10/22/2015
1
Causes and Effects of Paradigm Shifts in Clinical Research
Why the Drug Development Paradigm is Why the Drug Development Paradigm is
Failing and a Compelling Path ForwardFailing and a Compelling Path Forward
Ken Getz, MBA
Director, Sponsored Research Program, Associate Professor
CSDD, Tufts University School of Medicine
November 2015
10/22/2015
2
Agenda
• Our Traditional Drug Development Paradigm
• Why Drug Development Optimization Remains Elusive
• Compelling Value Proposition of a New Paradigm
3
Drug Pipeline Activity
4,8855,482
6,476 6,531
8,0108,617
9,349
10,150
2000 2002 2004 2006 2008 2010 2012 2014
Source: FDA
10/22/2015
3
30
35
2724
1721
31
18 1816
2119
15
2628
24
30
7
3
25
7
6
5
24
2
4 7
6
9
11
3
11
98 99 2000 01 02 03 04 05 06 07 08 09 2010 11 12 13 14
NDAs BLAs
Source: FDA
Year
Number of New Drug
and Biologics Approvals
Productivity as Measured by Annual Approvals
Overall Drug Development Durations(Cycle Time in Years from IND Filing to NDA Approval)
6.3 6.8 7.25.9 6.0 6.1 6.3 6.8 6.7
2.92.6 2
1.4 1.21.75 1.6
1.5 1.4
87-89 90-92 93-95 96-98 99-01 02-04 05-07 08-10 11-13
Mean Clinical Time Mean Approval Time
Source: Tufts, CSDD
10/22/2015
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Actual Study Enrollment Cycle Times
Multiplier of Planned Study
Duration to Reach Target
Enrollment
Overall 1.9
Cardiovascular 2.0
CNS 2.2
Endocrine/Metabolic 2.1
Oncology 1.7
Respiratory 1.9
Source: Tufts CSDD, 2012
* Does not include screen failure rates
$33.9
$54.6
$94.2
$127.4
$142.2
1995 2000 2005 2010 2015P
Source: EvaluatePharma
Total Global R&D Spending
CAGR
7.4%
$ US Billions
10/22/2015
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High and Rising Development Risk
21.3%
19.1%
16.4%
11.3%
1980s 1990s 2000s 2010s to date
Clinical Success Rates (IND Filing to Approval)
Source: Tufts CSDD, 2015
Capitalized Cost to Develop a Successful Drug
$179
$413
$1,044
$2,558
1970s 1980s 1990s 2000s
(US Millions in 2013 $s)
CAGR
9.3%
Source: Tufts CSDD, 2015
10/22/2015
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Cost per NME -- Total Annual Spend per Annual Approval
2.7
2.2 2.3
3.43.7
4.6
4.2
3.7
4.9
3.8 3.7
5.1
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
($US Billions)
Source: EvaluatePharma; PwC
10-Year Average -- $3.8 Billion/Drug
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Why is Performance Optimization So Elusive?
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Why is Performance Optimization So Elusive?
