Early Cancer Detection: Big Opportunity for Genomics Investors

Adding credibility to the long-term genomics investment thesis is the role genomics companies play in earlier cancer detection. Cancer detection is very much an “earlier the better” proposition. The earlier doctors can identify cancer in a patient, the more the odds of recovery and improved outcomes increase.

Fortunately, the actively managed ARKG is levered to some exciting trends, such as falling costs for next-generation sequencing (NGS). That’s relevant because it is very much a genomics issue, and evolving NGS capabilities are helping clinicians better understand the causes of cancer and how to spot the disease earlier.

“Fortunately, innovations involving NGS, bioinformatics, synthetic biology, and data processing have broadened our collective understanding of cancer,” writes ARK Invest analyst Simon Barnett. “Newer genomic domains like single-cell sequencing, long-read sequencing, optical mapping, and digital spatial profiling also are enhancing our understanding of tumor biology. ARK believes that the foundation of knowledge built during the past two decades will enable clinicians to detect cancer earlier and treat it more successfully.”

Something else for investors to consider is that genomics is one of the most tech-driven healthcare concepts, and ARKG is arguably the genomics ETF most levered to that trend.

“Novel approaches from biochemistry, sequencing hardware and artificial intelligence (AI) are converging and transforming oncology. Soon, with a simple non-invasive blood draw, for example, clinicians could be able to detect multiple forms of cancer in their early stages,” adds Barnett.

In fact, some genomics companies are already using machine learning to analyze thousands of blood samples to identify certain types of cancers more efficiently. That’s further confirmation of tech’s relevance in genomics and technology’s role in driving genomics costs lower.

“Our research suggests that machine learning has lowered the cost of methylation-based liquid biopsies dramatically, pushing them that much closer to commercialization,” notes Barnett. “Thanks to the plethora of methylation sites, extremely high coverage is not necessary to detect abnormally methylated tumor DNA. Because neural networks improve with more data, bigger models, and more computation, the accuracy and cost-effectiveness of liquid biopsies that include methylation is likely to increase over time.”

Machine learning is also vital in multi-analyte or multi-omic analysis, which is used to analyze DNA neomers indicating signs of cancer. Bottom line: It’s necessary to be innovative in the genomics space, and ARKG is home to plenty of innovative companies.

“The lines between and among these technologies have dissolved, encouraging if not demanding innovation and collaboration across these disciplines. Accordingly, incumbents who do not invest aggressively in R&D are likely to lose their footing in the new world,” concludes Barnett.

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