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Scientific Data for EvidenceBased Drug Regulation
Janet Woodcock, M.D.
Director, Center for Drug Evaluation and Research
Food and Drug Administration
September 24, 2009
Agenda
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Background
Scientific data in regulations, policy
standards, and guidance
Scientific data in decision-making
Generating new scientific data
Improving transparency
Background
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Pharmaceuticals are among the most
tightly regulated products in the U.S.
Manufacturing, human investigations,
market access, label claims, advertising
and promotion all regulated by the FDA
Regulation based on scientific standards to
the extent possible
Drug regulation has always been
controversial
Background (cont.)
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Many pharmaceutical standards are
harmonized internationally
It is very difficult for FDA regulations,
guidance, and policy to keep pace with
scientific innovation
There is also much remaining uncertainty
in the biological and social sciences
Scientific Data in Regulations
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Rulemaking process
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Currently can take 8 years at FDA
Avoid using specific numbers in regulation (i.e., limits) if
possible (specify in guidance)
Science informs approach
Example
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Pregnancy Labeling Rule (proposed)
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Data:
Animal toxicology
Pharmacologic data
Human exposure
Communications Science Data
How to relay sensible information to clinicians and pregnant
women on risks and benefits of using a drug?
Scientific Data in Policy Decisions
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How to approach the CFC withdrawal,
mandated by the Montreal Protocol, for
asthma inhalers?
How do deal with stearate in drug
products in the face of BSE?
If there is a shortage of a medically
necessary drug, how to decide if
unapproved drugs are OK?
Scientific Data in Standards
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Many FDA standards are technical
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FDA will often defer to SDO’s that establish technical standards
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Many scientific standards for drugs established internationally through
the International Conference on Harmonization of Technical
Requirements for Pharmaceuticals (ICH)
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Toxicology testing
Manufacturing standards
Clinical procedures such as Good Clinical Practices
NOT approval standards
FDA will go through Good Guidance Practice Procedures to establish
these ICH standards in the U.S.
Scientific Data in Guidance
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“Good Guidance Practices”
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Started by FDA
Involves dissemination of draft, public comment,
potentially workshops and public meetings, final
guidance
Large number of science-based guidances
Not binding on outside parties or FDA:
represent FDA’s best scientific judgment
Regulation, Policy, Standard
and Guidance Development
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Transparent, data-driven processes
Generally involve extensive input from
the affected communities, including the
scientific experts
Frequently involves public workshops
and scientific meetings
Used as basis for decisions on specific
product applications
Scientific Data in Decision-Making
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Individual applications are reviewed against
scientific standards
Massive amounts of scientific data often
evaluated-generated and submitted by
industry
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Investigational drug applications: 10,000
New drug applications: 140
Abbreviated new drug applications: 800
Manufacturing data: 5,000 submissions
Scientific Data in Decision
Making
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140 New Drug Applications (NDAs)
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Estimate that each NDA contains an
average of 10GB of data
FDA scientists review these data against
the established regulations, policies,
standards and guidance (guidance not
binding)
Reviewers document whether the data
meet the FDA standards in each area
Example: Animal Toxicology
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For an average, chronically dosed oral
medication that is a new molecular
entity, there may be 12 formal
toxicology studies performed (all
specified internationally), each of which
may be preceded by an informal dose
ranging study
Most of these will be submitted during
the IND phase of development
Example: Generic Drugs
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800 new applications per year
Contain scientific data (per standards)
on manufacturing, stability, impurities,
and, if parenteral, microbiology
For “pills”, will have both fed and
fasting bioequivalence studies that have
to pass limits established in regulations,
using studies specified in guidances
Scientific Data in Decision-Making
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Standards for Drug Labels (package insert)
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Each label statement must be backed up by
scientific data
Data reviewed by FDA staff to ensure label
accuracy
Standards for Drug Advertising
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Claims must be supported by data
Enforcement against transgressions – going
beyond the data
New Scientific Data
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There are huge knowledge gaps
throughout drug regulation
Poor translation of basic science into
actionable regulatory science
Lack of understanding/data on real
world outcomes of using drugs
Lack of application of known
communication science to drug labeling,
promotion and advertising
Translation of Basic Science
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FDA Critical Path Initiative seeks to
bridge gaps between basic science and
drug developmental science
Use of public-private partnerships to fill
gaps
Multiple successful partnerships ongoing
Put all results into public domain
Example: Predictive
Biomarkers in Toxicology
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Multiple drug companies had
biomarkers for drug induced kidney
toxicity
Consortium sponsored by C-Path
Institute brought 16 companies
together to share knowledge
Resulted in acceptance of new renal
biomarkers by FDA and EMEA
Now starting human testing
New Scientific Knowledge
about Drug Use Outcomes
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FDA carrying out the Sentinel Initiative
Use eHRs and other electronic health
data (e.g., claims) to form a distributed
network to do analyses about drug use
outcomes
Pilot starting this year
Will be a powerful source of new data:
intend to use public-private
partnerships
Improving Transparency
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Broad availability for scrutiny, analysis,
and replication of results is a hallmark
of good science
Transparency of drug regulatory
process has improved, but still needs to
be improved:
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Transparency of decision-making process
Transparency of basis (scientific data) for
decisions
Particular Challenges
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Animal toxicology and human data
considered commercial confidential and
not releasable
These data could be invaluable in
advancing the science of toxicology and
of human clinical trials (and drug
development)
Arguably, all human data should be
made publicly available in some form
Particular Challenges
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Not all FDA drug reviews are made
available in a timely manner
FDA lacks the staff to perform the
needed redaction of trade
secret/commercial confidential data
FDA releases adverse event reporting
data on a quarterly basis (receives
about 250,000 important reports
annually)
Transparency
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More needs to be done on data
availability and transparency
FDA has data that might be invaluable
in advancing human health if it were
available to researchers
Resource and legal barriers exist
Summary
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Drug regulation in the United States is a
extensively scientific data-driven
process, from the development of
standards to the review of applications
against the standards
Many of these scientific standards are
internationally accepted
More needs to be done on data access
and transparency