Life Science Trends 2014

Transcription

Life Science Trends 2014
Life Science
Trends 2014
Feature Article:
Big Data in the
Life Sciences
D. Alexander, C. Hamilton, A. McDowell, B. McMerty,
N. Burns, C. Hancock, J. McLaughlin
www.carlyleconlan.com
About Life Science Trends 2014
About this Report
Each year, Carlyle Conlan provides an overview of trends and innovations in the life science
industry, encompassing its drugs, biologics, devices and diagnostics sectors. This year is the
first year our European Partner, george james ltd, has been involved in its production. Their
participation in this and future reports will widen the breadth of the articles covered.
Utilizing a number of in-depth, premium research reports available in the industry, Life
Science Trends 2014 summarizes and presents a variety of the most up-to-date industry
news under several macro headers: Research and Innovation, Fundamental Trends,
Investing and Deal Making, Regulatory & Government, and Health Care. The result is a
meaningful, “quick-read” white paper into which topics our clients, partners and constituents
can dig deeper based on their individual interests.
Life Science Trends 2014 captures significant advances in the industry from the past year
and makes observations about developments of interest through the year ahead. Of central
importance is the understanding that trends do not necessarily change on a yearly basis. For
instance, the field of personalized medicine is expected to continue as a trend well into the
foreseeable future.
Our report may differ from others in that an early version is sent to CEOs, venture capitalists,
and other industry experts for review before its final release. This report was created using
both primary and secondary data. Secondary data is highlighted with associated links to
further information as available in the public domain or credited to the appropriate source.
We invite you to review the information contained in this report, which we trust you will find
interesting and relevant to the sector.
About Carlyle Conlan
Carlyle Conlan, headquartered in the Research Triangle Park, is an executive and professional
search firm focused on the life science and technology sectors. With a highly dedicated,
experienced, and professional team of specialists, we work with small, mid-sized and large
companies to secure their most important asset, human capital. Our placement focus is on
highly experienced individual contributors through C-level search in a variety of functional
position types throughout North America. More information about Carlyle Conlan can be
found at: www.carlyleconlan.com
About Life Science Trends 2014
About george james ltd
george james ltd was founded in 1999 to provide a range of both standardised and bespoke
recruitment and training service across Europe. As the network of contacts expanded new
services in corporate development were added in 2002.
Founded by two experienced and successful senior industry professionals with global
experience across a range of industries now served, they had been frustrated by the level of
service they experienced in both sales training and recruitment. As a result the principals’
initial focus was to develop and continually optimize services to address the issues they had
encountered. Both founders’ own career success had been based on the simple
understanding that nobody can advance his/her own career, and no company can maximize
its success without recruiting, developing and keeping the best talent. Helping their
customers achieve this is their core goal and specialization. Other successful, experienced
industry professionals who share this vision have joined to strengthen and expand the team.
More information about george james ltd can be found at: www.georgejamesltd.co.uk
Table of Contents
Research and Innovation
Finer Focus
In Vitro Diagnostics Growth to Spearhead Future of Medtech
Iknife: Sniffing Out Cancer
Wait, Did This 15-Year-Old from Maryland Just Change Cancer Treatment?
Regenerative Medicine, Global Aging Were Hot Topics at Life Science Conference in Stockholm
Top 10 Experimental Cancer Drugs – 2013
Microbiomes Make Big News
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Fundamental Trends
Open Innovation in Pharma: Defining the Dialogue
Gene Scans Solve Mystery Diseases in Kids, Adults
U.S. Outpaces Rest Of World By Large Margin In Research And Development Spending, And
Its Patent System Helps the U.S. Keep The Advantage
Pfizer Expands Clinical Trial Data Access Policy and Launches Data Access Portal
Club of 2018 Confirms Big Biotech’s Ascendancy
Advanced Genetic Testing Paves Way for Personalized Medicine
Tufts Report Confirms Domination of Biotech Products
IBM and Cleveland Clinic Put Watson To Work
Global Drug Spending to Reach $1 Trillion In 2014
Matters of Evidence
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Investment and Deal Making
Royalty-Based Venture Financing, Born In Boston, Could Shake Up VCs And Startups From
New England To The Northwest
Funding Dries Up for Medical Startups
Biotechnology Boom is Here to Stay, Investors Say
F-Star Forges Immuno-Oncology Spin Off in Latest Test of Asset-Centric Model
Vantage Point – Under Pressure to Return Profits, Venture Funds Raise New Money
SEC Moves Ahead With 'Crowdfunding' Proposal
Banner Year for Life Sciences IPOs
NIH Cuts, Reimbursement Fears Cited as M&A Deals in Life Science Tools, MDx Industries
Drop 15 Percent in 2013
Strong Momentum in Healthcare: Trends in Mergers and Acquisitions
Biotech 2013 by the Numbers: A Blockbuster Year
Summary of the Campbell Alliance 2013 Dealmakers’ Intentions Survey
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Regulatory and Government
Novartis Loses Landmark Drug Patent Battle in India
NHS Medicine Spend to Remain Flat for Two Years
Senate Spending Panel Approves $31 Billion for NIH in 2014, Restoring Sequester Cuts
2014 May Bring Unwelcome Change for In-Vitro Diagnostics Companies
FDA in Personalized Medicine
FDA to Regulate Some Medical-Related Apps
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Table of Contents
Misconduct Delayed Drug Approval
FDA Releases Guidance on Research Use, Investigational Use Only Ivds
Revision of the EU Medical Devices Directives
US New Drug Approvals Slip In 2013 Vs. Prior Years
Vantage Point – One year on, breakthrough designation remains an enigmatic accolade
GAIN Act: A Great First Step
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Health Care
Obamacare: Winners and Losers For Investors
5 Hot Startup Opportunities Created By Health Care Reform
Obamacare - A Game-Changer in the Making
4 Ways New Exchanges Will Radically Alter Health Insurance
As More Americans Have Surgeries Overseas, US Companies Consider 'Medical Tourism' a
Health Care Option
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Featured Articles – Big Data In The Life Sciences
Clinton Health Access Initiative – Paul Domanico
Eagle Genomics – Richard Holland
Code-N – Marketta Silvera and Randy Haldeman
Numedii – Gini Deshpande
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Research and Innovation
Finer Focus
PARP inhibitors were all but written off a few
years ago, but now are back with a focus on
BRCA1 and BRCA2 mutation-related cancers,
the Wall Street Journal reports.
Pharmaceutical companies such as
AstraZeneca, BioMarin, Clovis Oncology, and
Tesaro are beginning to see data indicating that
their drugs may help shrink tumors. For
example, in one study of ovarian cancer,
adding AstraZeneca's olaparib to chemotherapy
regimens appeared to allow patients with BRCA
mutations to live a median 11.2 months
without their cancers getting worse — 6.9
months longer than those who received a
placebo, according to the Journal.
Citigroup estimates that the per-month cost of
such drugs would be between $12,500 and
$15,000. "If we can specifically target the
patient, there's going to be a better benefit and
people are willing to pay more," Mary Lynne
Hedley, the president and CSO of Tesaro, tells
the Journal.
GenomeWeb
In Vitro Diagnostics Growth to
Spearhead Future of Medtech
In vitro diagnostics (IVDs) is not only the
largest segment within medtech, with forecast
worldwide sales of $58.8bn in 2018, it is also
one of the fastest growing, EvaluateMedTech’s
World Preview 2013 shows. The analysis of the
top 20 sectors of the worldwide medical device
market reveals that the IVD sector is
expanding at a CAGR of 5.1%, outpacing the
overall medtech market growth rate of 4.5%.
This expansion, fuelled by the increasing
demand for companion diagnostics and
interlinked innovations in molecular testing, is a
contrast to much of the rest of the medical
technology world. The diagnostic imaging and
orthopaedics sectors, for example, have belowaverage growth, with higher regulatory bars
and decreased investment working against the
development of fewer transformative new
technologies.
Regulatory changes are afoot on both sides of
the Atlantic, with the FDA finally issuing its
long-awaited rule on device identification
numbers. The Unique Device Identifier (UDI)
will have to be printed on each product’s label,
along with a scannable barcode to allow
physicians and regulators and even the public
to track the devices and monitor safety, as the
resulting data will be stored in a publicly
accessible database.
EvaluateGroup
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Research and Innovation
iKnife: Sniffing Out Cancer
Electrocautery surgical knives are widely used
in operating rooms to seal incisions with heat
and thereby reduce bleeding. Now a new,
“intelligent” version has been developed that
can analyze the smoke generated during the
cutting/cauterizing process to determine
whether the tissue being cut is healthy or
cancerous.
The smoke is sampled and analyzed by a mass
spectrometer which identifies particles based
on their mass and charge. One type of charged
particle commonly found in surgical smoke is
fat, and different tissues and cancers have
characteristic proportions of different types of
fat. So, by comparing samples to a database of
nearly 3,000 known standards, cancers and
other tissues can be identified with about 95
percent accuracy. Results are delivered in 2.5
seconds or less.
Burrus
Wait, Did This 15-Year-Old from
Maryland Just Change Cancer
Treatment?
If you’re feeling anxious about how U.S. kids
lag the world in science and math, or just in a
funk about politics or the mess in Europe, take
in this story of a high school freshman from
Crownsville, Md. who came up with a prizewinning breakthrough that could change how
cancer and other fatal diseases are diagnosed
and treated.
His name is Jack Andraka, and he loves science
and engineering with every inch of his 15-yearold soul.
Andraka’s diagnostic breakthrough is a humble
piece of filter paper, except that it is dipped in
a solution of carbon nanotubes, which are
hollow cylinders with walls the thickness of a
single atom, coated with a specific antibody
designed to bind with the virus or protein
you’re looking for. Andraka’s key insight is that
there are noticeable changes in the electrical
conductivity of the nanotubes when the
distances between them changes. When the
antibodies on the surface of the nanotubes
come in contact with a target protein, the
proteins bind to the tubes and spread them
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Research and Innovation
apart a tiny bit. That shift in the spaces
between tubes can be detected by an electrical
meter. Andraka used a $50 meter from the
Home Depot to do the trick but, he says,
doctors can just as easily insert his test-strips
into the kinds of devices used by millions of
diabetics around the world.
