Transcript Today's biomedical innovation: lost in translation

Today’s Biomedical Innovation:
“Lost in Translation”?
Janet Woodcock, MD
Director, Center for Drug Evaluation and Research
Food and Drug Administration
QB3 Entrepreneurs’ Discussion
University of California, San Francisco
Thursday, April 26, 2012
Will New Scientific
Discoveries Revolutionize
Treatment of Disease
(Soon)?
• Advances in both science and technology are providing
unprecedented opportunities for new approaches to disease
prevention, diagnosis and treatment
• However, in some senses, the barriers to successful
development have never been higher
• New paradigms for evaluation of diagnostic and therapeutic
interventions must be developed
– Faster
– More efficient
– But equally or more informative
2
Drug Development
• Currently takes more than 10 years and requires an
investment of over $1B to bring a single innovative
drug to market
• Clinical investigation, premarket application, and
postmarket stages are heavily regulated in most
developed countries
• Ongoing concern about ability of the drug
development enterprise to translate innovative
science and bring needed therapies to market
• Ongoing concern about the ability, and willingness,
of societies to pay for novel therapies
3
Research and Development Process
ONE
FDAAPPROVED
DRUG
5
PHASE 1
PHASE 2
PHASE 3
Number of Volunteers
20-100
LARGE
SCALE
MFG
100-500
1000-5000
6-7 YEARS
SOURCE: PhRMA 2008, Stages of Drug Development Process and attrition rate of compounds
as they travel through the drug development process over time.
0.5-2
YEARS
PHASE 4: POST MARKETING SURVEILLANCE
250
3-6 YEARS
FDA
REVIEW
CLINICAL TRIALS
NDA SUBMITTED TO FDA
5,000-10,000
COMPOUNDS
PRE
CLINICAL
IND SUBMITTED TO FDA
PRE-DISCOVERY
DRUG
DISCOVERY
4
For 12 PhRMA companies
Research Spending vs New Drugs Approved
during the Period 1997-2011
$120,000
25
Total R&D Spending
$108,178
Number of Drugs Approved
21
20
$88,285
$85,841
$83,646
$81,708
$80,000
16
$67,360
15
$63,274
15
14
$57,955
$60,000
11
$50,347
11
11
$45,675
10
$40,000
10
9
$35,9708
8
$33,229
5
Number of Drugs Approved
Total R&D Investment (in $Millions)
$100,000
5
$20,000
$-
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Source: InnoThink Center for Research in Biomedical Innovation; Thomson Reuters Fundamentals via FactSet Research Systems
5
Private & Public
Research and Development Spending
$80
$70
Total NIH Budget
$67.4
$65.3
PhRMA Member Companies' R&D Expenditures
Total R&D Investment (in $Billions)
$60
$63.2
$63.7
$47.9
$47.4
Entire Pharma Sector
$56.1
$51.8
$50
$47.6
$49.4
$45.8
$43.4
$40
$39.9
$37.0
$34.5
$30
$29.8
$31.0
$27.1
$26.0
$21.0
$20
$10
$11.3
$29.0
$29.3
$30.6
$31.0
$20.5
$17.8
$16.9
$11.9
$28.5
$23.3
$22.7
$19.0
$15.2
$27.9
$28.5
$15.6
$12.7
$13.7
$0
1995
1996
1997
1998
1999
2000
2001
Source: Burrill & Company, PhRMA, NIH Office of Budget
2002
2003
2004
2005
2006
2007
2008
2009
2010
Year
6
FDA NME Approvals
• Basically stable output over long term (vs increased
investment in basic research and R&D)
• Decline from late 1990s reflects primarily decrease in
submission of “me-too” drugs: now difficult to get on
formulary
• FDA seeing increased novelty in applications over recent 5
year period; more “game-changing” therapies
• Possibly reflects adjustment of industry strategies
• PDUFA program (currently up for re-authorization) ensures
that review times are relatively predicatable
7
In 2011, CDER approved 30 NMEs,
the highest total of NMEs approved in
seven years
*The final number of NME Applications filed in 2011 is projected, pending final validation of
the data and dependent outcome of 12 applications submitted in late 2011.
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CDER met review goal dates
for 97% of the new molecular entities
approved in 2011
Met PDUFA Target Dates
1.
2.
3.
4.
5.
6.
Adcetris
Arcapta
Benlysta
Brilinta
Caprelsa
Darilesp
Datscan
8. Dificid
9. Edarbi
10. Edurant
11. Eylea
12. Ferriprox
7.
