new insights on optimizing protocol design …...new insights on optimizing protocol design practice...
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New Insights on Optimizing Protocol Design Practice
to Maximize Development Performance
Presentation by Ken GetzSponsored by intilaris LifeSciences
March 23, 2017
intilaris Life Sciences – Our Mission
Focus on productivity improvements and process optimizationfor Clinical Development.
Provides full consulting services and technology enabling clients to optimize their clinical study design process.
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To improve productivity in Clinical Development.
www.intilaris.com I [email protected] I Basel: +41 61 633 2212 I New York: +1 (646) 849-1440
New Insights on Optimizing Protocol Design
Practice to Maximize Development Performance
Ken Getz, MBADirector of Sponsored Programs, Research Associate Professor
Tufts CSDD, Tufts University School of Medicine
March 2017
Drawn from a Decade of TCSDD Studies
• Assessing the Impact of Protocol Design Change on Clinical Trial Performance. American Journal of Therapeutics 2008 15(5); 450 – 457.
• Variability in Protocol Design Complexity by Phase and Therapeutic Area. DIJ 2011 45(4); 413-420.
• Measuring the Incidence, Causes and Repercussions of Protocol Amendments. DIJ 2011 45(3); 265 – 275.
• Quantifying the Magnitude and Cost of Collecting Extraneous Protocol Data. American Journal of Therapeutics 2013; March.
• New Governance Mechanisms to Optimize Protocol Design. Therapeutic Innovation and Regulatory Science,July 2013.
• Therapeutic Area Variability in the Collection of Data Supporting Protocol Endpoints and Objectives. Future Science Clinical Investigations 2014 4(2); 125–130.
• The Impact of Protocol Amendments on Clinical Trial Performance and Cost. TIRS 2016; 50:4; 436-442.
Primary Methodology Used
• Working group studies
• Consensus definitions of variables
• All data provided by sponsor companies
• All coding and categorizations conducted by sponsors’ own clinical teams and protocol authors
• Typical study has 16 – 20 sponsor companies and analyzes 8,000 – 10,000 protocols and/or 4,500 – 7,000 protocol amendments
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Agenda
• Key Takeaway Concepts
• Characterize Protocol Design Practices
• Quantify the Impact of these Practices on Clinical Trial Performance
• Optimization Opportunities
Key Takeaway Concepts
• Are you saying that protocol complexity is bad?
• Are regulatory agencies to blame for rising complexity?
• Tell us what specific procedures to remove?
• Why does Tufts CSDD believe that clinical trials are a waste of money?
• Protocol amendments improve study design; why do you recommend avoiding them?
10-Year Change in Protocol Design Practices
(Means) A Typical Phase III Protocol 2001 - 2005 2011-2015
Total Number of Endpoints 7 13
Total Number of Eligibility Criteria 31 50
Total Number of Procedures 110 187
Total Number of Procedures per visit 10 13
Proportion of Procedures that are ‘Non Core’ 18% 31%
Total number of data points collected* 494,236 929,203
Source: Tufts CSDD ; *Medidata Solutions
Endpoint Creep
1 1
3 4
3
8
2005 2015
Endpoint Type
Supporting, Tertiary, Exploratory
Key Secondary
Primary
Drivers of Scope Changes
• Scientific Context
• Statistical Context
• Habit and Operating Policy
• Risk Management
• Newer areas (e.g., outcomes;
economic assessment; comparative effectiveness; companion diagnostics; biomarker data)
Source: Tufts CSDD
Distinct and Total Procedures per Protocol
(means) 2005 2015 Change
Distinct Procedures
Phase I 25 36 44%
Phase II 24 37 54%
Phase III 22 35 59%
Phase IV 18 19 6%
Total Procedures
Phase I 165 253 53%
Phase II 131 219 67%
Phase III 110 187 70%
Phase IV 66 69 5%
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Source: Tufts CSDD
Protocol Administration Changes
37
31
62
50
Phase II Phase III
Work Effort to Administer Protocol
2005 2015
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Work EffortUnits
Nominal US Dollars
$862
$728
$1,386
$978
Phase II Phase III
2005 2015
Direct Procedure Costs per Patient per Visit
Other Operating Complexity Measures
(Medians)2001 - 2005 2011-2015
Number of Countries
Phase II 2 3
Phase III 5 10
Number of Investigative Sites
Phase II 21 30
Phase III 40 65
Number of Study Volunteers
Phase II 104 88
Phase III 368 302
Source: Tufts CSDD
Agenda
• Key Concepts
• Characterize Protocol Design Practices
• Quantify the Impact of these Practices on Clinical Trial Performance
• Optimization Opportunities
Impact on Recruitment & Retention
Source: Tufts CSDD, 2013
‘High’ vs. ‘Low’ Complexity Protocols
Study volunteer screen to completion rate
-53% lower
Time from Protocol Ready to FPFV (median)
+12% longer
Time from Protocol Ready to LPLV (median)
+73% longer
• More complex study designs are associated with lower levels of physician participation and referral rates (Ross et al. 2004)
• High study volunteer drop out rates are associated with complex protocol designs (Andersen et al., 2009)
Recruitment Timelines and Achievement Rates
Source: Tufts CSDD, 2013
Doubling Planned Timelines
Fail to Enroll a Single
Patient11%
Under Enroll37%
Meet Enrollment
Targets39%
Well Exceed
Enrollment Targets
13%
Enrollment Achievement Rates
1.9
Increase in Planned Study Duration to
Reach Target Enrollment
Overall 94%
Cardiovascular 99%
CNS 116%
Endocrine/Metabolic 113%
Oncology 71%
Respiratory 95%
Participation Burden and Missed Engagement
What did you least like about your participation experience?
