Systematic and serendipitous searching


Oct 1, 2013 (4 years and 9 months ago)



April 2011

Bio Business


Teaching an Old Drug New Tricks

Biotech companies hope to turn the practice of finding novel
uses for existing compounds into big business.

By Megan Scudellari | April 1, 2011

and Aris Persidis love to tackle big problems. As graduate students in the 1980s, the two

a naval architect and a biochemist, respectively

would spend long nights knocking
around ideas for how to engineer a better propeller or a sleeker keel, tang
ible challenges
involving multiple factors and many data points.

A decade later, the brothers turned their sights toward the big problems of a new discipline, one
where data were beginning to pile up. “We thought, ‘Why don’t we use engineering theories and

techniques to attempt to address some of the unbelievably complicated questions in
biomedicine?’” recalls Aris Persidis. “Someone had to do something like this, so we decided to
give it a go.”

Andreas Persidis cofounded Biovista in 1996, a biotech which
already has two repurposed drug candidates for treating
progressive multiple sclerosis. Courtesy of Dr. Andreas

In 1996 the Persidis brothers cofounded Biovista, a biotech
based in Charlottesville, Virginia. Over the next eleven years,
using their

engineering know
how, the duo developed a novel
technology to answer a simple question: If we know how a

drug works, can we look at data from laboratory studies and clinical trials to predict other
diseases for which that drug might be therapeutic? “Drugs

surprise us with new activities all the
time,” says Persidis. “A drug that is well seasoned is an excellent starting point for innovation.”

Drug repositioning or repurposing

an effort to find new uses for existing drugs

is not a new
idea. Viagra, for exam
ple, was first tested as a hypertension treatment before it became a
blockbuster drug for erectile dysfunction. Arsenic, once used to treat syphilis, is now regularly
used to combat leukemia. And thalidomide, a reviled antinausea medication for pregnant wo
that was pulled from international markets in the 1960s after it was found to cause terrible birth
defects, got a second wind in 2006 with US Food and Drug Administration approval for its use in
marrow cancer.

“Nature is very parsimonious,” says J
.K. Aronson, president emeritus of the British
Pharmacological Society, a professional association for UK pharmacologists. “If you’ve got a
system used in one place that can be used somewhere else, it is used somewhere else.”

By simply identifying a differ
ent disease that can be treated with an existing drug, companies can
skip preclinical and early clinical trials, and thus leapfrog much of the estimated 10

15 years,
and the more than $1 billion it takes to bring a new drug to market. Companies developing
drug candidates can also recoup major losses if a drug fails in Phase II or III trials by finding a
new indication in which to move it forward. But in the past, drug repositioning has been an
unpredictable process

an occasional happy accident when a do
ctor noticed a strange side effect
or a researcher documented an off
label use for a drug.

A drug that is well seasoned is an excellent starting point for innovation.

Aris Persidis, Biovista

Biovista already has two candidates for treating progressive
multiple sclerosis, both of which
proved successful in animal models of the disease, and the company has established partnerships
with Pfizer and the FDA. It is one of a handful of data
savvy young biotechs working to
transform drug repositioning from an o
ccasional coincidence to a systematic pursuit of new

“The value of drug repurposing is underappreciated,” says Pankaj Agarwal, director of
computational biology and bioinformatics at GlaxoSmithKline. “If you can find a new use for
something that’s

been out there for 5, 20, or 50 years, that’s very powerful.”

Systematic and serendipitous searching

NuMedii, a California
based biotech started in 2008, is one of the youngest companies to join the
repositioning movement, but it has made some of the quic
kest strides toward proving the effort
worthwhile. The company’s technology, developed by Stanford bioinformatician and pediatric
endocrinologist Atul Butte, maps gene activity patterns from a database containing molecular
profiles of over 300 diseases. If

two diseases share a molecular profile

a similar set of activated

perhaps they could also share drugs. Drugs that work for heart attack patients, for

instance, should perhaps be tested for effectiveness in people with muscular dystrophy, says

as the two conditions share similar activated pathways.

Butte has been validating such predictions at Stanford, with unpublished but promising results in
animal models, testing two existing medications that may be repurposed to treat Crohn’s disease
and l
ung cancer, respectively. The patents for both drugs have long since expired, which turns
out to be a double
edged sword. While the drugs are both cheap and available to repurpose as
new treatments for two serious illnesses, it is challenging to find a pha
rmaceutical partner to fund
the Phase II trials required to get the drugs approved for these new uses, says Butte. Though the
FDA offers patent protection for repurposed drugs in their new indication, there’s no guarantee
that a doctor won’t prescribe a ge
neric version that came on the market after the original patent
expired, even though it’s technically not approved for the new use.