Forbes
during the recent 9th annual Swedish-American
Life Science Summit Conference, where a broad
range of regenerative medical issues and
solutions took center seat.
These included the continuing work in
developing a novel hormone replacement
therapy for Alzheimer’s disease as a
preventative for those who are at risk,
treatment of tissue damage with Omega-3based regenerative technologies such as tissue
regeneration material derived from fish skin to
accelerate healing of wounds and tissue
reconstruction, and advanced treatment of
various medical diseases and disorders through
stem cell therapies that would enable people to
take control of their own health at the most
basic level – their own cell.
Forbes
Top 10 Experimental Cancer
Drugs – 2013
Regenerative Medicine, Global
Aging Were Hot Topics at Life
Science Conference in Stockholm
Is “regenerative medicine” here and now, or is
it still a vision of hope that requires more
research, if not further extended clinical studies
to achieve its global promise? And how much of
an impact does global aging have on the
bottom line of companies and governments
worldwide?
Scientists and medical experts from various
countries debated these issues in Stockholm
With the help of open-minded regulators,
pharma companies have ditched the traditional
march through three phases of clinical trials for
some cancer drugs. Trials of targeted drugs
offer rapid proof of efficacy against molecularly
defined malignancies, giving the authorities a
basis for approvals before late-stage studies to
prove that therapies prolong the lives of
patients.
In Fierce Biotech’s third annual report on 10
exciting cancer drugs, there are plenty of R&D
programs zipping through trials with the
blessing of the FDA, which has awarded
"breakthrough" status for expedited
development to treatments in oncology more
than any other field. Take Novartis' LDK378,
one of the featured treatments in this report. In
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Research and Innovation
March the next-gen ALK inhibitor joined the
"breakthrough" club amid Phase II trials, and
Novartis ($NVS) said it would seek FDA
approval next year with only three years of
development.
FierceBiotech
Microbiomes Make Big News
The spacecraft Voyager I sailed out beyond the
heliosphere and into interstellar space.
Scientists inched closer to developing human
body part replacements. The bones of Richard
III were identified and yanked from their home
under a parking lot and the cause of his death
was revealed (crushed skull).
These were among the big science stories that
broke this year, but the biggest, according to
Science News, was the advance of the idea that
organisms and the microbes that colonize them
are really superorganisms.
Revelations from the Human Microbiome
Project and other microbiome research soon
may "alter conceptions of what and who we
are," Tina Hesman Saey writes.
Because only around 10 percent of a human's
cells are actually human, with microbes making
up the remaining 90 percent, it is useful to
consider humans as a superorganism made up
of ourselves, as hosts, and our microbe guests.
For example, using the superorganism
approach could help scientists better
understand how diet, chemicals, and
environmental factors impact health.
Genome Web
Image Source: ondineblog.com
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Fundamental Trends
Open Innovation in Pharma:
Defining the Dialogue
There are a number of highly innovative US
companies, many of them in the information
technology (IT), electronics, and software
industries. What is interesting is that these
companies were at one time fully-integrated
entities—companies that made mainframe
computers, wrote the software, and sold you
the paper on which to print. Essentially, they
did everything from soup to nuts. That model in
the IT and electronics area has changed
dramatically over the last 30 years. Many of
the biggest names in those fields claim that
their adoption of an open innovation model led
to this result and saved their businesses. So,
what is open innovation?
thus must collaborate with others?" Or did
companies deliberately embrace it as a
behavior they should adopt, a culture they
should push forward? Or was it vice versa—did
the external environment intervene to force
their hand? The answer appears to be that
because the high tech environment changed
over the past 30 years, companies had no
choice but to adapt.
PharmExec
Open innovation can be categorized three
ways:
Type I is pure outsourcing, often touted as
open innovation, or R&D activity pursued by
external entities, such as contract research
organizations (CROs) and universities. Type II
consists of licensing and its variations—
collaborations, joint ventures, even in some
cases technology transfer, and perhaps what is
called "crowd sourcing;" where a number of
innovators come together to address a problem
and solve it. Type III is R&D in the space
beyond IP—an interesting concept, but which
doesn't really help us much with what this
means as applied to pharmaceutical innovation.
Rather than digging further into the jargon, we
need to ask what caused certain companies to
adopt what is called an open innovation model.
Did it just dawn on those companies to decide
"Oh, we need to create common platforms and
technologies to arrive at new products, and
Gene Scans Solve Mystery
Diseases in Kids, Adults
They were mystery diseases that had stumped
doctors for years — adults with strange
symptoms and children with neurological
problems, mental slowness or muscles too
weak to let them stand. Now scientists say they
were able to crack a quarter of these cases by
decoding the patients' genes.
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Fundamental Trends
Their study is the first large-scale effort to
move gene sequencing out of the lab and into
ordinary medical care, and it shows that high
hopes for this technology are finally paying off.
"This is a direct benefit of the Human Genome
Project," the big effort to decode our DNA, said
Dr. Christine M. Eng of Baylor College of
Medicine in Houston. "We're now able to
directly benefit patients through more accurate
diagnosis."
Yahoo
factor of 4-10 to one. (“How China Chases
Innovation”, U.S. News – The Outlook, by Bob
Davis, WSJ) About 2/3 of all R&D spending in
the US is privately funded. China was the
closest in R&D spending, at about 1/2 the level
of the US. Only Japan, Germany and South
Korea spent more as a percentage of GDP.
Interestingly, all the top R&D spending
countries, as a percentage of GDP, had strong
patent systems. The lowest spending countries,
Brazil and India, have notoriously weak patent
systems. Interestingly, despite its large R&D
spend, China lags the world in “new ideas”, still
focusing on imitating Western technologies and
producing them more cheaply.
With the US leading in R&D spend, and China
and other developing nations leading in low
cost production, common sense tells us the
patent system plays a vital role in protecting
the US’s R&D spend against free-riding, low
wage, imitator nations.
National Law Review
Pfizer Expands Clinical Trial Data
Access Policy and Launches Data
Access Portal
U.S. Outpaces Rest of World by
Large Margin in Research and
Development Spending, and Its
Patent System Helps the U.S.
Keep the Advantage
On September 30, the Wall Street Journal
reported that the US leads the world in R&D
spending – at $450 billion – by a wide margin,
outpacing Japan by a 3 to 1 margin, and most
of the rest of the industrialized world by a
Pfizer Inc. (NYSE: PFE) announced an update of
its clinical trial data access policy that will
simplify and broaden access to information
gathered in Pfizer-sponsored clinical trials. The
updated policy builds upon and expands the
company's established methods of clinical trial
information sharing, including Pfizer's long
track record of submitting for publication
results from all interventional clinical trials in
patients and its pioneering efforts to provide
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Fundamental Trends
clinical trial results and data to study
participants.
Pfizer's updated policy meets or exceeds
the "Principles for Responsible Data
Sharing" issued by the Pharmaceutical
Research and Manufacturers of America
(PhRMA) and the European Federation of
Pharmaceutical Industries and Associations
(EFPIA) in July 2013.
FierceBiotech
Club of 2018 Confirms Big
Biotech’s Ascendancy
The ascendancy of the big biotech sector is
beyond doubt. Nothing shows this better than
an analysis of these companies’ growing
representation in the exclusive club of the 50
biggest-selling drugs between now and 2018.
True, some big pharmas are maintaining the
senior sector’s blockbuster reputation, though
not without help from their junior friends. And,
as EvaluatePharma data reveal, there now
seems to be no stopping biotech’s biggest
representatives such as Gilead Sciences, which
in five years could boast no fewer than three
top-50 drugs and six in the top 100.
A couple of the sector’s senior companies –
Roche and Novartis – do remain pivotal. But
beyond, big pharma’s dominance diminishes
sharply, with Lilly and AstraZeneca especially
hard hit and set to have just one top-50 drug
each in 2018, against four and three
respectively last year, as patent expiries on
Crestor, Nexium, Cymbalta and Cialis take their
toll.
Roche’s upper hand in any case comes thanks
to drugs such as Avastin, Rituxan, Herceptin,
Kadcyla and Perjeta, and thus largely owes its
success to Genentech. And of course AbbVie’s
sole representative is Humira, the global best
seller of both last year and 2018, which as a
monoclonal antibody is certainly no typical big
pharma drug.
EvaluateGroup
Advanced Genetic Testing Paves
Way for Personalized Medicine
Washington - New genetic testing methods
may not only help identify the potential risk for
individuals to develop certain diseases but may
also open the door for more targeted therapies
and management strategies, which could be of
particular benefit in higher risk patient
populations.
“Recent advances made in genetic mapping
techniques such as the development of whole
exome and genome sequencing are allowing us
to better and more quickly identify hereditary
diseases ranging from genodermatoses such as
hidradentitis suppurativa and familial
disseminated superficial actinic porokeratosis
(DSAP) to a variety of cancers and other
inheritable diseases,” Jorge R. Toro, M.D., said
at the 90th Atlantic Dermatological Conference
in Washington. He is chief of the department of
dermatology, Washington DC VA Medical
Center. “These breakthrough technologies can
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Fundamental Trends
help forge a more personalized medicine
approach for our patients.”
Dermatology Times
Tufts Report Confirms
Domination of Biotech Products
A new analysis from the Tufts Center for the
Study of Drug Development has highlighted the
way the pharmaceutical industry "has
dramatically shifted its R&D focus from its
historical concentration on small molecule
drugs to today's dominant focus on
biotechnology products".
The study notes that biotech products, which
accounted for only 7% of revenue generated by
the 10 top-selling treatments worldwide in
2001, made up 71% of the top 10 last year.
The number of biologics in clinical trials grew
155% in 11 years, from 355 in 2001 to 907 in
2012, with big pharma involved in about 40%
of all biotech products in development last
year.
PharmaTimes
IBM and Cleveland Clinic Put
Watson to Work
IBM Research used the Cleveland Clinic’s
Medical Innovation Summit to debut two new
projects using its Watson computer system to
help doctors and medical students make more
informed and accurate healthcare decisions.