1. Protocol design complexity
2. Collaboration and Integration Inefficiencies
3. Regulatory burden
4. Poor public and patient engagement
Trends in Protocol Design Practices
Scientific Characteristics
A Typical Phase III Protocol 2002 2012
Total Number of Endpoints 7 13
Total Number of Procedures 106 167
Total Number of Eligibility Criteria 31 50
Average number of Major Amendments 2.3 3.6
Proportion of procedures that are ‘Non-Core’ 18% 31%
Source: Tufts CSDD ; (* Medidata Solutions)
10/22/2015
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Trends in Protocol Design Practices
Operating Characteristics
A Typical Phase III Protocol 2002 2012
Total Number of Countries 11 34
Total Number of Investigative sites 124 196
Total Number of Patients Randomized 729 597
Total number of data points collected* 494,236 929,203
Source: Tufts CSDD ; (* Medidata Solutions)
Impact of Complexity on Performance
(All TAs, Phases II-III) ‘High’ Complexity
Compared with ‘Low’
Complexity Protocols
Study volunteer screen to completion
rate
-50%
Time from Protocol Ready to FPFV
(median)
+12%
Time from Protocol Ready to LPLV
(median)
+73%
Source: Tufts CSDD16
10/22/2015
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Frequency of Amendments
Source: Tufts CSDD, 2010
2
2.6
3.6
2.3
Phase I Phase II Phase III Phase IIIb/IV
Mean Number of
Amendments per Protocol
Phase I
New and Modified Safety
Assessment
(15.4% of Total)
Phase IIChange in Eligibility Criteria
(17.2%)
Phase IIIChange in Eligibility Criteria
(15.2%)
Phase IIIb/IVChange in Eligibility Criteria
(17.9%)
Top Reasons for Amendments
The Cost of Implementing Protocol Amendments
43%
52%
37%
30%
38%
Overall Phase I Phase II Phase III Phase
IIIb/IV
Proportion Occurring Before
First Patient First Dose
Source: TCSDD 2010 analysis of 3,596 amendments
• Results in 2 months of
unplanned time and $497,500 in
unplanned direct costs to
implement
• 37% of all amendments are
deemed avoidable
– A significantly higher
percentage of avoidable
amendments observed
before FPFDose
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74.9
17.0
91.5
66.0
15.8
82.0
70.2
16.4
86.5
Clinical Phase* Approval Phase** Total Phase***
Mo
nth
s
Interrupted Uninterrupted All
* p=0.0131; ** p=0.4147; ***p=0.0116
The Impact of Collaboration and Risk-Sharing (2000-2011)
Source: Tufts CSDD 2013; N=289 drugs approved between 2000 – 2011
2011/12 Collaboration Assessments
• 22% of 89 sponsors had terminated
an integrated alliance
• 30% of 81 sponsors reported that
alliances were failing to deliver
expected cost and time savings
• 48% of 81 sponsors reported that
CROs can’t work collaboratively
– 60% of 57 CROs said the same
of their Sponsors 2%
45%
17%
70%
Very Satisfied Somewhat Satisfied
Satisfaction with
Relationship Quality and
Effectiveness
Sponsors CROs
Sources: Vantage Partners, Avoca, TCSDD
10/22/2015
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Growing Reliance on Outsourcing
$33.9
$54.6
$94.2
$127.4
$142.2
$3.8$10.4
$24.3
$43.1
$59.7
1995 2000 2005 2010 2015P
R&D Spend Spend on Contract Preclinical and Clinical Services
20-year
CAGR
7.4%
14.8%
Source: EvaluatePharma; William Blair & Wells Fargo Securities
$ US Billions
The Incidence of Change Orders
1.1
2.3
4.1
2.4
Phase I Phase II Phase III Phase IV
1.1
2.5
5.3
2.2
Phase I Phase II Phase III Phase IV
Integrated Alliances(Average Number per Study)
Transactional Relationships(Average Number per Study)
Source: Tufts CSDD, 2012; N =138 studies
10/22/2015
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Foundational Factors
Outsourcing Practice Culture
• Inconsistency
• Poor execution
• Legacy and New
Juggling Act
• Distrust
• Risk Aversion
• Commodity view of
External providers
• Protocol Complexity
• Poor Site
Management
• Poor Patient
Engagement
Barriers to Realizing Relationship Potential
Total Active Investigators World Wide
18,608
28,24629,883
34,959
39,791
1997 2001 2005 2009 2013
Unique 1572 filers
Source: Tufts CSDD analysis of FDA’s Bioresearch Monitoring Information System File (BMIS)
10/22/2015
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Site Enrollment Achievement
Fail to Enroll a Single
Patient
11%
Under EnrollUnder Enroll
37%37%Meet Enrollment Meet Enrollment
TargetsTargets
39%39%
Well Exceed
Enrollment Targets
13%
(N= 15,965 sites participating in 153 global phase II and III clinical trials)
Source: START Study Tufts CSDD-goBalto, 2012
Clinical Trial Process Inefficiencies
Phase II/III Programs Coefficient of Cycle
Time Variances
Study Design and Approval .8
Site Identification .9
Pre-Visit to Contract/Budget Sent to Site 1.1
Contract/Budget Sent to Site to Contract Execution 1.0
Contract Execution to Site Initiation 1.2
Site Initiation to FPI 1.4
LPLV to Data Lock .8
Source: Tufts CSDD, 2012
10/22/2015
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111
139
266
245
263254
278
2001 2003 2005 2007 2009 2011 2013
Complaints for Non-Compliance and Fraud
Source: FDA CDER Office of Compliance
Limited Connection and Relevance
27%
63%
10%
'Yes' 'No' 'Not Sure'
Percent ‘Somewhat’ and ‘Very’
Willing to Participate
Source: CISCRP 2013 N=5,701; Research!America, 2010; N=1,000 – 2,000 Adults;
87%93%
58%64%
73%
Overall North
America
Europe South
America
Asia
Pacific
Percent of the Public that
Can Name a Living Scientist
10/22/2015
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Who makes a greater contribution to human health?