Firazyr
14. Gadavist
15. Horizant
16. Incivek
17. Jakafi
18. Natroba
19.
Gadavist
10. Incivek
11. Jakafi
12. Onfi
13.
13.
Nulojix
20. Onfi
21. Potiga
22. Tradjenta
23. Victrelis
24. Viibryd
25.
Xalkori
26. Xarelto
Tradjenta
14. Victrelis
15. Viibryd
16. Xalkori
17.
27. Yervoy
Zelboraf
29. Zytiga
28.
First Cycle Approval
1.
2.
3.
4.
Adcetris
Benlysta
Caprelsa
Dificid
5.
6.
7.
8.
Edarbi
Edurant
Erwinaze
Eylea
9.
Yervoy
18. Zelboraf
19. Zytiga
9
Innovation in drug approvals for 2011
First in-Class Drugs
1.
2.
3.
Adcetris
Benlysta
Darilesp
4.
5.
6.
Firazyr
Jakafi
Nulojix
7.
8.
9.
Potiga
Victrelis
Xalkori
Yervoy
11. Zelboraf
12. Zytiga
10.
Approved First in the U.S.
1.
2.
3.
4.
Adcetris
Benlysta
Caprelsa
Dificid
5.
6.
7.
8.
Edarbi
Edurant
Eylea
Incivek
Horizant
10. Jakafi
11. Natroba
12. Nulojix
9.
Tradjenta
14. Victrelis
15. Viibryd
16. Xalkori
13.
Yervoy
18. Zelboraf
19. Zytiga
17.
Orphan Drug Approvals
1.
2.
3.
Adcetris
Caprelsa
Erwinaze
4.
5.
6.
Ferriprox
Firazyr
Jakafi
7.
8.
9.
Nulojix
Onfi
Xalkori
Yervoy
11. Zelboraf
10.
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Role of Regulatory Standards
• Certainly some of the costs are driven by increased
expectations—over the last several decades--about
evaluating the performance of the drug (both for safety and
efficacy) before it goes on the market
• Even after an expenditure of $1B per successful drug, multiple
important clinical questions remain unanswered (e.g. dose
and regimen, use with other therapies, optimal duration of
therapy, consequences of long-term use)
• Academic clinical community constantly clamors for more
data to be generated premarket and postmarket
• Payer community has rising expectations—e.g., Europe
11
Key Issues
• How to balance information needs of prescribers, patients
and payers against desire for speedy access to better
therapies (more effective, less toxic etc.) on the part of
prescribers and patients?
• How to keep the biomedical innovation sector alive with a
viable business model, but also keep new innovations
affordable for society?
• How to translate the vast amount of new knowledge about
human health and disease efficiently, rather than using the
time-consuming, costly and inefficient methods currently in
place?
• Is there a more prominent role for the academic biomedical
sector?
12
Can the Academic Biomedical Sector
Become a more Integral Part of the
Drug
Development
Ecosystem?
Background: A Very Long
Time Ago
• Professors were engaged in drug discovery
(and experimented upon themselves and their
grad students)
• Industry commercialized discoveries
• Industry largely unregulated
14
Background: 1950-60s
• Growth of mainstream (and other) pharmaceutical
houses
• 1000’s of unstudied, possibly ineffective drugs on
the market
• Start of a long period of seminal drug discoveries:
cardiovascular disease; infectious disease; cancer;
psychiatric disorders
• Beginning of the requirement to show drug efficacy
(1962)
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“Modern Era”
• Huge pharmaceutical companies: massive “fully
integrated” drug discovery and development
enterprises
• Academic focus on molecular biology of health and
disease: “basic biomedical science”
• Outpouring of novel therapies and also x’s in a
class (e.g., 17 NSAIDS)
• Society increasingly less impressed with novelty
– Decreased tolerance of uncertainty
– Regulators respond with more testing
requirements
– Cost effectiveness questions arise
16
Now
• Pharmaceutical industry: progressively greater
investment and diminished return
• Biotech: success, but can society afford the
products?
• Venture capital: fleeing medical products sector
• Academia: 30 year investment in biomedical
research sector—will funding keep rising? What is
the academic role in translational research?
• Regulators blamed for:
– Current problems in drug development
– Excess conservatism
– Excess enthusiasm
17
Current Government and Industry Roles in
Pharmaceutical Research & Development
18
Future: Opportunities for
New Roles and Relationships
to Improve Process
• Pharmaceutical Sector Competencies
–
–
–
–
–
–
–
Rigor
Medicinal chemistry
High throughput screening
Lead optimization
Manufacturing and scale up
Late phase development
Marketing and distribution
19
Future: Potential Shift in
Roles?