“WatsonPaths” and “Watson EMR Assistant,”
both early-stage projects with a focus on
decision-support, may help healthcare
providers deal with growing pressures to
practice evidence-based medicine as the
amount of available evidence balloons.
“The vision is for WatsonPaths to act as a
useful guide for students to arrive at the most
likely and least likely answers to real clinical
problems, but in a classroom setting,” says J.
Eric Jelovsek, director of the Cleveland Clinic
Multidisciplinary Simulation Center.
Watson EMR Assistant aims to help doctors
uncover key information from patients’
electronic medical records to improve the
quality and efficiency of care they provide.
Burrill Report
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Fundamental Trends
Global Drug Spending to Reach
$1 Trillion in 2014
Global spending on medicines is expected to hit
the $1 trillion threshold in 2014 and reach $1.2
trillion by 2017, driven by greater access to
medicines by the world’s rapidly expanding
middle class, together with stronger economic
prospects in developed nations.
After several years of spending growth below 3
percent per year, global drug expenditures are
forecast to increase at a 3 to 6 percent
compound annual rate over the next five years,
according to new research released by the IMS
Institute for Healthcare Informatics.
The report, The Global Use of Medicines:
Outlook through 2017, found that growth in
global spending on medicines increased 2.6
percent to $965 billion in 2012 and is forecast
to gradually reach 5 to 7 percent in 2017, the
highest pace of growth since 2009. With the
rising number of innovative new drugs
expected to be approved over the next five
years, particularly for the treatment of cancer,
spending on specialty medicines is expected to
reach $230-240 billion in 2017, up 38 percent
from the $171 billion spent in 2012. Typically
biologics that are used for conditions requiring
complex treatment, specialty medicines will be
the single largest contributor to branded drug
spending growth through 2017.
Burill Report
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Fundamental Trends
Matters of Evidence
Ernst and Young’s Beyond Borders 2013 report focuses on “Matters of Evidence”. As the 2012 report
coined the term “HOLNet’s” (Holistic Open Learning Networks) to describe collective efficiencies in the
market, the 2013 edition describes the move toward outcomes-focused, evidence driven health care
systems. Through a survey of 62 companies in the biotech sector E&Y found that, while companies
overwhelmingly felt prioritized products should exceed the current standard of care and demonstrate
value to payers, relatively few had taken steps to add payer / reimbursement expertise to their
companies. Many companies, though, have considered discontinuing products that might not exceed
the current standard of care.
Through panel interviews with VC’s and Big Pharma corporate executives, the report offers additional
insight. Tao Fu, Head of M&A at Johnson and Johnson states, “we do extensive payer research for
every significant business development project we manage, particularly those that are later-stage.
We certainly don’t expect smaller biotech companies, with their relatively limited resources, to
conduct large payer studies. But we do expect them to thoroughly think through the incremental
value their products will bring to medical practice and design their clinical development plans and
target product profiles accordingly.”
Brian Edelman, VP of Corporate Finance and Investment Banking at Eli Lilly, adds “Why are biotech
companies so frequently unprepared to demonstrate the differentiated value of their products? I
believe that underlying this development is a paradigm shift. Our society has decided that it’s only
willing to pay for innovation up to a point. Effectively, this translates into a situation in which only
one or two agents will be reimbursed in any area of care. We might lose something in the process.
Lipitor, which was a late stage statin to get approved, went on to become the best-selling drug of all
time, in large part because it was legitimately seen as a better treatment. In today’s industry, a
product like that might never get payer coverage in the first place.” –
E & Y Beyond Borders Report 2013
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Investment and Deal Making
Royalty-Based Venture
Financing, Born in Boston, Could
Shake Up VCs and Startups from
New England to the Northwest
Every once in a while, an investment model
comes along that turns the innovation
community on its head. The venture capital
industry, still less than 50 years old, is one
example. Now an emerging paradigm called
royalty-based financing, applied to early-stage
startups, may be another. The approach has its
roots in the Boston area, and is starting to
generate some serious buzz in the Northwest.
If you’re a VC, angel investor, or entrepreneur,
it definitely needs to be on your radar.
The concept of royalty-based financing is
simple. Instead of buying equity in a young
company, an investor agrees to receive a
percentage of the company’s monthly
revenues—up to a limit of, say, three to five
times his or her investment. Instead of waiting
five or 10 years for a startup to go public or get
acquired, an investor can start seeing returns
almost immediately. This approach means
investors should be able to fund a much wider
range of startups than just those that typically
receive venture backing—the ones that have
potential to grow huge, fast.
Xconomy
Funding Dries Up for Medical
Startups
The medical-device industry, struggling to
adapt to a thriftier health-care system, is
getting squeezed by a venture-capital drought.
Investment in the medical-device and
equipment industry is on pace to fall to $2.14
billion this year, down more than 40% from
2007 and the sharpest drop among the top five
industry recipients of venture funding,
according to an analysis of data compiled by
PricewaterhouseCoopers and the National
Venture Capital Association. Venture money
received by the biotechnology sector declined
28% over the same period, while software
startups recorded a 75% increase.
As a result, the industry responsible for making
prosthetic hips and other devices is having to
get creative. Entrepreneurs are taking on more
debt and looking for cash in unusual places,
including family investment funds overseas and
high net worth individuals in the U.S., people in
the industry say.
Wall Street Journal
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Investment and Deal Making
Biotechnology Boom is Here to
Stay, Investors Say
There have been more than 30 initial public
offerings of biotechnology companies as of this
article’s date, and there’s a line around the
block of promising new entrants looking to
debut on the public markets.
But don’t call it a bubble. Those in the know are
calling it a boom, and saying the good times
are likely to continue for biotech, even in the
face of clinical setbacks and other bumps in the
road.
These were the impressions of investors in both
publicly traded and privately held biotechnology
companies who served as panelists at the Bio
Investor Forum in San Francisco. The
conference is organized by the Biotechnology
Industry Organization.
Wall Street Journal
F-Star Forges Immuno-Oncology
Spin Off in Latest Test of AssetCentric Model
Bi-specific antibody specialist F-star threw its
hat into the asset-centric ring with the creation
of a new company called F-star Alpha, which
has a license to a broad range of its oncology
assets and €9.4m ($13m) in new venture
funds.
The hope is that this structure will enable the
company and its investors to capitalise more
easily on leads that have emerged from F-star’s
platform. Given that Alpha’s focus is trained on
arguably the hottest area of research right now
– immuno-oncology – it would seem to have a
good chance of attracting interested parties,
and providing proponents of the asset-centric
model a well needed success story.
The so-called asset centric model – creating a
company around one or more assets with the
primary end motive of finding them a new
owner – is being tested in various
manifestations as venture capital-backed drug
developers and their investors search for new
business models that will help keep the cash
flowing in both directions (Index Ventures adds
big pharma to asset centric model, March 21,
2012).
For platform companies, providing investors
with an opportunity to sell out or at least
receive a return is particularly tricky, outside a
complete takeover. Others have already turned
to the asset-centric approach for a solution, for
example in the US by Nimbus Discovery and
Forma Therapeutics (EP Vantage Interview –
Forma’s fix for VC model driving deals, January
27, 2012).
Evaluate Group
Vantage Point – Under Pressure
to Return Profits, Venture Funds
Raise New Money
Private drug developers awaiting a thaw in the
last few years' frigid financing conditions will
take heart at the recent flurry of new funds
raised by life science-focused venture capital
firms. The past few months have seen the huge
US healthcare investor Orbimed raise $735m
and early-stage California investor 5AM
Ventures raise $250m, while in Europe Edmond
de Rothschild Investment Partners and Gilde
have both managed to close funds.
12
Investment and Deal Making
At firms flush with new cash the mood is
inescapably upbeat. “You are about to see a
huge resurgence in venture capital in
healthcare,” says Jonathan Silverstein of
Orbimed. “This year a few funds managed to
raise capital– next year there will be a bunch
more.” However as investors return to these
high risk propositions, venture firms will remain
under tremendous pressure to prove that they
can turn the biotech bull run into returnable
profits.
Much of the optimism emanating from the
venture capital community is being forged by
the buoyant US IPO market and a belief that
the FDA is becoming more co-operative,
particularly over the most innovative products.
Banner Year for Life Sciences
IPOs
The boom in life sciences IPOs on U.S.
exchanges, and biotech IPOs in particular, was
the biggest story of 2013 for the sector. During
the best year for initial public offerings across
all sectors since 2000 in the United States, 52
life sciences companies completed initial public
offerings to raise a total of $7 billion. that
compares to 16 companies that went public in
2012 and raised $1.1 billion.
Evaluate Group
SEC Moves Ahead With
Crowdfunding' Proposal
Startups and entrepreneurs could soon reach
larger numbers of potential investors through
investment websites under "crowdfunding"
rules proposed by federal regulators.
The Securities and Exchange Commission, in a
5-0 vote, outlined a plan aimed at helping
startup companies sell shares online, allowing
them to pool together small amounts of capital
from ordinary investors.
Supporters say the long-delayed plan could
spur significant growth in the young
crowdfunding marketplace.
Wall Street Journal
The surge of IPOs reflected robustness in the
public markets, the strong performance of
established biotech companies, and pent-up
demand for good biotech stories. The approval
in 2012 of 39 new molecular entities by the
U.S. Food and Drug Administration—many of
them innovative biologics, cancer, and rare
13
Investment and Deal Making
disease drugs— and the agency’s willingness to
enable the advancement of promising therapies
for unmet needs, bolstered investor enthusiasm
for the sector.
The post-IPO return for the 52 life sciences
companies that went public in 2013 is 47.6
percent on average as of December 27, 2013.
A total of 41 companies, or 78.8 percent,
ended the year above their IPO price, and
seven of them more than doubled their initial
offering price. The 16 companies that went
public in 2012 were up 61.8 percent on
average at the end of 2013, a sign that bodes
well for the continued strong performance of
the current year’s newly public companies.
