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Verge Genomics is using technology to develop new treatments for incurable diseases

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Alice Zhang headshot
Alice
Zhang, co-founder and CEO of drug discovery company Verge
Genomics

Verge
Genomics


  • Alice Zhang started Verge Genomics in 2015 with Jason
    Chen to combine innovation in neuroscience, machine learning
    and genomics and apply it to the drug discovery
    process. 
  • The vision for Verge was to become the first
    pharmaceutical company that automated its drug discovery
    engine, helping to rapidly develop multiple lifesaving
    treatments in diseases like Alzheimer’s disease, ALS, and
    Parkinson’s disease where no cure exists today. 
  • On Monday, the San Francisco-based company announced it
    had raised $32 million in series A funding, led by DFJ,
    bringing its total amount raised to $36.5 million.

The drug development process is
laden with problems that make it lengthy and expensive. Right
now, it takes 12 years and $2.6 billion to get a single drug to
market, with the drug discovery and development
process costing $1.4 billion

Verge Genomics, run by
29-year-old Alice Zhang, is trying to address these problems by
making drug discovery faster and cheaper.

On Monday, the San
Francisco-based company announced it had
raised 

$32 million in
series A funding, led by DFJ, bringing its total amount raised to
$36.5 million.

Zhang was three
months shy of her MD and PhD graduation from University of
California-Los Angeles when she left school to start Verge
Genomics in 2015 with Jason Chen, who she met during the
program.  

I just became very frustrated
with the drug discovery process,” she said. “It’s largely a
guessing game where companies are essentially brute force
screening millions of drugs just to stumble across a single new
drug that works.” 

At the time, Zhang also
recognized the advancements in neuroscience, machine learning and
genomics occurring all around her. Genome sequencing had become
more and more affordable, and breakthroughs in understanding how
function connects with genes opened a new field of possibilities
for exploring disease and health. And there was an opening for an
opportunity to guesswork out of drug discovery. The vision for
Verge was to become the first pharmaceutical company that
automated its drug discovery engine,
helping 

to rapidly
develop multiple lifesaving treatments in diseases like
Alzheimer’s disease, ALS, and Parkinson’s disease where no cure
exists today. 

Recently, other big pharmaceutical agencies like Pfizer and
Novartis are also starting to follow suit,
adapting technology
to different steps of the clinical trial
process. At least 18
pharmaceutical companies
 and more
than 
75
startups
 have been working on integrating machine
learning into the drug discovery process.

Verge, 14 people large, functions at full capacity. Not only do
they have computer scientists managing the front-end of machine
learning, but they also have researchers working in its own
in-house drug discovery and animal lab. The team is stacked
with computer scientists,
mathematicians, neurobiologists, as well as industry veterans and
drug development veterans. 

There are three main problems in
drug discovery that Verge is using data and software to tackle.
The first is that many diseases like Alzheimer’s disease are
caused by hundreds of genes. Verge’s algorithms on human genomic
data can map these genes out. The second is instead of using
animal data only for pre-clinical trials, Verge uses human data
from day one, which may enable greater insight into how effective
the drug actually is on human cells. Drugs that work in mice
often
fail in humans
, and that’s because mice usually serve as
primary mammal model. Instead of tediously screening millions of
drugs, the algorithm will computationally predict drugs that
work.

Verge uses brain samples from patients that have passed away from
Alzheimer’s disease or Parkinson’s disease for its human data,
obtained through partnerships with over a dozen different
universities, hospitals and brain banks. The company then
RNA-sequences them in-house, which allows them to measure the
gene expression in its most current state, and it can measure
simultaneously how all of the genes in the genome are behaving.
This data helps scientists figure out what’s actually causing
disease in these patients and see if there are connections
between genes and disease.

Verge’s scientists can make predictions about what drugs they
think will work. They can take a patient’s own skin cell and turn
it directly into their own brain cells in a dish. Then the
predictions can be tested on these brain cells to see if they can
rescue them from dysfunction or death – a basic test of drug
efficacy. That validation data can feed back into the
platform and continuously improve predictions over time, even
across different diseases.

The Verge algorithm identifies drugable targets for treatments,
then design drugs accordingly. This is done by mining through
human samples to identify groups of genes that are implicated
with the disease, and what crucial hub in these gene networks can
turn them on or off. 

The latest investment in Verge
will serve to advance its ALS and Parkinson’s disease drugs.
There are six drugs in development, closer to the clinical end,
which are being tested to make sure they’re safe and non-toxic.
The funding will also be used to expand the number of diseases
Verge has in its portfolio. 

Emily Melton, a partner at DFJ, told Business Insider that
investment in early stage startups is largely about the team, the
uniqueness of the idea and the capability and expertise of the
research team. But what drew her in most was Zhang. “She was this
brilliant founder, with a very organic desire to create an
impact,” said Melton. “She felt like it was her calling.”

Using system learning to recognize patterns that would otherwise
go undetected by the human eye can speed up the process while
creating a bigger and better feedback loop, said Melton. “We’re
rethinking how drug discovery is done, and we’re rethinking how
therapeutics are developed.”


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