• Academic Strengths
– Molecular biology of target; pathways;
pathogenesis
– Animals and in vitro models and testing scenarios;
in depth disease understanding
– Relationships with relevant patients
– Proximity of patients and laboratory
20
Future Role of Academia in Drug
Discovery and Development
• Partnering with industry in discovery and translation
of specific products or therapeutic areas
• Research leading to new evaluative tools for
predicting, understanding and assessing the effects
of medical products in the relevant species (people)
• Hubs for clinical trial networks that incorporate
community practitioners and also have the capacity
for integration of sophisticated bench science
21
Role of Academia: Urgent
Need for New Evaluative
Tools
• Drug manufacturing and scale up
– Multiple academic consortia working on this; poorly funded
• Safety evaluation: little changed in decades
– Traditional empirical evaluation in animals
– Human safety evaluation a “side effect” of efficacy evaluation
• Efficacy evaluation: Predicting and confirming efficacy
still a huge challenge; generally still empirical
– Affects academic efforts as well as industrial
– Many late failures due to efficacy problems
22
Discovery and Translation of
Specific Innovations
• “Academic based drug development”
• Thousands of less common disorders that are not
subject to industrial development
• Specific pathways or mechanisms that have been the
subject of extensive research in a particular
laboratory
• Early bench to bedside translation
– Proof of concept studies
– Pharmacodynamic evaluations
23
Streamlining the Bench to
Bedside Transition
• “Exploratory IND” guidance
– Tailor required toxicology studies to proposed
investigations
– Can be significantly reduced for single dose or microdose
trials, or brief administration
• Phase 1 trial cGMPs
– Remove phase 1 clinical trial material from extensive
cGMP requirements in regulations
– These were written for commercial products
– Companion guidance: ability to use laboratory produced
material with specific safeguards
24
Development of Evaluative Tools:
A Tremendously Neglected Area
•Better science is needed to both predict and assess
safety and efficacy of investigational products
•Now: “Build an airplane and then see if it can fly”
•Major causes of failure in Phase 3 clinical
development
– Lack of effectiveness against placebo or active
– Unexpected drug toxicity
– Commercial non-viability (not better than existing therapy)
25
Evaluative Tools
• Current drug development might be viewed as what physics
would be without engineering
• Large amount of biochemical knowledge but few ways to
assess state of whole organism and impact of interventions at
the organism level
• Most assessment tools are not standardized so limited ability
to compare one experiment to another
• Little insight into sources of variability of treatment response,
even current therapies
• As a result, most clinical development programs are “brute
force” empirical efforts: extremely costly and time-consuming
26
Safety Evaluation: Opportunities
• Routine rat or dog studies good for predicting safe
first-in-human dose but not for understanding less
common toxicities
• Structure Activity Relationships
– FDA has collaborated to make some screening programs
available that correlate computer readable structural
motifs with known animal or clinical adverse outcomes
from FDA databases
– Opportunities to link structure with other assays that are
becoming available and also do more extensive link to
clinical data
27
Safety Evaluation: Opportunities
• Systems biology approach to drug toxicity
• Screens for off-target receptor binding
• Gene expression in response to drug exposure:
safety pharmacogenomics
• Cellular systems for assessing drug responses
broadly
• Human pharmacogenomics: not just drug
metabolism
– Allelic variability in drug target
– Uncommon alleles increasing risk of major drug toxicity
28
Development of Biomarkers for
Prediction of Safety or Efficacy
• Many potential biomarkers discovered in academic
laboratories but never understood sufficiently for:
– Use in drug development
– Regulatory decision making
• FDA attempting to introduce more rigorous process as part of
“Critical Path Initiative”
• FDA Guidance on “Drug Development Tools” qualification
process: US and EU will work with groups on qualifying new
tools for use in drug development
• A central role for academic scientists
29
Predicting, Measuring, and
Improving Efficacy
• New endpoints
• New trial designs
• Use of biomarkers to subset disease ( prognostic or
response predictors)
– Jupitor trial (C-reactive protein; rosuvastatin)
– Screening tumors for activating pathways
– Known as “enrichment”, CDER guidance
• Use of patient-reported outcomes
• Conducting natural history studies to understand
disease course—particularly in rare diseases
30
New Endpoints
Foundation for the National Institutes of Health (FNIH)
• Scientific work on endpoints and clinical trial designs
– FNIH and the Biomarkers Consortium are developing
endpoints for clinical trials in skin infections and community
acquired pneumonia
– Helps reduce uncertainty around using a new endpoint or
trial design
– Includes academia, industry, IDSA, NIH, and FDA
31
New Endpoints in Pain Trials
Why ACTION?