Burrill Report
NIH Cuts, Reimbursement Fears
Cited as M&A Deals in Life
Science Tools, MDx Industries
Drop 15 Percent in 2013
Though Thermo Fisher Scientific's pending
$13.6 billion purchase of Life Technologies sent
shockwaves through the industry and led some
to speculate about further deals, mergers and
acquisitions in the life science tools and
molecular diagnostics space were down year
over year in 2013.
The number of M&A deals completed in 2013 or
announced during the year totaled 47, down 15
percent from 55 transactions in 2012, and
down from 58 in 2011. Activity was down in
both the first and second halves of 2013 year
over year as 23 deals were done in H2 2013,
compared to 28 in the comparable year-ago
period. In the first half of 2013, 24 deals were
completed, down from 27 a year ago.
GenomeWeb
Strong Momentum in Healthcare:
Trends in Mergers and
Acquisitions
The impending decrease in venture investment
in healthcare companies is based on the time
lag between funds raised and capital available
to deploy. Equity investment from venture
funds are deployed from two different sources:
1) dollars invested by “newer funds” — 2010
vintage and later — into new company
investments, and 2) the mostly follow-on
activity supporting existing companies with
additional equity from the substantial amounts
of capital raised in the vintage 2006–2008
“older funds.” The lion’s share of the current
capital invested in the last few years has come
from these older funds, which will no longer be
available as these fund reserves are used up.
Since 2010, the number of new funds and
dollars raised has declined significantly. Thus,
we believe that dollars invested into healthcare
venture-backed companies will come down to
the $5–$5.5 billion level in the next few years,
leading to a smaller percentage of overall
venture investment into healthcare — likely
18–20 percent of total venture investment — if
overall investment remains consistent.
14
Investment and Deal Making
The $5–$5.5 billion number is still higher than
new healthcare fundraising dollars on a yearly
basis, although the fundraising data presented
does not accurately take into account one
important part of the healthcare venture
ecosystem: corporate venture funds. Corporate
venture has emerged as an important source of
capital for healthcare companies, although
corporate venture fundraising (or dollars
available for investment) is not adequately
tracked. According to our estimates, healthcare
corporate venture represents 15–20 percent of
all capital invested into healthcare venturebacked companies. Even though corporate
venture has become more active in venture
investment and has helped to fill some of that
innovation gap created by reduced healthcare
venture fundraising (especially in Series A
biotech), paired with a reduced amount of
capital from traditional venture it is not enough
to sustain the current capital investing pace. As
a result, we will see decreased dollar
deployment into healthcare companies from its
current level. Doug Fisher, Partner with
InterWest Partners, agrees: “We are already
starting to see this trend among our portfolio
companies who are raising money. The bar is
higher and there are fewer funds able to
invest.”
And yes, investors did very well in biotech in
2013. This chart says it all:
In a year where the markets outperformed, the
biotech sector performed even better, posting
returns not seen since 1999. Phenomenal. No
wonder we saw a huge influx of generalist
investors into healthcare stocks in 2013.
The Street
Silicon Valley Bank Healthcare M&A Report
Biotech 2013 by the Numbers: A
Blockbuster Year
Hello, 2014! Before we crack open the new
year, let's close the books on what was a very
big 2013 in biotech investing.
15
Investment and Deal Making
Summary of the Campbell Alliance 2013 Dealmakers’ Intentions Survey
With 2012 being described as the “Year of the Earnout” the view of 2013 is that this trend is set to
continue with in-licensers forecasting increasing acquisitions with earnouts as acquirers look to reduce
initial exposure and target companies continue to face challenges in raising finance.
Overall the view of 2013 was a positive one with several interesting trends developing. Compared to
previous years there is a shift towards increasing interest early stage assets with in-licensers less
positive than out-licensers on the prospects for phase 3 deals, reversing previous trends for later
stage deals being in the ascendance. Oncology remains the therapeutic area of great interest to inlicensers, particularly these early stage assets. Not surprisingly this move towards earlier stage assets
has resulted in increased deal discussions but a significant drop in yield of deals with up-front
payments, down to 1% from 7% in the previous year. The conclusion is that life for the deal makers
whilst not being more productive is certainly a lot busier as a larger number of higher risk deals are
assessed
Looking more closely into the numbers the most striking statistic as to why most deals failed is the
difference in valuation and trust between parties. Figure 6. The perceived deficiency of pricing and
16
Investment and Deal Making
market access information was seen by in-licensers as the biggest issue leading to negotiation
breakdown. Figure 7. If negotiations are initiated with shared commercial assumptions, deal-term
expectations and trust deal conversion rates potentially increase tenfold. The message to outlicensers is that pre negotiation investment in detailed pricing and market access information is the
biggest single factor within their control that significantly increases the potential for a successful
outcome.
When looking at the details of the negotiations, the valuation method most used by in-licensers is
risk-adjusted NPV (rNPV) followed by the use of comparable deals. There is also evidence to suggest
in-licensers have lower hurdle rates than out-licensers may realize; this assumption may be part of
the reason unrealistic commercial expectations are presented by an out-licenser, which for the
reasons above greatly increases the risk of a failed negotiation. One of the reasons for optimism on
an increasing deal rate was a widening discount rate spread which is aiding deal making with 2013
reporting a significant increase in spread; in-licensers’ discounted rates down 300 basis points and
17
Investment and Deal Making
out-licensers’ up 300 basis points. This results in becoming viable in situations in which the valuating
gap was previously too large to bridge.
Finally, looking at supply and demand there are indications it is a seller’s market for approved
oncology, antibiotics and vaccine assets with strong interest from in-licensers and a relatively
restricted supply. Areas of particular interest are Orphan products and antibody-drug conjugates,
which were viewed as the two “hot” areas, Figure 14
Campbell Alliance
18
Investment and Deal Making
NHS medicine spend to remain
flat for two years
Novartis Loses Landmark Drug
Patent Battle in India
India's Supreme Court rejected drug maker
Novartis AG's attempt to patent an updated
version of a cancer drug in a landmark decision
that health activists say ensures poor patients
around the world will get continued access to
cheap versions of lifesaving medicines.
Novartis had argued that it needed a patent to
protect its investment in the cancer drug
Glivec, while activists said the drug did not
merit intellectual property protection in India
because it was not a new medicine. In
response to the ruling, Novartis said it would
not invest in drug research in India.
The court's decision has global significance
since India's $26 billion generic drug industry,
which supplies much of the cheap medicine
used in the developing world, could be stunted
if Indian law allowed global drug companies to
extend the lifespan of patents by making minor
changes to medicines.
NBC News
After almost two years of negotiations, the UK
Government and pharma industry have agreed
a revision to the system for drug pricing of
branded medicines in England to commence
from January 1, 2014.
One of the main points of the note in the new
Pharmaceutical Price Regulation Scheme
(PPRS) is a price freeze on NHS medicine
expenditure in England over the next two years
in order for the service to help claw back part
of the £12bn annual drug budget amid wider
cost-cutting measures.
This comes despite previous growth forecasts
in NHS medicine spend of 3.87 per cent and
3.52 per cent for 2014 and 2015 respectively,
meaning that pharma companies effectively
have to face a price cut on branded medicines
to stick to the revised budget.
Prices will then be allowed to increase over the
next three years, although at a rate less than
previously forecast.
The agreement, which was negotiated between
the Department of Health (DH) and the
Association of the British Pharmaceutical
Industry (ABPI), also clarified that pricing
assessment for new drugs could take into
account the wider value of a medicine.
NHS
19
Regulatory and Government
Senate Spending Panel Approves
$31 Billion for NIH in 2014,
Restoring Sequester Cuts
The mandatory across-the-board federal cuts
known as sequestration slashed $1.55 billion
from NIH's budget this year and will result in
belt-tightening at labs with ongoing grants as
well as hundreds fewer new grants than in
2012. The measure approved by the Senate
appropriations Subcommittee on Labor, Health
and Human Services, Education, and Related
Agencies includes $30.955 billion for NIH. That
figure would provide a 1% boost of $307
million over NIH's 2013 budget (before
sequestration), which was essentially the same
as in 2012.
NIH has strong support from Senate
Appropriations Committee Chair Barbara
Mikulski (D-MD), who held a press conference
yesterday to discuss NIH at Johns Hopkins
University in Baltimore. Mikulski said that she is
determined to reverse "reckless cuts to
American biomedical research." NIH Director
Francis Collins was on hand as well and
warned: "We're putting an entire generation of
U.S. scientists at risk and our own nation at
risk as well" with the sequester cuts. Hopkins
officials said that the sequester has cost the
university $38 million in NIH funding this year
and will force the layoff of dozens of staff
members.
Science Mag
An online summary states that the bill includes
$40 million that the president requested for
NIH's proposed BRAIN brain-mapping initiative.
Although the increase falls short of the $31.3
billion requested by President Barack Obama,
Jennifer Zeitzer, legislative relations director for
the Federation of American Societies for
Experimental Biology (FASEB), said that her
group is "thrilled" with the figure. "It's far
better than the current situation and it's a
move in the right direction," she says. FASEB
has been pushing for $32 billion for NIH in
2014 to shore up the agency's budget after a
decade of flat funding and losses to inflation.
2014 May Bring Unwelcome
Change for In-Vitro Diagnostics
Companies
Earlier this year, the Centers for Medicare and
Medicaid, proposed a rule that does not spell
welcome news for in-vitro diagnostics
companies.
"If you come in for an outpatient procedure,
and they're doing any laboratory work, it's all
20
Regulatory and Government
going to be packaged into the primary
procedure. [If this goes into effect] that would
mean that it there would be no extra payment
for those lab tests. Obviously that's a pretty big
change," explained Barb Peterson, President
and CEO of Emerson Consultants, which
advises medtech companies on reimbursement
strategies among other things.
This proposed rule is part of CMS' annual
updates to its payment and fee schedules.
A difficult government reimbursement
environment is not the only challenge that invitro diagnostics companies are facing these
days. Faced with the prospect of having to
cover millions of previously uninsured people,
and not knowing what their healthcare
consumption is going to be like, private
insurers are increasingly becoming very
conservative.
"I know this is a general statement but they
are saying "no' to pretty much everything,"
Peterson said, referring to payors' covering new
products, be it new medical devices,
procedures and tests.