(Top 5 mentions)
Percent of Total
Not knowing whether I was getting the investigational treatment
30%
Location of the research center 22%
Study visits were too time consuming
19%
Compensation was not enough given the demands of the study
16%
Study procedures were too cumbersome
15%
14%9% 7%
Disclosure that Ireceived the
investigationaldrug or a
comparison
A summary of mystudy results
News aboutwhether my
investigationaldrug was approved
Source: CISCRP, 2015: N= 2,849 Patients Who Completed Participation
What information did you receive after completing your study?
111
139
266
245
263254
278269
2001 2003 2005 2007 2009 2011 2013 2015
Complaints for Site Non-Compliance and Fraud
Source: FDA CDER Office of Compliance
Frequency of Protocol Amendments
Source: Tufts CSDD, 2015
1.8
2.22.3
1.9
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 Reason for Amending
The Cost of Implementing Amendments
43%
52%
37%
30%
38%
Overall Phase I Phase II Phase III PhaseIIIb/IV
Proportion Occurring Before First Patient First Dose
Source: TCSDD,2016
Implementation Cost:
On average three additional months of
unplanned time and $141,000 and
$535,000 in unbudgeted direct costs
per phase II and III protocols
respectively
Optimization Opportunities
• Creating ‘Line of Sight’ via protocol authoring tools
– SPIRIT, TransCelerate Common Protocol Template
– Reducing number of ‘Non-Core’ procedures
– Avoiding select protocol amendments
• Soliciting input into pre-approved protocol designs
– Feasibility Review Committees
– Patient and Site Advisory Boards
• Planning for pre-approved design changes
• Gathering strategic input based on published decisions from health care payers and providers
Distribution of Procedures by Endpoint Type
(Means) Phase II Phase III
Proportion of Total Procedures that are ‘Core’
64.9% 58.6%
Proportion of Total Procedures that are ‘Standard’
9.7% 7.1%
Proportion of Total Procedures that are ‘Required’ (Includes informed consent)
4.6% 3.7%
Proportion of Total Procedures that are ‘Non-Core’
20.7% 30.6%
Source: Tufts CSDD 2014; N= 25,287 procedures from 137 protocols
Distribution of Direct Procedure Costs
Core 48%
Required 19%
Standard 10%
Non-Core 23%
Distribution of Study Budget Direct Costs by Procedure Classification
• Direct cost to administer procedures only
• Wide variability by therapeutic area
• $4-$6 billion annual spend on all active phase II & III global clinical trials to administer non-core procedures
Source: Tufts CSDD 2014; N= 25,287 procedures from 137 protocols
Targeting Avoidable Amendments
Percentage of Total
Amendments
Cause Categories
Completely Avoidable 23%• Protocol design Flaw• Inconsistency and/or Error in the Protocol
Somewhat Avoidable 22%• Recruitment Difficulty• Investigator/Site Feedback
Somewhat Not Avoidable 30%• New Data Available (other than safety data)• Change in strategy/objective• Change in Standard of Care
Completely Not Avoidable 25% • New Safety Information Available• Regulatory Agency Request to Amend• Manufacturing Change
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Source: Tufts CSDD, 2015
Feasibility Review Committees
‘Modest’ to ‘Major’ Improvement observed in: Percent of Companies
Number of amendments 67.5%
Investigative site work burden 53.3%
Overall study cycle time 44.3%
Speed to Last Patient Last Visit 43.6%
Study budgets 42.0%
Source: Tufts CSDD 2014; N= 63 companies
Patient Engagement Initiatives
33%
40%
57%
Lack Funding
Lack Internal Expertiseand Processes
Internal Resistance
Top Perceived Barriers to Adoption(Percent of Total)
77%
70%
47%
40%37%
PatientAdvisoryBoards
ProfessionalAdvisory
Panels
CT ResultsSummaries
HomeNursing
Networks
WearableDevices
Percent of Total Companies Reporting
Source: Tufts CSDD 2016; N= 30 companies; CenterWatch 2016 N=95 companies
Adoption Rates of Simple Adaptive Designs(e.g., early termination due to futility; blinded SSRs)
22%20%
DIA Working Group 2011 Tufts CSDD 2012
Expected Increase in Complexity
• Growing focus on rare and specialty diseases
• Rising interest in precision and stratified therapies
• Growing incidence of co-therapies and companion diagnostics
• Increasing pressures to gather more data – structured and unstructured -- to measure clinically meaningful benefit and differentiate and position drug product
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Key Takeaway Concepts
MITIGATION AND MANAGEMENT MINDSET– Are you saying that protocol complexity is bad?
MANY BEHAVIORS AND PRACTICES TO OPTIMIZE– Are regulatory agencies to blame for rising complexity?
CLEAR OPPORTUNITIES TO TARGET– Tell us what specific procedures to remove?
– Why does Tufts CSDD believe that clinical trials are a waste of money?
– Protocol amendments improve study design; why do you recommend avoiding them?
Ken Getz
Director, Sponsored Research Programs, Associate Professor
Tufts CSDD, Tufts University School of Medicine
617-636-3487, [email protected]
Recap – Questions You May Wish to Consider
30 www.intilaris.com I [email protected] I Basel: +41 61 633 2212 I New York: +1 (646) 849-1440
▪ End Point Creep & Explosion in number of data points▪ Greatest growth is in “supporting, tertiary, exploratory” endpoints;▪ 50% are not meeting enrollment targets▪ Frequency of amendments▪ Drivers that lead to increased complexity continue to grow▪ …
How are you planning to manage these issues and others that Ken raised?
intilaris LifeSciences can help.Contact intilaris for strategic clinical project planning: • Consulting, • Support Services, • Technology
Q&Aintilaris LifeSciences
www.intilaris.com
Basel: +41 61 633 2212
New York: +1 (646) 849-1440