Bringing Artificial Intelligence and Automation to Genetic Analysis

Chad Carter, vice president and general manager of Microarray Genetic Solutions at Thermo Fisher Scientific, shares his perspective on how AI is advancing genetic research and underscores Thermo Fisher’s continued commitment to investing in its microarray platform to help labs increase productivity.

For the first time in history, scientists expect to release an entire human genome by the end of 2023 [1]. Previously, the Human Genome Project released a composite human genome based on DNA from multiple people. Today, research has advanced to the point that we can now read the genome from a single human being without gaps.

While researchers are on the cusp of reading the entire human genome, the scientific community also continues to advance clinical research using genetic analysis. Thanks to advances in genetic analysis technology, scientists today are able to glean powerful, actionable insights from across a broad range of genetic targets – all from very small amounts of sample — and accurately interpret and report this data in a timely manner.

As the amount of genetic information available to the scientific community continues to grow, so does the need for more powerful, automated technology to analyze that data. Artificial intelligence (AI) will play an increasingly important role in genomics to help identify genetic disorders, improve diagnoses, advance disease research and more [3]. Chad Carter, vice president and general manager of Microarray Genetic Solutions at Thermo Fisher Scientific, says AI coupled with innovation in microarray platforms will greatly accelerate genetic analysis and interpretation, enabling labs to take their genomic research to the next level.

What is the potential for AI to improve genetic research?

Researchers today need to translate massive amounts of data – while continuing to run their lab workflows efficiently. AI can help researchers quickly prioritize the most important mutations in a sample, greatly increasing productivity for lab directors and clinical geneticists by minimizing time spent manually searching for genetic associations.

AI and advanced algorithms are expected to play an increasing role in helping researchers quickly and efficiently translate that data. Rather than comparing samples one by one, researchers want the ability to compare samples to many, many other samples. AI can provide a powerful tool for researchers to cross-reference all relevant genes and known samples of similar genetic makeup.

What types of genetic research can benefit from automation and AI?

AI is being used across genetic research applications to improve and accelerate researchers’ computing power. One area we’re focused on is improving data analysis in cytogenetic research, which looks at changes in chromosomes and is primarily used in prenatal, postnatal and cancer research. Chromosome banding analysis is the gold standard to identify cytogenetic abnormalities, and AI and automation can greatly increase efficiency for what once was a very time-consuming and complex task [4].

How is Thermo Fisher improving cytogenetic data analysis for labs?

One of the main challenges cytogeneticists have always faced is interpretation – what has changed and how important is it? Traditionally this has required a lot of manual research by mining the internet and various databases to find that information. We work closely with our customers to cater to their needs and challenges and one output of that is our Chromosome Analysis Suite (ChAS) software. ChAS is one of the most powerful analysis tools available in the industry to accurately interpret genetic information and turn it into meaningful results.

We are continuing to invest in and evolve our data analysis capabilities. For instance, last year we partnered with Genoox, a genomic data company, to further enhance researchers’ ability to streamline data analysis and get results efficiently. With our CytoScan Automated Interpretation and Reporting (AIR) Solution, ChAS customers can now access Genoox’s cloud-based AI platform, Franklin. The integration of ChAS and CytoScan AIR means researchers can develop internal databases, easily import historical cases, and correlate their results with evidence from curated data from the Franklin community. So instead of taking hours to dig through research and literature, with automated interpretation and reporting researchers can find a pathogenic association almost immediately in just a few clicks potentially saving time, money, and other precious resources.

What’s next in cytogenetic analysis?

While advances in digital automation are accelerating data analysis, we are also working on innovating our tried-and-true microarray technology to accelerate the front end of the workflow – the time to results. Later this year we are introducing Array to accelerate labs’ genetic research workflow to just two days. With faster turnaround times labs can essentially double their lab output with the exact same installed equipment base to become more efficient, productive, and profitable. The new array is designed to help researchers expand their investigations with wide-ranging coverage across critical regions while using up to 50% less sample than many commercially available chromosomal microarray analysis solutions.

Thermo Fisher is investing in our content, instruments, and assays to continue to make the microarray a more efficient and cost-effective platform for high-content genetics.

For more information, please visit thermofisher.com/reproductivehealth.

References

1. BBC | Why the human genome was never completed
2. PLOS Biology | Big Data: Astronomical or Genomical?
3. NIH | Artificial Intelligence, Machine Learning and Genomics
4. NIH | How artificial intelligence might disrupt diagnostics in hematology in the near future

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