MDDI
FDA in Personalized Medicine
In a report published in October 2013, the US
Food and Drug Administration delineates its
role in — and the challenges it faces for —
implementing personalized medicine.
"We're very, very excited about this report
because I think it captures the broad context of
what's happening in science and medicine
today and the role of the FDA as we enter the
era of personalized medicine, and for us,
personalized medical product development,"
said Margaret Hamburg, the FDA
commissioner, at a press briefing according to
MedPage Today.
The report notes that FDA has altered some of
its regulatory processes to better fit with how
personalized medicines and their related
diagnostics need to be evaluated. For example,
it says that the agency has moved three
regulatory programs affecting in vitro
diagnostics — premarket review, compliance,
and post-market safety — into a single
location, which should "[ensure] that all
diagnostic device activity related to these
products would spring from a common
consolidated technical and regulatory base."
GenomeWeb
FDA to Regulate Some MedicalRelated Apps
Instead of having all health apps follow
stringent requirements, the U.S. Food and Drug
Administration announced that it will focus its
attention on mobile medical apps that might
harm patients if they do not work as intended.
The organization added that most health and
medical apps only pose a low risk of injury for
21
Regulatory and Government
consumers, and the majority will not be as
strictly regulated.
"Some mobile apps carry minimal risks to
consumer or patients, but others can carry
significant risks if they do not operate correctly.
The FDA's tailored policy protects patients
while encouraging innovation," said Dr. Jeffrey
Shuren, director of the FDA's Center for
Devices and Radiological Health, said in a press
release.
Medical mobile apps can aid doctors in
diagnosing patients without having them come
into the office. They can also help patients
manage their chronic conditions.
CBS
misconduct at sites in China where clinical trials
were performed, reported Bloomberg.
Documents published by the FDA reveal that
during trials overseen by Bristol-Myers Squibb
(BMS), which developed the drug in partnership
with Pfizer, some patients were given the
wrong drug, records were badly kept and
secretly manipulated to cover up good-practice
violations, and “serious adverse reactions”
went unreported.
The news raises questions about the reliability
of clinical trials carried out in China, which has
become a hotspot for such research because of
the huge pool of potential subjects and the low
costs, which can be as little as half of those in
the U.S., according to the Tufts Center for the
Study of Drug Development.
Thomas Marciniak, an FDA medical team leader
who wasn’t directly involved in the Eliquis
application process but reviewed the trial
independently, told Bloomberg that problems
with data collection and misconduct will
continue as long as drug manufacturers keep
doing trials in places like China without
providing better oversight. “What we need is
high-quality trials,” said Marciniak, who
emphasized he was not speaking on behalf of
the FDA. “If we’re not getting them in the lowcost areas, either fix the low-cost areas, or stop
doing them [there].”
The Scientist
Misconduct Delayed Drug
Approval
FDA Releases Guidance on
Research Use, Investigational
Use Only IVDs
US Food and Drug Administration (FDA)
approval for the blood-thinning drug Eliquis
was delayed for 9 months due to errors and
The Food and Drug Administration has released
a guidance document that lays out and clarifies
22
Regulatory and Government
the rules for how in vitro diagnostic products
for research use only (RUO) and investigational
use only (IUO) may be used, labeled, or
marketed.
FDA created the guidance on RUOs and IUOs,
which has been in development for several
years, because it is concerned that unapproved
or uncleared IVDs are being used for clinical
diagnostic use, even though their performance
characteristics and manufacturing controls have
not met the agency's clinical standards.
The agency allows an investigational device
exemption (IDE) for medical devices that
enables them to be used in research without
receiving premarket approval or 510(k)
clearance, but a lack of clarity in the exemption
has created a loophole that makes it possible
for RUOs and IOUs to seep into clinical use.
GenomeWeb
Revision of the EU Medical
Devices Directives
All of the current legislation regulating medical
devices is in the process of being revised at
European level. This will replace the existing
three European directives with two European
regulations.
The original European legislation was drafted
over 20 years ago and since then there have
been substantial changes. The number of
Member States in the EU has more than
doubled and there have been technological
leaps in device technology.
As a consequence, the application of the
existing medical devices directives is different
across the EU. This makes it difficult for the
legislation to achieve its objectives: the safety
of medical devices and their free movement in
the EU’s single market
The current system has operated well for the
period that it has been in place. We cannot
completely remove the risk to patients from
medical devices and there is a balance to be
struck between subjecting devices to
exhaustive scrutiny and allowing innovative
life-saving and life-changing devices onto the
market.
Nonetheless, we have to learn lessons from the
safety concerns of some metal-on-metal hip
replacements and fraudulent PIP breast
implants, and it is clear that the regulatory
system is in need of strengthening in some
areas.
MHRA
23
Regulatory and Government
U.S. New Drug Approvals Slip In
2013 vs. Prior Year
The number of new drugs approved in the
United States fell in 2013 compared with the
previous year as fewer applications were filed,
though several products for hard-to-treat
diseases were approved in record time.
The U.S. Food and Drug Administration
approved 27 new drugs in 2013, down from a
banner year in 2012 which saw 39 drugs
approved, the greatest number since 1997
according to FDA data.
The regulatory agency attributed the drop in
approvals in 2013 to fewer applications. As of
Dec. 11, 32 applications had been filed,
compared with 41 for 2012, the FDA said. Over
the past five years, the average number of new
drug filings per year was 35.
Reuters
Vantage Point – One year on,
breakthrough designation
remains an enigmatic accolade
For Scioderm it was a no-brainer. Once the
private biotech group became aware of the US
FDA’s new breakthrough therapy designation it
realised that its epidermolysis bullosa project
SD-101 ticked all the boxes and – just two
months after filing – the agency approved its
application.
Others have not been so lucky. But one year
after the new category was enacted by
legislation much secrecy remains, and it is far
from clear whether receipt or non-receipt of the
accolade is a material, disclosable event. If
anything is clear it is that the main
beneficiaries have been big pharma and big
biotech.
It was perhaps not supposed to have been this
way. The FDA has, for instance, promised to
work closely with successful sponsors on
clinical trial design and provide “intensive
guidance” on development as early as phase I
– a benefit surely aimed at small, cashstrapped biotechs (FDA not such a soft touch
on breakthrough therapies, June 26, 2013).
Yet almost 90% of the 19 granted
breakthrough therapy designations (BTDs) that
have been disclosed so far have benefited mid
and big-cap firms – an imbalance boosted by
Tuesday’s receipt by Novartis of BTD for
bimagrumab.
Evaluate Group
GAIN Act: A Great First Step
With over 2 million infections – and 23,000
deaths – caused by antibiotic resistant bacteria
each year in the US, everyone agrees there is
an urgent need to find new, effective antibiotic
therapies. One measure designed to spur such
development is the Generating Antibiotics
Incentives Now (GAIN) Act, signed into law last
year. Given the growing threat posed by
resistant bacteria, we decided to hold a
workshop with leading experts about what
effect the GAIN Act might have to incentivize
antibiotic development.
The GAIN Act is a “pull” incentive, providing a
payout at the end of the development process
with five years of guaranteed market
exclusivity and priority FDA review for
antibiotics that target qualifying pathogens.
24
Regulatory and Government
The value of this incentive can vary greatly
depending on how much patent life is left on a
medicine when it receives approval, because
market exclusivity is separate from the IP
protections granted by a patent. During the
market exclusivity period, the FDA will not
approve another version of the same drug even
if a drug’s patent life is expired. Conversely, if
a drug still has five or more years of strong
patent protections in place, the market
exclusivity provided by GAIN will not be of
much additional value.
Biotech Now
25
Health Care
Obamacare: Winners and Losers
for Investors
5 Hot Startup Opportunities
Created By Health Care Reform
Martin Tillier I hesitate to wade into the quagmire that is
politics, particularly regarding the Affordable
Care Act (aka Obamacare), but good trading
and investment decisions require at least an
understanding of the issues. In the current US
environment it seems that anything which
challenges preconceptions is dismissed as bias;
the best I can hope for here is to be accused of
bias by both sides. I can assure you that, as I
have been trained to do, I look at this purely
from an investment opportunity perspective.
The desirability or otherwise of the law could be
debated ad nauseum, but my concern is how
best to profit from the realities of it.
A key provision of the Affordable Care Act went
into effect on October 1, 2013, as statewide
insurance exchanges opened up around the
country.
This is the way traders are. They may have
political views, but they are trained to assess
potential economic effects and act on them.
I have been following markets, and the political
influences on them, for around 35 years. In
that time, I think that Obamacare is probably
the most misunderstood piece of legislation I
have seen. People on both sides of the political
divide have attached qualities, and therefore
consequences, to the law that simply don’t
exist. Obamacare is not a cure for all of the
forthcoming problems that demographics will
present, nor is it a calculated attempt to
destroy the US.
Nasdaq
But that’s just the latest in a series of changes
to the U.S. health care system that will open up
new opportunities for entrepreneurs.
With the passing of the Health Information
Technology for Economic and Clinical Health
(HITECH) Act in 2009, doctors got new
incentives to move from paper-based to digital
systems. As a result, investors poured funding
into new electronic medical record providers,
like CareCloud and Practice Fusion. Since then,
doctors’ use of electronic systems has shot up
— in May, the department of Health and
Human Services announced that doctors’ and
hospitals’ use of health IT has nearly doubled
since 2012.
Smart entrepreneurs are paying equally close
attention to the Affordable Care Act (ACA, also
known as Obamacare). We’ve already seen new
companies form to offer private health
insurance exchanges so consumers can shop
for affordable care. These exchanges are open
for business Oct. 1, 2013, enabling individuals
to sign up online, by phone, or in-person, with
health insurance coverage starting next year.
VentureBeat
26
Health Care
implement: Drexel University's John Cannan
needed 42 pages to describe the legislative
history in the American Association of Law
Libraries' journal. The whole experiment might
collapse of its own weight even if Republicans
fail in their efforts to eviscerate it legislatively.
But focus on the exchanges, the new electronic
markets where health insurance will be sold the
way flights are sold on Expedia or Orbitz.
