July 13, 2024

Helmy Eltoukhy is the chairman and co-CEO of a leading precision oncology company Guardant Health.

The $1,000 Genome. Much was promised when the scientific community reached this momentous milestone: Every newborn would be sequenced at birth, human disease would be solved and unimaginable longevity would be within our grasp.

That milestone has come and gone, and yet humanity still struggles with many common illnesses as it did thousands of years ago. So, what went wrong? Even with the promise of genome sequencing, what hurdles should those in the diagnostics industry consider?

The Evolution Of Genome Sequencing

I began my career in genomics back in 2000 when the first human genome was sequenced, which at the time cost an estimated $1 billion to sequence. The science was promising while the cost inaccessible. I was involved in various National Institute of Health-funded research initiatives to get us to $100,000 per genome and subsequently $1,000 per genome and then worked on research for advanced versions of genome sequencers.

Many of us, myself included, overestimated the value of sequencing the genome itself, which is to decode the sequence of four letters (A’s, C’s, G’s, T’s ) that make up the three billion-letter-long word that is an individual’s unique genome.

The same three billion letters sit inside almost every cell of one’s body, all 37 trillion of them. Make no mistake, the ability to read the genome is a powerful tool—leading to solutions for rare and inherited diseases, better cancer therapies and our ability to combat infectious diseases with vaccines and create more potent drugs. However, the cures to many other common illnesses such as diabetes, inflammatory diseases, neurodegenerative diseases or various cardiovascular diseases remain elusive. The reality is many of these diseases do not change the sequence of letters in the genome as is the case for cancer or many rare diseases.

New Frontiers In Disease Detection

I think one important reason that DNA sequencing has not been the panacea we had hoped for is that traditional sequencing has been blind to another very important feature of the genome. This feature answers the common question: If every one of the cells in our body has the same genome, why do liver cells look different than skin cells and eye cells?

The reason lies in the aforementioned three billion letters that encode more than 20,000 genes, of which some markers or switches determine which genes are off and on in each cell. The state of those switches determines the functionality of a cell, how it looks and what it does. This is referred to as the epigenome. It also turns out that almost every disease leaves a robust fingerprint on the epigenome of the affected cell.

By tracking the collective state of those switches in blood, it turns out that one can detect deadly conditions like cancer early. Detecting the epigenome in blood, while very powerful for early cancer detection, may only be the beginning of its utility. I believe that it’s likely that routine sequencing of the cell-free epigenome in blood may unlock our ability to detect many other diseases early—almost certainly inflammatory and liver diseases, cardiovascular disease and perhaps even neurodegenerative diseases too. The ability to quantitatively detect and track such diseases through a simple blood test could lead to an exponential growth in our ability to treat them.

Caveats To Watch For With New Healthcare Technologies

As the cost of analyzing billions of markers in our blood moves closer to zero than $1,000, the future looks to continue to become brighter.

So what will we do with such a deluge of information? Obviously, this presents an exciting time for the diagnostics industry, but there are a number of caveats to watch out for.

1. Focus On Utility Over Information

Inventing a new shovel does not automatically mean one has found gold, just as discovering new biological data does not mean one has solved a disease. The ability to sequence the human genome at low cost spawned many start-ups that have all but disappeared given the lack of actionable data.

2. Business Model Innovation Often Trumps Technological Innovation In Healthcare

Healthcare is a land of entrenched incumbents, many of which are fiercely protecting their domain and the status quo. This is why healthcare is one of the few industries we still see employing fax machines and pagers. One needs to determine how best to support technological innovation in a sustainable way within the constraints of the existing system.

3. Start Small By Addressing A Single Area Of High Unmet Need

Even the largest tech companies in the world have failed when trying to disrupt healthcare’s Goliaths. But like David, one needs to be humble, start modestly with five smooth stones and aim wisely.

Once the new technology is established and embedded within the system, one can rapidly expand the indications of use and become a Goliath in due time.

I think intuitive surgical or immunotherapies, such as Keytruda, are great examples of starting with a single indication and reinvesting rapidly over time to scale operations to serve patients. As another example, my company launched liquid biopsies for advanced cancer patients by starting with lung cancer and expanding to multiple types of cancer over time.

I think the next decade will truly be exciting as healthcare entrepreneurs unleash new tools and the amount of data that physicians will then have at their fingertips during a routine visit will be unfathomable.

Indeed, to keep up, physicians will need the healthcare equivalent of today’s exciting genAI technologies, akin to Microsoft’s CoPilot, to help them process an individual’s medical data. In this bright future, I believe we will then have the ability to detect disease before it’s born when a cure through lifestyle changes and preventative medicine are still possible.

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