Life Science

Trends 2014

www.carlyleconlan.com

D. Alexander, C. Hamilton, A. McDowell, B. McMerty,

N. Burns, C. Hancock, J. McLaughlin

Feature Article:

Big Data in the

Life Sciences

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 befound 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 1

In Vitro Diagnostics Growth to Spearhead Future of Medtech 1

Iknife: Sniffing Out Cancer 2

Wait, Did This 15-Year-Old from Maryland Just Change Cancer Treatment? 2

Regenerative Medicine, Global Aging Were Hot Topics at Life Science Conference in Stockholm 3

Top 10 Experimental Cancer Drugs – 2013 3

Microbiomes Make Big News 4

Fundamental Trends

Open Innovation in Pharma: Defining the Dialogue 5

Gene Scans Solve Mystery Diseases in Kids, Adults 5

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 6

Pfizer Expands Clinical Trial Data Access Policy and Launches Data Access Portal 6

Club of 2018 Confirms Big Biotech’s Ascendancy 7

Advanced Genetic Testing Paves Way for Personalized Medicine 7

Tufts Report Confirms Domination of Biotech Products 8

IBM and Cleveland Clinic Put Watson To Work 8

Global Drug Spending to Reach $1 Trillion In 2014 9

Matters of Evidence 10

Investment and Deal Making

Royalty-Based Venture Financing, Born In Boston, Could Shake Up VCs And Startups From

New England To The Northwest 11

Funding Dries Up for Medical Startups 11

Biotechnology Boom is Here to Stay, Investors Say 12

F-Star Forges Immuno-Oncology Spin Off in Latest Test of Asset-Centric Model 12

Vantage Point – Under Pressure to Return Profits, Venture Funds Raise New Money 12

SEC Moves Ahead With 'Crowdfunding' Proposal 13

Banner Year for Life Sciences IPOs 13

NIH Cuts, Reimbursement Fears Cited as M&A Deals in Life Science Tools, MDx Industries

Drop 15 Percent in 2013 14

Strong Momentum in Healthcare: Trends in Mergers and Acquisitions 14

Biotech 2013 by the Numbers: A Blockbuster Year 15

Summary of the Campbell Alliance 2013 Dealmakers’ Intentions Survey 16

Regulatory and Government Novartis Loses Landmark Drug Patent Battle in India 19

NHS Medicine Spend to Remain Flat for Two Years 19

Senate Spending Panel Approves $31 Billion for NIH in 2014, Restoring Sequester Cuts 20

2014 May Bring Unwelcome Change for In-Vitro Diagnostics Companies 20

FDA in Personalized Medicine 21

FDA to Regulate Some Medical-Related Apps 21

Table of Contents

Misconduct Delayed Drug Approval 22

FDA Releases Guidance on Research Use, Investigational Use Only Ivds 22

Revision of the EU Medical Devices Directives 23

US New Drug Approvals Slip In 2013 Vs. Prior Years 24

Vantage Point – One year on, breakthrough designation remains an enigmatic accolade 24

GAIN Act: A Great First Step 24

Health Care Obamacare: Winners and Losers For Investors 26

5 Hot Startup Opportunities Created By Health Care Reform 26

Obamacare - A Game-Changer in the Making 27

4 Ways New Exchanges Will Radically Alter Health Insurance 27

As More Americans Have Surgeries Overseas, US Companies Consider 'Medical Tourism' a

Health Care Option 28

Featured Articles – Big Data In The Life Sciences

Clinton Health Access Initiative – Paul Domanico 29

Eagle Genomics – Richard Holland 33

Code-N – Marketta Silvera and Randy Haldeman 36

Numedii – Gini Deshpande 42

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 below-average 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

1

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 prize-winning 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-year-

old 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

2

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

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

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-3-

based 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 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

3

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

4

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?

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

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

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.

5

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

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

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 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

6

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

7

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

8

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

9

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

10

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

11

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 Asset-Centric 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.

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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.

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

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.

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

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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.

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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 venture-

backed 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.”

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.

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

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 in-

licensers, 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 out-

licensers 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

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

NHS medicine spend to remain flat for two years 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

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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.

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.

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

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 in-

vitro 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 Medical-

Related 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

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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 Delayed Drug Approval US Food and Drug Administration (FDA)

approval for the blood-thinning drug Eliquis was delayed for 9 months due to errors and

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 low-

cost areas, either fix the low-cost areas, or stop doing them [there].”

The Scientist

FDA Releases Guidance on Research Use, Investigational Use Only IVDs

The Food and Drug Administration has released a guidance document that lays out and clarifies

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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, cash-strapped 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.

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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 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. 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

5 Hot Startup Opportunities Created By Health Care Reform

A key provision of the Affordable Care Act went into effect on October 1, 2013, as statewide

insurance exchanges opened up around the country.

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

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Health Care

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

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 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 infectious-disease 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, co-morbidities 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, dis-

similar 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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Big Data in the Life Sciences

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 concept-

based 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 concept-based 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