Eligible consumers—the uninsured, those who
buy insurance on their own and certain
others—will pick a policy from competing
private insurance plans. Some will get
government subsidies; some won't. The theory
is that more choice and more competition will
yield better value.
Wall Street Journal
4 Ways New Exchanges Will
Radically Alter Health Insurance
Obamacare - A Game-Changer in
the Making
What if Obamacare actually works? More
precisely, what if the new health-insurance
marketplaces called exchanges work? They
might just change the way most Americans get
health insurance. Admittedly, this is a big if.
The launch of the exchanges was marred by
software glitches, confusion and outright
resistance in some states. The Obama
administration has delayed so many provisions
of the law, formally known as the Affordable
Care Act, that it resembles departure monitors
on a stormy summer afternoon at New York's
La Guardia Airport.
Messy drafting and a tortured partisan path
through Congress made the law hard to
When the next phase of the Affordable Care Act
(ACA) kicks into gear January 1, 2014, each
state will be required to offer its residents
access to health care insurance through an
online marketplace, often referred to as a
“health insurance exchange.” These exchanges
were open for business as of Oct. 1, 2013,
allowing individuals to sign up online, by phone
or in-person, with health insurance coverage
starting next year.
Until now, buying health insurance has been a
daunting task for most individuals and small
businesses. But purchasing health insurance
through exchanges will more closely resemble
booking a vacation on Expedia or Orbitz. People
using this vehicle to enroll will see lots of
options, common features among the offerings,
and greater transparency around price, quality
and consumer ratings.
27
Health Care
Similar to the implementation of Medicare, we
should expect program design and operational
issues at the outset. We already have seen
some technological glitches, which will need
adjustments and mid-course corrections as
these systems are rolled out in each state. But
despite the initial bumps in the road, the
exchanges will serve as a catalyst to alter the
way health insurance is purchased. In the
longer term, they will transform the entire
health care system.
Forbes
As More Americans Have
Surgeries Overseas, US
Companies Consider 'Medical
Tourism' a Health Care Option
With the rising costs of U.S. healthcare, an
increasing number of Americans are going
overseas for medical care. Medical procedures
that would cost U.S. citizens thousands of
dollars out of pocket are paid in full by the
company they work for when they decide to
have the procedure done in another country.
American companies now see outsourcing
medical care as an alternative option. Also
known as “medical tourism,” this option saves
companies and employees thousands of dollars
since surgeries and other medical treatments
can be as little as half the cost in a foreign
country than in the U.S.
There are downfalls to consider. Patients who
receive treatment overseas run the risk of
getting an infection or possibly dying. There
have been documented cases of post op
complications resulting in serious further injury.
U.S. citizens needing expensive medical
treatment must assess their options to
determine if “medical tourism” is the right
choice for them.
ABC
28
Big Data in the Life Sciences
This year Carlyle Conlan and george james, Ltd. were pleased to interview several senior
professionals involved in big data breakthroughs in the life sciences sector. The enormous
increase in data volume from segments like sequencing and systems biology coupled with
trends in pre-competitive data sharing and advanced computing frameworks is in the early
stages of providing robust signals that will, ultimately, decrease the cost of drug
development and maximize the industry’s return on investment.
Clinton Health Access Initiative
Paul Domanico
The Clinton Health Access Initiative (CHAI) is a global health organization employing over
1000 people in dozens of countries that is committed to strengthening integrated health
systems in the developing world and expanding access to care and treatment for HIV/AIDS,
malaria, tuberculosis, malnourishment, amongst other health issues facing these areas. With
respect to AIDS care and treatment in Africa alone, CHAI has successfully improved drug
distribution, reduced the cost of HIV treatment by up to 90 percent and HIV diagnostics by
up to 80 percent, and has saved developing nations over $3 billion in overall treatment costs
since 2003.
Life sciences veteran Paul Domanico helps CHAI carry out its mission. Paul, now senior
director of research and development (R&D) at CHAI, has 27 years of experience in
discovering and developing drugs and medical technologies. Before joining CHAI Paul was a
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Big Data in the Life Sciences
managing partner at life sciences consulting firm, Innovalyst. His experience also includes
R&D executive posts at GlaxoSmithKline, where he created the industry’s first technology
accelerator for early-stage companies combining GSK’s expertise and infrastructure with
outside investment.
The goals for CHAI’s R&D department are to identify, develop, validate, and transfer for
manufacture and distribution better and less expensive formulations of existing AIDS, TB,
and Malaria medicines, to use applied analytics to identify cost effective ways to optimize
healthcare in low resource setting, and to grow an R&D portfolio of new medicines, vaccines,
diagnostics, and technologies for these diseases and others. Carlyle & Conlan’s Don
Alexander recently interviewed Paul about his thoughts on big data.
Don: How do you define big data?
Paul: An extraordinary amount of information that comes from very different sources and
that includes structured and unstructured data. Big data involves a suite of sophisticated
analytical approaches to analyse this data to differentiate relevant direct and indirect
relationships from the truly irrelevant. The purpose is to find a deeper relationship between
disparate types of information to help inform and direct your business. And this is the critical
bit, when you are trying to expand your understanding of a field, how do you ensure you
have the focus tuned appropriately?
Structured data is easier to work with but represents only a small part of what we analyse.
For unstructured data, Big Data tools need to be trained to annotate this information for key
words, grammar, and concepts. So, this means that to be successful you must build a strong
team of domain experts and big data analytics experts who are committed to finding new
correlations and causalities, and possess the rigor to stay focused and to ensure the findings
are meaningful and will, in fact, impact the direction of your business.
Don: Can you offer a case study as an example?
Paul: CHAI is partnering with the Center for Innovation Management Studies (CIMS) at NC
State University’s Poole College of Management to explore big-data analytics to discover
novel ways to diagnose and treat infectious disease in third-world countries. Initially, the
CHAI-CIMS partnership will focus on developing faster, more cost-effective ways to diagnose
tuberculosis (TB). The project is designed as a three-stage, proof-of-concept scheduled to
take roughly 18 months to complete. In addition to advancing its TB diagnostics work, the
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Big Data in the Life Sciences
CIMS-CHAI partnership will also create capabilities within CHAI to address other infectiousdisease efforts.
Low resource settings bring into play a number of additional challenges associated with the
diagnosis and treatment of disease. One goal is to improve our understanding of those
factors that impact healthcare, and then rank and summarize them into target product and
service profiles. As an example, we are looking to identify TB diagnostic platforms that do not
involve lung sputum, which is difficult to obtain and to work with. Big Data will bring to our
attention all types of information related to TB, pulmonary disease, latent disease, comorbidities associated with infectious disease and as important put these into perspective by
ranking them against investment, type of investment, development stage, consistency, etc.
Don: What discoveries did you make that you can attribute to big data?
Paul: We noticed that factors related to demography and healthcare systems were more
important than first realized. In many parts of the world migration of workers can have a real
impact on all aspects of disease monitoring and management. We also showed that as hard
as one tries to stay connected to relevant information in a specific field, you can’t and won’t
be able to know everything. So, Big Data tools can help make connections across scientific
silos and help to verify those connections. Specifically, we identified some very exciting work
related to miRNA exosome profiles from breath and blood as a potentially new approach to
diagnosing pulmonary disease and potentially to diagnose both active and latent TB using the
same platform. We were aware of exosomes but not the amount of work that has taken place
and that was related to our work.
Don: What issues or limitations did you have or expect to encounter? For example,
would you have done anything differently in retrospect? What limitations do
current tools have that the tools of tomorrow might address?
Paul: The reality is that Big Data is currently not a product but a partnership or service
between client and provider. In the medical field, we are in the early days for Big Data
analytics. Irrespective, integrating Big Data approaches into corporate culture requires a
sustained commitment or it will end up being a waste of time and money.
Don: Looking ahead in the next few years, what other types of challenges in the life
sciences, do you expect big data to help address?
Paul: Big data will revolutionize how research, business, and investors connect and
collaborate. From my perspective, the challenge is actually not the analytics but ensuring big
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Big Data in the Life Sciences
data objectives and the queries associated with these objectives are excruciatingly clear.
Only then will the output be meaningful and have a positive impact on business. For this to
happen, I strongly believe that organizations need to bring in expertise from the outside to
ensure that proper diligence is done on their big data objectives and approach. I am sure this
is true not only for the life sciences but for all verticals exploring big data. My sense is that in
data rich areas, such as consumer products and social media, the value of big data will be
realized more quickly than in the life sciences but I am looking forward to changing that
situation.
Don: What else?
Paul: It is very difficult to keep your focus when evaluating the results from a big data
analysis because you retrieve such interesting and potentially valuable information. It is like
being a kid in a candy store. Successful teams will have developed a mechanism to help
them stay on track and highlight trends and findings that should be explored at a later date.
I also know that the very concept of big data analytics can be confounding to an
organization. I suggest that organizations new to big data start simple, establish small
successes, and then expand the scope of their big data efforts as their experience and
confidence grows. Along the same line of thinking, big data will have its fair share of skeptics.
This is good and healthy. The articulate skeptic can be your most important team member to
help demonstrate big data’s value and return on investment.
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Big Data in the Life Sciences
Eagle Genomics
Richard Holland
The explosion of data in the life sciences has sparked the growth of companies like Eagle
Genomics, a specialist in helping clients manage and analyze genomic data. Eagle’s client list
covers a range of companies in drug discovery, agriculture and personal hygiene, all of them
looking for ways to use genomic data to develop new products.
Eagle’s Chief Business Officer Richard Holland has more than nine years of bioinformatics
experience spanning both industry and academia. He is a founding member of the Open
Bioinformatics Foundation, the organization that backs most of the key open-source
bioinformatics programming toolkits such as BioPerl and BioJava. Richard was also lead
developer on BioJava, the primary resource for Java developers working in bioinformatics.
Richard recently took time to talk with Carlyle & Conlan’s Don Alexander about big data.
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Big Data in the Life Sciences
Don: What is your definition of big data?
Richard: Many people think of big data in the life sciences in terms of marketing and sales
information revolving around physicians and patient stratification. Eagle is involved in R&D
data, genomic sequencing data, and NGS (next generation sequencing), so, the front end of
R&D. The data is usually thousands of smaller files with different sources of information, dissimilar structures, and a diversity of data types and formats. Given the diversity, it can be a
challenge to pull everything together.
