Genomics, precision medicine: 
The next healthcare revolution


JUNE 17, 2018

Fifteen years ago this month, the full human genome sequence was published for the first time, heralding a new era of medicine. This was one of the most important events in the history of genetics and molecular biology. But why was it so important? And have the hoped-for medical breakthroughs actually materialized? And what is the potential importance of AI technology for speeding up genomic sequencing and significantly reducing its cost?


Unfortunately, in order to understand and appreciate this exciting next chapter in saving human life, and fathom even a little of what is going on in genetic research and the increasing importance of artificial intelligence (AI), it’s essential to define several basic terms in genetics, without getting too technical. Most important, AI used in molecular research is at work to give us data-driven medicine or precision medicine that, as some scientists say, qualifies to be called “the democratization of diagnosis.”

Our bodies consist of millions of cells. Each cell consists of instructions for making another version of us. This set of instructions is termed a genome. Genomes are made up of DNA. DNA is a chemical code that guides and governs human growth and determines our health. Four chemical building blocks (“bases”) make up each DNA molecule. You may have heard something about “sequencing DNA” that means determining the kind of genetic information carried in a particular segment of DNA. Genes are a small section of DNA that contain instructions for characteristics like hair color. Basically, genes store information. 

We will stop here before delving too deeply into the anatomy of DNA. Suffice it to say that a copy of the human genome, containing a vast amount of information, is contained in all cells. AI combined with vast increases in computing power is accelerating the process of researching and sequencing human genomes to predict and prevent disease. Whereas the original sequencing of the human genome took 10 years and cost about $3bn, now is can take minutes and cost under $500. 

We are in the era of medicine and AI being able to perform DNA analysis virtually in real-time. A single strand of DNA is one ten-thousandth the width of a human hair. A firm called Oxford Nanopore has developed a hand-held reader that can sequence genetic material in minutes. Its hand-held reader squeezes each strand through a tiny hole and reads its electrical signals that are instantly converted into a DNA sequence.

We are hearing medical scientists predict that within the next 10 years, everyone will get sequenced at birth. What does this mean? In theory every baby born (and parent) will have an assessment of its genetic disposition to particular diseases and preventative steps can be taken accordingly. This already is happening in hundreds of hospitals in countries throughout the world with new technology that also is collecting and analyzing diagnostics information from hundreds of thousands of patients. And thanks to AI and algorithms, this technology can analyze billions of data points in just a few minutes. Tests that would normally take months can now be done in hours.


Cancer is one of the diseases benefiting most. Doctors are able to diagnose a patient’s cancer by comparing diagnostic information instantly with tens of thousands of other patients and the types of treatment that worked best for persons with exactly similar types of cancer. AI engines now can harness radiomics: the ability to extract useful information from medical images, for example, tumors. The combined AI/radiomics capability enables predictions of how a tumor is likely to develop. 

Without hype, this is a revolution in healthcare: increasing numbers of patients are being diagnosed and matched with treatments using precision medicine, AI and computing power to integrate data and insights from the genetic drivers of disease. Whereas in traditional medicine we wait until people are sick to treat them, using a combination of genomic analysis with metabolic profiling, blending algorithms and genomic data, patient’s conditions can evaluated in a matter of minutes.

Some of the most important impacts of AI are not visible and newsworthy. For example, AI is at its best when it has a large amount of data to work with. So thousands of companies, research institutions and universities in more than 100 countries are collaborating and sharing data to enable physicians to identify causative genetic variants of diseases. We are seeing the emergence of a vast global database that, harnessing AI and cloud-based computing power, is driving the development of next generation genomic R&D. Of course, with advances in sharing of data comes challenges for data privacy but that too is under control by extracting personal information from records.

As for the ever-present question of whether or not AI will replace or free up doctors, the consensus thus far is that it will free up doctors to do more of what they need to do.  In a sense the question already has been answered by the capabilities of AI, algorithms, and other technology to sift through unprecedented mountains of data to discover medical clues that otherwise would never have led to precision medicine’s diagnostic capabilities.