“If there’s no one clear partner who’s going to benefit, the funding for the trial is questionable,”
adds Butte. “It’s a cat
22.” Still, the experiments demonstrate the technology’s promise in
predicting which diseases an existing drug might treat

a critical proof of concept that the
technology could prove valuable when applied to patented drugs that aren’t selling well in th
current indication, says Gini Deshpande, cofounder of NuMedii. “Our goal is to help our
pharmaceutical partners realize the full potential of the drug that they’ve spent enormous
amounts of money developing,” she says.

Biovista is also eager to partner

with pharmaceutical companies to reposition marketed drugs, as
well as those languishing on dusty shelves after failing at some step during preclinical or clinical
development. The company’s technology collects publicly available data on diseases, drugs,
targets, and adverse events, then organizes the data into 20 comparable categories

such as gene
associations and comorbidities

and scans for similarities. It’s eHarmony for medicine, says
Persidis with a laugh: “compatibility in many dimensions. That’s why

we can navigate all 23,000
diseases and all 6,000 adverse events against all 20,000 human targets and 95,000 drugs and
pharmacologically active compounds with reasonable data in the public domain.”

The technology’s predictions are then tested in vitro and

in vivo, Persidis says

with an
impressive 70 percent success rate. The platform’s prognostic value has caught the attention of
Pfizer, who last November inked a deal with Biovista to identify novel indications for a number
of existing Pfizer medications.

based Melior Discovery relies
on “systematic serendipity” to identify
potential new uses for old drugs. COURTESY

While Biovista and NuMedii take a
heavy approach, leveraging
massive computing power to reposi
tion drugs,
Melior Discovery uses a more opportune
modus operandi. Since 2005, the small,
based biotech has relied on what CEO Andrew Reaume calls “systematic

serendipity” to identify potential new uses for old drugs, a.k.a. the stumble
hem technique.
Using a nonhypothesis
driven method, the company runs drugs through a series of 40 animal
models representing a wide gamut of illnesses, from Alzheimer’s disease to asthma to overactive
bladders, looking to see what works. “It’s a way to unc
over potential therapeutic effects that
otherwise would not have been predicted,” says Reaume.

As haphazard as the approach sounds, it has produced remarkable results: In 5 years, the
company has run over 250 compounds through the 40 animal models and foun
d potential
therapeutic uses about 30 percent of the time, says Reaume. Their lead candidate, MLR
1023, a
kinase activator discarded as a treatment for gastric ulcers after poor Phase II results, showed
activity in a mouse model of Type II diabetes and wil
l soon begin a Phase II trial for the disease.
“Nobody in the field of diabetes, as well studied as it is, was predicting that [this] kinase would
be an attractive target,” says Reaume. “Now we’ve shown it to be one.”

Never too early

Though these biotechs
are validating their platforms using existing drugs, their executives
believe the true hotbed for the technology might be even earlier in drug development. During
preclinical analysis, these approaches may be able to identify two to four indications for a
compound that companies can pursue in parallel to see which is the most successful. “That’s
where you’re going to start to see some gains in this approach,” says Deshpande. “You’ll see
minimization of failed clinical trials and better drugs coming out for
therapeutic indications.”

“It would make sense, if you’ve got a new drug, to try and see if that drug affects all the different
targets in your pharmacology lab,” adds Aronson. “You might find there’s a drug that you’d
synthesized for one purpose that has
an action in another system entirely.”

Big Pharma is also making a play at developing systematic repositioning programs. In 2007
Pfizer established an Indications Discovery Unit in St. Louis, a group dedicated to repositioning
the company’s failed compound
s and finding new indications for the promising ones.
GlaxoSmithKline has shown a similar interest, but is exploring bioinformatics methods to prove
that drug repositioning is a profitable effort before committing significant resources. “The
approaches are

largely unproven. We still have a long way to go to show how much value it can
generate,” says GSK’s Agarwal, who is leading the work. “But I think it’s promising.”

“There’s a good dose of healthy skepticism in the pharmaceutical industry about [bioinform
approaches,” adds Deshpande. “But if we see a couple of success stories come out of this
approach, we’ll see this field open up really, really widely.”