Don: Can you give an example?
Richard: The use case cited often is for Unilever, a manufacturer of consumer goods such as
skin care products. The case study involved the bioinformatics of how products behave where
Eagle took existing workflows, moved them, optimized them and made them scale. The
design is what is important. Eagle is working on a platform to manage data more effectively
as moving around data from place to place is an issue. Metadata management includes
cataloging files and describing them at the experimental level, in a consistent manner, to
work out gaps in organizational knowledge that occur or to test a new hypothesis.
Don: What discoveries did you make that you can attribute to big data?
Richard: As Eagle focuses on early stage R&D it is a little harder to say. The suspicion is that
there are R&D contributions to stratification of products.
Don: What issues or limitations did you have or expect to encounter?
Richard: Data is not homogenous. It is varied in detail and sometimes poor quality so you
have to separate and QC it. The second issue is what one is trying to achieve with
sequencing. Often, the approach is “I have this data, tell me what it means.” while the
better approach may be “I have this question, what do I need to test to get the answer?” The
other consideration is that requirements change rapidly and the data can change the
direction of the product so one needs to make allowance for these directional changes.
Don: Looking ahead to the next few years, what other types of challenges in the life
sciences do you expect big data to help address?
Richard: Given early stage R&D, the data itself solves nothing. The ability to solve issues is
improved by the ability to access data. In order to forge ahead, there needs to be greater
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availability of public shared data. In order to get value, sources of data that include changes
of consent systems for broader research use, need to be leveraged. The FDA, for instance, is
often playing catch up with cloud infrastructures. Regarding data security, most cloud
providers are more secure than the pharma companies themselves.
Don: What other big data issues are you thinking about?
Richard: The concept of Big Data has been around for some time. Ten to twenty years ago,
it was called data integration, so this is not a new problem and there have been many years
of research ongoing. Only recently has the scale of the issue gotten to the point where people
have to take it seriously. It is important to think of the lessons learned from previous data
integration efforts. There will continue to be specialist niches in big data as there is only so
much one can do in terms of standardization, mining and analysis. Clients shouldn’t assume
that off-the-shelf systems that claim to do “X” will do “X” 100 percent of the time. Regarding
advances in machine learning and artificial intelligence, one has to understand that biological
facts are less well-understood and hugely diverse when compared to physics or chemistry
where systems can be very well modeled in great detail. There could be thousands of
reasons why one has cancer and it is difficult to find combinatorial methods that would tell
you why. The diversity of cancer is so huge, for instance, that the traditional methods of
machine learning don’t really work as well.
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Big Data in the Life Sciences
Code-N
Marketta Silvera and Randy Haldeman
The life sciences have always produced large amounts of data. As the amount of data
produced grows exponentially, new methods are needed to glean useful insight from it. Cloud
computing company Code-N was founded to solve Big Data problems that can’t be solved
with the keyword-based Internet software and search technologies. Code-N’s technology
spans the gamut of life science applications helping pharmaceutical and biotechnology
companies more quickly and more efficiently discover new drugs, repurpose old ones and
monitor the current slate of already commercialized products for both safety and competitive
reasons.
Code-N founder and Executive Chairman Marketta Silvera has more than 20 years experience
as chief executive of four technology companies serving the health care and financial
industries. Her Big Data background includes work with life science inventors and
cheminformatics experts at the Netherlands Bioinformatics Center several years ago to
develop concept-based technology solutions that leverage public/private partnering and Big
Data. Code-N is led by CEO Randy Haldeman. Before becoming Code-N’s CEO, Haldeman led
the content division of Symyx/Accelrys (NASDAQ: ACCL), a leading provider of informatics
solutions to more than 1,300 corporations in the pharmaceutical and biotechnology industries
including companies such as Merck, Bristol Myers Squibb, Pfizer, Eli Lilly, Novartis,
AstraZeneca, and GlaxoSmithKline. Marketta and Randy took some time recently to share
their thoughts about Big Data with Carlyle & Conlan’s Don Alexander.
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Big Data in the Life Sciences
Don: What is your definition of big data?
Marketta: Big Data is for real and it’s exploding in our digital lives. Since the late 1990s,
assisted by the Internet, the world’s businesses and population have freely participated in
generating new data in numerous forms. By now there are many definitions for Big Data. The
consulting firm NewVantage Partners’ “Big Data Executive Survey 2013” defines Big Data as
“collections of data so large, complex, or requiring such rapid processing (sometimes called
the volume/variety/velocity problem), that they become difficult or impossible to work with
using standard database management or analytical solutions.”
But it’s the volume of Big Data that’s unimaginable. Consider that just a year ago, the world
was creating some 2.5 exabytes (25 billion gigabytes) of data every day, which on an annual
basis is equivalent to filling 30,000 new U.S. Libraries of Congress. TechAmerica Association
estimates that 90 percent of the data that has ever existed has been created in the past two
years. Internet searches, satellites, massive research projects like the human genome,
mobile devices, security cameras and remote sensors – all these data generators and dozens
more, are fueling data proliferation on an epic scale.
Big Data has become the new raw material in business, next to capital and labor. Today’s big
market opportunity lies in innovative technologies that help extract the intelligence and
relevant insights from overwhelming quantities of information. The benefits of accessing this
vast resource are extraordinary. For example, decoding the human genome took ten years
the first time it was done. Now it can be achieved in one week. Companies’ investments in
Big Data are projected to rise from 19 percent in 2013 to 50 percent by 2016, according to
the NewVantage Partners survey.
Big Data has the potential to transform everything.
Don: Can you give an example?
Randy: One of the impediments to rapid adoption of Big Data solutions in the life science
industry is that for each drug, disease and treatment, there are dozens of synonyms to
describe each. In the past, there was no easy way to successfully connect these "dots"
across databases; and thus, much of the potential discoveries due to cross-pollination never
happened. The hurdle the industry must clear in order to connect massive amounts of data is
to define a universal way, i.e. a conceptual way, to identify each entity involved, whether it
be a chemical, gene, protein or toxic affect. No single software application can address that.
a comprehensive approach must be taken.
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Big Data in the Life Sciences
Over the past 10 years, semantic languages have been brought to the forefront in an attempt
to connect this data, but the fatal flaw is that they can’t handle the massive redundancies
and ambiguity. The next-level semantic technology is needed, and that’s what Code-N
is currently launching to the market – a concept-based approach that can connect and
interpret this data as well.
Code-N has created the world’s largest meta-thesaurus of chemicals, genes, proteins and
diseases. Starting with the 2 million chemical-gene-protein terms in the UMLS thesaurus,
Code-N added several million more from sources such as DrugBank, KeGG, CAS,
HomoloGene, HMDB, ChEBL, MeSH, and dozens of other industry sources to create the most
comprehensive compendium of concepts, synonyms and database identifiers known in the
industry. While leveraging this mega meta-thesaurus, Code-N built a series of solutions that
can access multiple industry databases simultaneously, whether structured or unstructured,
public or private, and connect the-dots between these no matter what the different genes,
chemicals or proteins are called. These multiple databases can be queried using simple
sentences, with no need for complex syntax or Boolean operators. Now that this conceptbased technology is available, exciting advances are possible. Big Data can be leveraged to
address current challenges such as competitive surveillance, drug repurposing, advanced
safety and toxicology analysis, and resurrecting “shelved molecules.”
Don: Tell me more about how Big Data can help overcome these challenges.
Randy: In competitive surveillance, a search for competitive information on compounds,
targets and diseases from two companies can simultaneously access 23 million PubMed
abstracts, all patent grants and applications, clinical trial data, FDA repositories, and internal
databases within 2 or 3 seconds, then send an alert to all interested parties within a
company. Even if a competitor is trying to obfuscate its recent research by describing its
findings with obscure terms, the concept-based system will be able to identify these and
bring them to the light-of-day.
Big Data can be used to find ways to repurpose drugs coming off patent. This research
usually takes weeks or months to find viable opportunities. With new applications that can
"connect-the-dots" in Big Data, this process can be made orders-of-magnitude faster. Being
able to scour all published literature to find all the targets that “Drug A” affects, these
applications can then "follow the trail" to see what disorders can be influenced in a positive
way when these targets are affected.
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Big Data in the Life Sciences
Toxicology analysis benefits from Big Data. When comparing the potential effects of a new
compound to known toxic chemicals, scientists are often limited to comparing the up- and
down-regulation of just two or three genes and proteins at the same time. The advent of
technologies that can more adeptly handle Big Data means there are no longer limits on the
amount of comparisons that can be made at the same time. A "digital fingerprint" can be
created with the combination of dozens of affects that a new compound is known to cause,
and compare that with a library of known toxins within seconds.
And Big Data can also salvage molecules that have been shelved for one reason or another.
Every pharmaceutical and biotech company has a catalog or database of molecules or
compounds that didn't meet expectations for a specific task. Some were too costly to produce
for an intended market or didn't have the expected effect on the particular target. Others
were toxic or simply lost out to a "superior" compound. What if these compounds and their
known properties and characteristics could be aggregated in an open-source data store, and
shared with the entire industry? This is a perfect challenge for Big Data. Sharing these data
pre-competitively would help others avoid making the same mistakes again and again.
Imagine being able to search on an idea and quickly see it’s a non-starter because the drug
class is associated with liver damage. Information like that would make drug discovery
smarter and lead the field in more productive directions. Imagine if the billions of dollars
"wasted" on failed molecules wasn't wasted, but leveraged to further the science on
other discoveries industry-wide.
Don: What discoveries did you make that you can attribute to Big Data?
