A Conversation with Professor Wing Wong, founder of GenomCan genomics startup

Amino Capital
Jun 1, 2017 · 5 min read

Genomics. It’s the fastest developing research field in computational biology, and for good reason — it seeks to restructure and redefine the way we approach medicine. When President Obama announced the new “Precision Medicine Initiative” in early 2015, he injected $130 million for the collection and research of one million donors’ DNA sequences. And in the past few years the cost of analyzing a human genome dropped from $400 million to less than $1,000, driving genomics as the latest and most promising field.

Since his appointment as professor in 2004 at Stanford University, Professor Wing Hung Wong has been researching computational models to apply to problems in precision medicine and genomic sequencing. His lab, comprised of between 12 and 15 researchers from various areas of expertise, developed software for the analysis of next generation sequencing and microarray data.

Amino Capital caught up with Professor Wing Wong to ask about his lab and the potential of genomics and precision medicine.

Your lab has a focus on precision medicine. Can you describe the research you’re conducting in that area?

We know a lot of human diseases have a strong genetic component. Over the past twenty years people have used genomic methods to try to establish associations between specific genomic regions and specific phenotypes.

The way this is usually done is by defining a specific number of individuals affected by a certain disease, let’s say children with autism. You find some people who are not affected by the disease, normal children, and then you do a genotype analysis. If you happen to see a region in which the genotype in the disease group is very different from the genotype in the control group, then that’s an indirect indication that these regions may be related to the phenotype. I call that a trait-focused or phenotype-focused approach.

But we’re trying to pursue an approach where the way you group these individuals is that you look for individuals that share serious mutations in a particular gene. Out of a million people you may find a few hundred, and from the rest you construct a control. Then you can compare those to groups, and look for phenotypes that are different.

This is just a reverse of the previous method. We’re trying to see if we can find something new that is not available than the previous methods.

What’s the benefit of this reversed approach?

The benefit is now you have the opportunity to define new phenotypes. Previously you have to start from a well-defined disease. How do people define diseases? It’s physicians from day to day practices, they say “Okay this group of people seem to share something abnormal so I’m going to call this a disease,” but that’s very haphazard. We feel like the key to defining the phenotypes is to find the right grouping of people, and what could be more natural in grouping than to use the genome?

What applications does your research have?

Recently a postdoc [of mine] returned to China and started her own company there based from our research, it’s called GenomCan. I sort of serve as an advisor and in a sense a co-founder.

They’re trying to focus on medical issues that have to do with prenatal and infant health. The earlier in life the higher the chance that some conditions are induced by genetics. A lot of childhood issues have genetic components, and she’s working with Chinese hospitals and trying to get to the interesting samples and to apply the genomic analysis to generate information.

What impacts could GenomCan have on medicine?

We are hoping to find the genetic causes that underlie a lot of the cases of infant mortality. Often the infant will have a certain condition and you don’t understand why, and if it’s serious enough it could be fatal. A lot of these cases are genetically based. If we know the genetic causes then we can try to screen for this earlier and screen for high accuracy. But if you don’t know the cause, you can’t screen.

The hope is that it will enable us to avoid the tragic situation of losing a fetus or infant.

Zooming out, what do you think is the potential of genomics research?

So much of about our health and our body is affected by the genome. Now you have the ability to see the blueprint of the body, and you can work out all the consequences. Once you workout how to interpret it, then you have ways to address any difficulty that’s due to imperfection of the desired gene. That’s the general picture. I think the genome is a very large part of medicine now, and in the future it will become even more important.

How has technology developed to allow for this research?

Twenty five years ago we didn’t have the power to generate this data, and it would take billions of dollars to even look at one person’s genome. Now you can just draw a sample of blood and send it off, and in two weeks you’ll get the complete genome.

With the development of genomics, what does the future of medicine look like?

From this point on I think medicine will transition toward situations where genome data is part of standard medical records. Like for every child the first thing you do is to get the genome as part of the permanent record, and later on you can do more sequences because of the genetic changes as a person development. Mutations and changes will occur and you will monitor those.

That will be important for the medical information, and a diagnosis will be made on top of that. It will be a basis for the rest of medicine.

When do you think this technology will developed enough to use in general practice?

I think we’re at some transition point now. I have no doubt that fifteen years from now that will be the standard. Whether that will be the standard in ten or five years, I don’t know how fast that will happen. But I’m sure it will happen, on a scale of ten to twenty years.

  • Alex Wong, a contributor to AMINO Capital medium blog

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AMINO insights

AMINO Capital is built by engineers and scientists who work tirelessly to help you win data and talents.