen cold cases.

Why it matters: - STRmix helped Utah investigators connect Ted Bundy to the 1974 murder of 17-year-old Melissa Ann Smith, a 52-year-old cold case. - The case shows how modern DNA software can turn degraded or mixed evidence into usable forensic leads in old violent-crime investigations. - The result also strengthened the link between Smith’s case and another Utah murder already tied to Bundy.

What happened: - The Utah Bureau of Forensic Services used STRmix and Short Tandem Repeat DNA genotyping to reexamine evidence in the Smith case. - Forensic scientists connected the Smith evidence to a second decades-old Utah murder that had already been linked to Bundy. - Earlier this year, DNA from that second case connected Bundy to the murder of 17-year-old Laura Ann Aime. - Bundy had admitted before his 1989 execution that he killed Aime. - Investigators then used the Aime case evidence to revisit the Smith case and link Smith, Aime and Bundy. - Y-STR testing, which examines repeating DNA sequences on the male Y chromosome, further supported the conclusion that Smith was also a Bundy victim.

The details: - STRmix is used by more than 100 case-working laboratories in the U.S. to interpret complex or degraded mixed DNA profiles. - The software has been used in more than 700,000 criminal cases worldwide since its introduction in 2012. - STRmix is designed to evaluate all available DNA evidence using probabilistic modeling rather than fixed manual thresholds. - The software assesses the likelihood of different combinations of DNA contributors. - STRmix has been especially useful in violent-crime, sexual-assault and cold-case investigations. - Dr. Jo-Anne Bright, a co-developer of STRmix and senior science leader at the New Zealand Institute for Public Health and Forensic Science Limited (PHF Science), said STRmix is popular because it can interpret DNA faster than older manual methods and use more information from a DNA profile. - STRmix Limited is a wholly owned subsidiary of PHF Science, a New Zealand government research organization. - STRmix Limited was created to better serve international users of the software. - STRmix was first introduced in 2012. - The company says the software has been trusted by more than 130 forensic laboratories worldwide. - Related products include FaSTR DNA, DBLR and STRmix NGS. - FaSTR DNA integrates with STRmix to analyze raw DNA data and assign a NoC estimate. - DBLR works with STRmix to support kinship analysis, rapid database searches, mixture-to-mixture matches and visualization of DNA mixture evidence. - STRmix NGS provides continuous mixture interpretation and likelihood-ratio generation for profiles generated using next-generation sequencing. - STRmix, FaSTR DNA and DBLR are designed to cover the workflow from analysis to interpretation and database matching.

Between the lines: - The Bundy case is a high-profile example of how probabilistic genotyping can revive evidence once considered unusable. - The sequence of findings suggests that one solved cold case can help unlock another when investigators can compare degraded evidence across cases. - The software’s value is not just in producing a DNA result, but in making results statistically interpretable and admissible.

What's next: - STRmix is likely to remain a tool for cold-case reviews and other investigations involving mixed or degraded DNA. - The broader workflow around STRmix, including FaSTR DNA, DBLR and STRmix NGS, is positioned to support more laboratory use cases as forensic evidence types evolve. - For more information about STRmix, visit the company’s announcement.

Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.

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