Source: CISCRP 2013 N=5,701
46%
33%
12%9%
Organ Donor Blood Donor Financial Donor CT Volunteer
Little Recognition and Appreciation
Failure to Engage Health Providers
• 23% of volunteers report that they
learned about clinical trials from their
primary/specialty care physician (CISCRP,
2015)
– Greater disparities among minority
patients given low physician
involvement
• 60% of physicians report referring
patients into clinical trials with a typical
referral rate of <1% of community served (Tufts CSDD, 2015)
– 87% of physicians who have conducted clinical
research in the past report regularly referring
their patients
Medical
Doctors
Pharmacists Nurses Auto
mechanics
Perceived Honesty and Integrity
Source: Gallup Survey, 2010
Percent of Public
Rate Very High/High
26%
66%71%
81%
10/22/2015
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Paradigm Shift to Optimize Performance
‘Product-Centric’ ‘Patient-Centric’
Linear, Sequential Multi-directional, iterative
Compartmentalized Open
Insular Integrated
Centralized Ownership and Risk Shared Ownership and Risk
Rigid Flexible/Adaptive
Proprietary Clinical Data at the core Patient experience at the core
Focus on Great Science Focus on Great and Feasible Science
Participant as Subject Participant as Partner
(Key Characteristics)
Ernst & Young: Shift to Pharma 3.0
From
Pharma 2.0
To
Pharma 3.0
Business Model Product-Centric Consumer-Centric
Value Drivers Revenue, profitability Heath outcomes
Brand Value Product profile Consumer experience
Go-to-Market Strategy Pitching Listening and co-creating
Inorganic Growth M&A Innovative Partnerships
Innovation Spark Product differentiation Collaborative models
Information Assets IP and approval based
on clinical data
IP, approval and
reimbursement based on
real world evidence
Source: E&Y, 2013
10/22/2015
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Forming a New ‘Learning Health Care Ecosystem’
• Patient-empowered & centered drug
development and health care
• Democratization of health data and
information (EHR, mobile devices)
• Boundaries blurred between care
providers, payers, federal agencies and
research sponsors under integrated,
learning health systems
Engagement Objectives
1. Relevance
2. Feasibility
3. Convenience
4. Ownership
Parallel Developments
Regulatory Agencies
Quasi-Regulatory;
Public-Private
Clinical Research Conduct
• Individual company
initiatives; policies
and practices
• Service and
technology
solutions to
improve
convenience
• Engagement meetings
with select patient
communities to
define better
endpoints
• Guidelines on
‘acceptability’ and
‘use’
• CTTI; PCORI; MRCT;
IOM; TransCelerate;
NHC; EUPATI
• Frameworks
• Standard practices
and processes
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Proliferation of Piloted and Planned Initiatives
• Real world, pragmatic trials
• Home nursing networks
• Telemedicine
• Wearable ePRO devices
• E-Consent
• Integrated clinical & EHR data
• Lay-summary risk management
• Lay-summary clinical trial results
• Protocol feasibility review committees
• Patient advisory boards
• Professional panels
• Advocacy group involvement
• Open design and crowdsourcing
• Adaptive designs and licensing
• Real-time data collection
• Direct-to-patient clinical trials
The Value Proposition
of Patient Centered Drug Development
LevelLevel of Improvementof Improvement Cycle TimeCycle Time Success RateSuccess Rate
5% $102 million $153 million
10% $250 million $384 million
25% $390 million $486 million
Source: Tufts CSDD
Savings on Capitalized Costs in 2013 $s
10/22/2015
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Ken Getz, Director of Sponsored Research and Associate Professor
CSDD, Tufts University School of Medicine
617-636-3487
Q&A and Thank You!