open source pharma: the future of drug development

July 2014

Open Innovation:The Future of Drug Development

Tomasz Sablinski, MDCo- Founder, CEO

“Toward a New, Open Source Pharmaceutical Industry”July 16, 2014 Bellagio, Italy#opensourcepharma

Does TLS Model Apply to Global Health ?

1. transparency

2. crowdsourcing

3. telemonitoring

Sixty Years of Declining Productivity

Dismal Success Rate in Late Development

The World of Computing Power vs. Pharma

The world ofPharma:CRF Books

Technology Today

most clinical studies are conducted as if we were still in the 1980s

yet

technologies exist to move clinical research into the 21st century

Technology Today

The first electronic medical record system was installed at Akron Children Hospital in 1962

February 17, 2012

Drug Development – Current Model

Multiple Patient Visitsto Expensive Sites

High-Cost Patient Recruitment

Insular Protocol DesignDriven by Market Access

+

20th Century Data Capture & Analyses

+ =

+

Pharma CompanyInfrastructure

+

Exorbitant Wasted Costs

Does This Look Familiar?

After: Henry Chesbrough, 2007

The closed innovation paradigm

The Open Innovation Paradigm

Open Innovation…

…Connecting Problems with Solutions

From Open Innovation to Crowdsourcing

one-on-one cooperations

crowdsourcing

consortia

Transparency Life Sciences

Transparency Life Sciences is the world’s first drug development company based on open innovation

We are revolutionizing drug developmentby transforming clinical trials – the most expensive & inefficient element

Drug Development – TLS Model

Get protocol input fromglobal community of patients, MDs,

researchers; facilitates patient recruitment

Minimize site visits,Improve data quality,Execute at fraction of

usual cost

+ =

Deliver more drugswith optimal labels

1. Crowdsourcing 2. Telemonitoring/eHealth

Impact

3. Transparency – Build trust & participation

Crowdsourcing – “10,000 Minds Are Better than 10”

Context• Web-based approach solicits global

input from researchers, patients, MDs

• Applies proven open innovation methodologies to clinical protocol design

• Opportunity to gain from expertise in and outside drug development

• Tiered incentives to participate:• Professional development (researchers)

• Impact / Belonging (patients)

• Community, financial (everyone)

Impact• More relevant protocols, lower costs,

patient and researcher engagement

TLS Crowdsourcing Stats – As of July, 2014

Visits: over 34,000Unique visitors: 21,8000

Registered users: 1,100 +Contributors: 370 +

TLS Protocol Builder – Sample Feedback

Protocol Builder (MS)

“Real advances in one's ability to walk, use hands, reduction in stiffness are key endpoints that I would like to see in studies.”

- Patient X

Crowd Input - Patients

“Metabolic response from Phase II would be required and useful for Phase III response ranges “

- Researcher Y

Crowd Input - Researchers

TLS Platform in Action – Metformin in Prostate Cancer

TLS Protocol Builder – Sample Researcher Feedback

The Long Tail Model, Chris Anderson - 2004

think of: Amazon or Netflix vs. brick and mortar retailers

The Long Tail Model in Clinical Research

design: KOLs only

participation: few easily accessible patients

I G N O R E D

The Long Tail Model – Transparency LS

design: patients and physicians involved; head or long tail

execution of clinical trials: making it possible for the long tail patients to participate: telemedicine

Growth of Telemedicine

The Wireless Revolution Hits Medicine

Telemonitoring – Riding the Wave

Context• Remote patient-monitoring device market

will reach $1.9 billion in 2014 (Juniper Research)

• By 2020, 160 million Americans will be monitored and treated remotely for chronic conditions (Nerac)

Impact• Goal: slash costs, improve quality

• Circumvent high fixed costs of hospitals, clinics (cost)• Eliminate observer bias (quality)

• Baseline assumption is first/last visit in clinic, balance of data collection via telemonitoring

• TLS leverages expanding ecosystem of FDA-compliant telemonitoring service providers

Benefits of Telemonitoring in Clinical Research

Quantitative

Obvious – less expensive trials

Qualitative

Non-obvious – new endpoints, novel designs

Three Reasons to be Optimistic

1. social changes / culture

2. technology

3. crisis

TLS Model Does Apply to Global Health

1. transparency

- essential to do good

2. crowdsourcing

- motivated contributors

3. telemonitoring

- cost efficiency, operational facility