Randy: One example of using this breakthrough “concept technology” is a client who was
looking to repurpose the cholesterol-lowering drug, atorvastatin (marketed under the name
Lipitor®). Since it is now off-patent and has a fairly strong safety profile, they wanted to see
how the Code-N solution could speed-up uncovering possibilities they might be able to
market. They stated their scientists were able to come up with a new target about once
every seven to 10 working days. While using the Code-N repurposing application, they were
able to connect-the-dots between 23 million PubMed articles, 1.5 billion pharmacological data
statements and 25 years of patents to produce dozens of unclaimed treatment ideas in less
than seven seconds. For instance, the data suggested that atorvastatin might be used to
treat Huntington’s Disease, Multiple Sclerosis (reducing brain plaque), and xanthomas. The
data does have to exist to "connect-the-dots" but if it does exist, a conceptual approach can
extract these insights whether atorvastatin is called atorlip in one database and totalip,
xavator, C33H35FN2O5 or one of its other 96 synonyms in the others.
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Big Data in the Life Sciences
Code-N isn’t claiming to be an authority on the science of treating diseases – that is left up to
the pharma and bio-tech companies it serves. But what Code-N does is provide the
informatics solutions that can access massive amounts of Big Data from many disparate
sources and bring-to-light ideas within seconds that scientists can then investigate and test.
Another example of a problem that can be solved with Big Data is to be able to quickly
identify safety issues with new compounds by creating digital fingerprints of their effects and
matching them to a library of known toxins. Identifying those safety issues early can stop
development of a compound immediately.
Don: What issues or limitations did you have or expect to encounter?
Marketta: Disruption in any industry needs to happen when the status quo begins to prevent
progress and innovation. It is healthy to challenge inertia and drive change. We’ve all
witnessed frequent reporting on the fact that the life sciences industry is lagging in its ability
to innovate. The reasons include slowness and reluctance of converting old infrastructures to
new technologies due to risk aversion that drives companies to stick with familiar business
models and R&D tools. A scientist at a major conference said: “Unless we learn to value big,
potentially disruptive ideas, we won’t see transformational breakthroughs.” We’ll continue to
get the status quo: linear, unproductive drug pipelines, siloed data that fails to support open
collaboration and partnerships, and outdated regulatory structures and funding models that
stifle R&D.
The good news is that the phenomenon of Big Data is poised to fuel this disruption
beneficially. Even though many health care organizations are still wrestling with basic
transaction systems, such as electronic medical records, significant initiatives are under way
to leverage Big Data to accelerate drug lead discovery, development, repurposing, and
safety. There’s a strong incentive to leverage all public and precompetitive private data
sources to speed up innovation and disrupt the old paradigms. Open collaborative
organizations are successfully being introduced to pursue cures for a wide range of
challenging diseases. And, on the business side, pharma companies are using Big Data to
drive new inventions to make up $35 billion in lost revenue from patent expirations just a
year ago.
The life science industry has begun the process of structuring itself more openly. Industry
forums and initiatives are valuable contributors. Big Data provides “raw material” for the
emerging open environment. New bioinformatics technologies and infrastructures are needed
to “cross the chasm.”
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Big Data in the Life Sciences
Of all U.S. industries, the life science industry has one of the biggest gaps in what can be
done with Big Data and what is actually being done. Big Data can be leveraged in so many
ways to advance science, improve safety and create positive results for patients but we are
only in the initial phases of this revolution.
Don: Looking ahead to the next few years, what other types of challenges in the life
sciences do you expect big data to help address?
Marketta: Big Data has become a buzz phrase, which can easily be hyped inappropriately as
the long-awaited trove of missing answers and cures. In reality it’s the “raw material” for all
that and
more when enabled through advanced technologies to connect all relevant data
simultaneously, discard the “noise” and interpret the data in response to “smart” questions.
It has the potential of providing deep knowledge for reasoning and predictive capabilities
needed for the medicine of the future but not available today.
Today we are dealing with the “first phase” of utilizing Big Data – establishing the baseline
for required infrastructures, bridging the silos for instant, simultaneous data access and
implementing integrated “intelligent results” via next-generation semantic analytics.
It’s quite exciting to think of what lies right ahead of us as a result of the vast Big Data “raw
material” and technologies that can extract intelligence from it. Not only will we be able to
use real-time data, for example, to repurpose drugs to treat multiple diseases and to
discover new warnings of side effects, but also to unlock the power of data to improve clinical
care. We’ll be able to get to the genome level for real-time detection of diseases and find out
in advance whether it’s resistant, infectious, etc. We can look forward to relating the entire
microbial genome to the human genome and targeting the best treatment, understanding
what has to be done to prevent spreading of a disease and how to prevent it in the first
place. Future Big Data will assist in “precision medicine” that is expected to use in-depth DNA
analysis to personalize drug therapy for patients and search for the genetic causes of
diseases.
Don: What other Big Data issues are you thinking about?
Marketta: The most interesting characteristic of Big Data is that it’s heuristic by nature. The
information, hypotheses, innovations and feedback that the life sciences industry feeds into
Big Data around the clock, increase its “brain power,” which in turn enables our conceptbased semantic solutions to point out the most up-to-date discoveries to build on, which in
turn accelerates next innovations in the industry. We call that the “Heuristic Big Data Cycle”.
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Big Data in the Life Sciences
NuMedii
Gini Deshpande
Finding and developing new drugs has always been challenging. NuMedii faces those
challenges with technology that discovers potential new drugs and reduces some of the risks
in drug development. The key is big data. NuMedii’s proprietary technology comes from
Stanford University, where it was developed in the lab of Atul Butte, a scientist and
entrepreneur known for his work in biomedical informatics. NuMedii holds an exclusive
license for the technology, which consists of hundreds of millions of raw human, biological,
pharmacological and clinical data points that the company has
normalized and annotated. These data are integrated with proprietary network-based
algorithms to find both drug candidates as well as biomarkers that can predict a compound’s
efficacy for a particular disease.
NuMedii is led by founder and CEO Gini Deshpande, who has more than 10 years experience
incubating, developing and commercializing life sciences technologies that bring scientific
innovations to patients. Gini has worked as a consultant helping startups raise money and in
strategic marketing for Affymetrix, where she was responsible for the Academic Business
Research Unit – the company’s largest customer segment. At NuMedii, Gini raised the
company’s Series A financing, built the team and advisory boards and structured strategic
partnerships with Thomson Reuters and Aptalis. Gini took some time recently to speak with
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Big Data in the Life Sciences
Carlyle & Conlan’s Don Alexander about how NuMedii uses big data.
Don: What is your definition of big data?
Gini: Big data is quite a buzzword and is hard to define. Our definition of big data is data that
is unstructured, often dispersed and not always useable. In life sciences, the scale of big data
is even more complex. There are big challenges that lie in synchronizing disparate data types
with little standardization and from different platforms. Human biology is complex and
profiled using many different tools, so there are several modalities of data that are collected
and need to be connected together to extract meaningful information from life sciences big
data.
Don: How is NuMedii using big data?
Gini: NuMedii might be characterized as a “Digital Pharmaceutical Company.” The company
leverages a lot of life sciences big data but is very much a biotech company as the focus is on
developing effective compounds. Internally, we have developed tools for working with life
sciences big data and as we are the primary consumers of this data, we have focused on the
accuracy and quality of data, rather than building nifty user interfaces. Because we develop
drugs to a certain point ourselves, all of the data that gets incorporated into our big data
technology is tied to its utility for discovery of effective drug assets rather than building in
new features with little practical utility. Recently, we have structured a partnership with
Thomson Reuters that helps us to leverage the strength of Thomson’s knowledge content
with our big data platform to create a really robust technology to discover effective drugs.
Don: How do you monetize Big Data?
Gini: The fundamental value in life sciences big data is when we positively impact the life of
a patient. To that end, NuMedii focuses on discovering and de-risking effective drugs
identified by our big data technology. We are currently re-purposing existing compounds and
our big data technology is being built to enable work with new molecular entities (NMEs) in
the future. We test these drug candidates in appropriate preclinical models and our plan is to
take these through a Phase 2a proof of concept (PoC) study in relevant patient populations.
We plan to partner with or outlicense our drug candidates to specialty pharmaceutical
companies that have formulation, clinical development and commercialization capabilities to
bring these drugs to market. These partnerships will generate revenues for the company,
with a combination of upfront and milestone payments along with royalties. For instance, the
partnership with Aptalis Pharma for our gastroenterology and cystic fibrosis portfolio is a
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Big Data in the Life Sciences
good example of how we partner our programs. We anticipate doing more collaborations
along these lines in the future.
Don: What discoveries did you make that you can attribute to big data?
Gini: There are papers on our web site covering the following discoveries
Epilepsy drug Topiramate (Topamax) could help fight inflammatory bowel diseases such as
Crohn's disease
Cimetidine (Tagamet), an acid inhibitor that is used to treat heartburn, interacts with
pathways involved in lung adenocarcinoma, a type of non-small-cell lung cancer
A tricyclic antidepressant, Imipramine (Tofranil), on small-cell lung cancer
Don: What issues or limitations did you have or expect to encounter?
Gini: There are limitations in the types of diseases or conditions profiled with high
throughput molecular data. Smoking cessation, for instance, has not been studied using
microarray tools, so we may be unable to utilize our big data technology to identify drugs for
this condition. There are also challenges that are not technological. Translating big data into
drugs requires a good understanding of side effects, intellectual property, formulation or
other issues that come into play in drug development. This is the reason we have built
translational capabilities into our team. Additionally, information is sometimes siloed and
there are barriers to getting data where trials, say, have failed. In terms of big data
technology itself, there will be the need to work across technical architectures as more data
types become available.
Don: Looking ahead to the next few years, what other types of challenges in the life
sciences do you expect big data to help address?
Gini: People are continuing to understand, through molecular biology, that diseases are an
amalgamation of different conditions and systems. Big data and methodologies that enable
identification of subsets of patients and markers can be very useful in expediting the process
and reducing the cost of drug discovery and development.
Don: What other big data issues are you thinking about?
Gini: Resource challenges in finding people who have the skill sets to work with all of this
data. What we do requires very different training from the ground up. The skill sets to
tackle these issues requires a different way of thinking.
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Contact Us:
For more information or to submit comments, please contact:
For Carlyle Conlan:
Don Alexander
Practice Head and Vice President, Life Sciences
dalexander@carlyleconlan.com
For george james, Ltd.:
Neil Burns
Founding Director
Neil.Burns@georgejamesltd.co.uk