Scientific Data for Evidence-Based Drug

Regulation

Janet Woodcock, M.D.Director, Center for Drug Evaluation and

ResearchFood and Drug Administration

September 24, 2009

Agenda

Background Scientific data in regulations,

policy standards, and guidance Scientific data in decision-making Generating new scientific data Improving transparency

Background 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.)

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

Rulemaking process 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 Pregnancy Labeling Rule (proposed)

Data: Animal toxicologyPharmacologic dataHuman exposureCommunications 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

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

Many FDA standards are technical

FDA will often defer to SDO’s that establish technical standards

Many scientific standards for drugs established internationally through the International Conference on Harmonization of Technical Requirements for Pharmaceuticals (ICH)

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 “Good Guidance Practices”

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

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

Individual applications are reviewed against scientific standards

Massive amounts of scientific data often evaluated-generated and submitted by industry Investigational drug applications: 10,000 New drug applications: 140 Abbreviated new drug applications: 800 Manufacturing data: 5,000 submissions

Scientific Data in Decision Making

140 New Drug Applications (NDAs) 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

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

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

Standards for Drug Labels (package insert) Each label statement must be backed up by

scientific data Data reviewed by FDA staff to ensure label

accuracy

Standards for Drug Advertising Claims must be supported by data Enforcement against transgressions – going

beyond the data

New Scientific Data 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

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 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 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

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: Transparency of decision-making process Transparency of basis (scientific data) for

decisions

Particular Challenges 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 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

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 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