AI-boosted ‘smart PCR’ testing offers promise

3 minute read


Adelaide researchers say even a small improvement in PCR using artificial intelligence has the potential to make a huge impact in public health.


Applying machine learning to DNA profiling has created promising new inroads into critical DNA testing, say Flinders University researchers.

They say their findings have the potential to make a huge impact in public health as well as other sectors like forensics and even national security.

PCR (polymerase chain reaction) DNA profiling has enabled the rapid and efficient collection and analysis of large amounts of data or samples, but little had changed since it was developed in the 1980s said Flinders University academic Dr Duncan Taylor, from Forensic Science SA.

“Even a small improvement in PCR performance could have a huge impact on the hundreds of thousands of forensic and intelligence DNA samples amplified every year – notably when samples are degraded,” he said.

The new research, published in the journal Genes, found significant improvements both in the quality of DNA profiling and more efficient PCR cycling conditions with the use of artificial intelligence methods, said College of Science and Engineering PhD candidate Caitlin McDonald, who led the study.

“Our system has the potential to overcome challenges that have hindered forensic scientists for decades, especially with trace, inhibited, and degraded samples,” says McDonald, who recently presented on the study at the International Society of Forensic Genetics conference.

“By intelligently optimising PCR for a wide variety of sample types, it can dramatically enhance amplification success, delivering more reliable results in even the most complex cases.

“Beyond forensics, this system has the capacity to revolutionise other fields that depend on PCR, such as clinical diagnostics and environmental monitoring, by boosting efficiency, reducing errors, and enabling high-throughput analysis across diverse applications.”

PCR is a common laboratory technique used to amplify or copy small segments of genetic material, for example in DNA fingerprinting, diagnosing genetic disorders or detecting bacteria or viruses such as covid.

Backed by other Flinders University’s College of Science and Engineering experts, including Professor Adrian Linacre and AI computer scientist Associate Professor Russell Brinkworth, the study used machine learning to create new so-called “smart PCR” systems – targeting large-scale potential alterations and faster cycling conditions for rapid and more accurate results.

The researchers then conducted large-scale tests of the new systems.

Flinders University Professor Linacre, who focuses on DNA forensic technologies, said PCR was widely used across various fields and applications, including forensic science, animal research, medicine, and national security.

“AI and machine learning are so new, yet harnessed correctly, have the possibility to greatly increase the sensitivity of PCR testing,” said Professor Linacre.

“With further research, these AI-ML methods have potential to improve the quality of DNA evidence used in criminal investigations, and to increase the quality trace DNA samples, enhancing the criminal justice process.”

Associate Professor of autonomous systems Russell Brinkworth said improving existing processes would further define AI applications in the future. 

“Traditionally DNA amplification required all settings to be in place before the process commenced. This did not take into account the many possible differences between samples and conditions,” he said.

“By utilising advances in machine learning and sensors, we have changed the process of PCR from a one-size-fits-all to a customised and optimised individual experience, producing higher quality and quantity DNA faster than previously possible.”

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