Clinical studies, particularly efficacy trials, notoriously flawed
for analgesic drug development
• Frequent failed studies with drugs known to be effective
• Extremely small treatment effects even when successful
• Multiple causes, e.g.:
Large placebo effect
Missing data
Study design flaws
Study analysis flaws
Investigator quality
Frequent use of foreign sites
32
New Endpoints
Innovative clinical trial design to facilitate
schizophrenia drug development…
• FDA and National Institute of Mental Health (NIMH)
• “MATRICS” clinical trial guidelines designed to facilitate novel
compound development to treat cognitive impairment from
schizophrenia (MATRICS) clinical trial guidelines for cognitiveenhancing drugs in schizophrenia
33
Developing New Biomarkers
and Patient Reported
Outcomes Measures (PROs)
• C-Path Institute (nonprofit): submitted new
biomarkers for drug induced kidney injury (data
produced by a consortium); FDA and EMA accepted;
undergoing clinical evaluation
• PROMIS (NIH PRO effort)
• C-Path Institute: PROs for specific diseases for
qualification
34
Quantitative Disease-Drug-Trial Models
Diverse
Expertise
FDA Data
Disease
Model
Biology
Natural Progression
Placebo
Biomarker-Outcome
Physiology
Drug
Model
Pharmacology
Effectiveness
Safety
Early-Late
Trial
Model
Patient Population
Drop-out
Compliance
Preclinical-Healthy-Patient
Disease-drug-trial models are mathematical representations of the time course of
biomarker-clinical outcomes, placebo effects, drug’s pharmacologic effects and trial execution
characteristics for both the desired and undesired responses, and across experiments.
35
Quantitative Disease-Trial Models:
Alzheimer Disease
Diverse
Expertise
FDA Data
Disease
Model
Natural Progression
Placebo Response
Physiology
Trial
Model
Patient Population
Drop-out
36
Adaptive Design with
Biomarkers
I-Spy 2: screening trial for investigational breast
cancer drugs
• Biomarker Consortium--- public/private partnership: FDA /
NIH / PhRMA companies
• Attempts to identify biomarker-defined response subgroups
• Adaptive design against standard-of-care
• Ability to screen multiple investigational agents in one trial
• Selected compounds could have rapid route to accelerated
approval based on larger trial in responsive subgroup
37
Re-engineering the Clinical
Research Enterprise
• Currently, clinical research is:
–
–
–
–
–
Extremely expensive
Unpleasant for most participants
Inefficient
Not totally reliable
Unavailable for the vast majority of patients (e.g., cancer patients)
38
Clinical Research in Drug
Development
•
•
•
•
Unique clinical trial at multiple stages of development
New investigators, support personnel, unique CRFs
Long lead time to set up
Frequently slow recruitment, many sites fail to recruit
adequately
• Lack of involvement of community practitioners, so that
available universe of patient limited, often sites are
competing for patients for several protocols
• Rapid movement of clinical trials in drug development
overseas
39
How to Address Problem?
• Consider clinical trial networks with the capacity to perform
multiple trials
• Include community practitioners with appropriate logistical
support
• Academic medical centers as hubs
• Standardized CRF templates for much of data collection
• Ultimately improve quality of data, involve community in
clinical research
40
The Clinical Trials Transformation
Initiative (CTTI)
• Formed in 2008
• FDA and Duke University - founding
members of a public-private
partnership
• Members include stakeholders from
government, industry, academia,
patient and consumer
representatives, clinical
investigators, professional societies,
and clinical research organizations
41
CTTI Current Projects
•
•
Improving the public
interface for use of aggregate
data in clinicaltrials.Gov
Investigator
Site metrics for study start up
•
Building quality in
•
Use of central IRB for
multicenter clinical trials
IND Safety
Reporting
Sponsor
Patient
42
Summary
• There are major problems with current drug
development paradigms
• New scientific knowledge provides huge opportunity
for improvement
• The biomedical research community should have a
greater role in many aspects of drug discovery and
development
• Future drug development must include many
innovative partnerships
• The clinical research enterprise in the US must be
transformed
43