Regulatory Science Jan 8 Cafe Scientifique

  • 379 views
Uploaded on

Regulatory Science : Uniqueness - Processes - Apllication A. Alan Moghissi, PhD …

Regulatory Science : Uniqueness - Processes - Apllication A. Alan Moghissi, PhD
provides insight on how regulatory policy decisions could be made
Jan 8 Cafe Scientifique - Arlington

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
379
On Slideshare
0
From Embeds
0
Number of Embeds
1

Actions

Shares
Downloads
0
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. REGULATORY SCIENCE• UNIQUNESS • PROCESSES • APPLICATIION A. Alan Moghissi PhD Institute for Regulatory Science Potomac Institute for Policy Studies George Mason University moghissi@nars.org 1
  • 2. What is Regulatory Science?• There are many individuals who have claimed that regulatory science is not science. Regulatory science is being contrasted with research science, academic • science, and many other similar terms.• REGULATORY SCIENCE CONSISTS OF SCIENTIFIC FOUNDATION OF POLICY NOTABLY REGULATORY DECISIONS• Included is scientific foundation of legislative and judicial decisions.• Decisions based on uncertain SI is common 2
  • 3. METRICS FOR EVALUATION OFREGULATORY SCIENCE INFORMATION• The process started at ~ 1978 by the development of the concept of Best Available Science (BAS); Metrics for Evaluation of Scientific Claims were derived from BAS leading to MERSI.• Betty R. Love, Sorin R. Straja, Dennis K. McBride and Michael S. Swetnam are contributors to both BAS/MESC and MERSI 3
  • 4. MERSI PRINCIPLES• OPEN-MINDEDNESS PRINCIPLE Implies that the scientific community must be open-minded• SKEPTICISM PRINCIPLE requires that those who make a claim must provide evidence supporting the claim• REPRODUCIBILITY PRINCIPLE Implies that a claim is proven if anyone with the necessary competency and tools can reproduce it.
  • 5. MERSI PRINCIPLES• Universal Scientific Principles: All scientific disciplines use certain methods, processes, and techniques in pursuit of their professional activities. Also scientific laws apply not only to a specific discipline but to all scientific disciplines. E.g. all scientific disciplines use specific computational methods and apply the rules of statistics in sampling, analysis, and reporting their results.
  • 6. MERSI PRINCIPLESTransparency Principle: One of the primary reasonsfor controversies associated with regulatory science isthe assumption of regulators and regulatory scientiststhat the public is incapable of comprehending the uniquestructure of regulatory science. If a scientific issue iscomplex, it is the responsibility of regulatory scientists toexplain the subject to the public in a language that isunderstandable to its recipients. 6
  • 7. PILLAR: CLASSIFICATION OF SCIENTIFIC INFORMATION• One of the primary reasons for the uniqueness of regulatory science is the need to consider the level of maturity of a regulatory science claim.• Science evolves and new discoveries, advancement of scientific knowledge, and numerous technologies result from the evolution of science.• Therefore, it is necessary to classify scientific information (SI) in terms of its level of maturity and its reproducibility.
  • 8. PILLAR: CLASSIFICATION OF SCIENTIFIC INFORMATION• Proven SI• This class consists of scientific laws— sometimes called scientific principles—and their applications. The cornerstone of this class is compliance with Reproducibility Principle implying that any investigator who has the proper equipment and the necessary skills can reproduce it. Therefore, this class of SI does not require assumptions or any other conditions for its validity. This class also includes those applied sciences that are entirely based on scientific laws and that exclude assumptions.
  • 9. PILLAR: CLASSIFICATION OF SCIENTIFIC INFORMATION Evolving SI• The overwhelming scientific advances in virtually all disciplines are Evolving SI. Virtually all regulatory science information is included in this class.• Reproducible Evolving SI: Reliable information dealing with a subject that is not completely understood constitutes the core of this class. This class of scientific information is based on two attributes:• This SI class complies with Reproducibility Principle implying it is clearly and unambiguously reproducible by those with appropriate skills and equipment.• The scientific claim does not violate USP.
  • 10. PILLAR: CLASSIFICATION OF SCIENTIFIC INFORMATIONEvolving Science• Partially Reproducible Evolving SI: Sometimes called Rationalized Science, or Extrapolated Science, the key characteristic of this class is that the scientific foundation of information placed in this class is derived from Proven Science or Reproducible Evolving Science but it uses assumptions, extrapolations, default data, and other processes in deriving its results and conclusions.• This class includes a large number of SI used in regulatory science. Whereas some of the regulatory information placed in this category relies heavily upon proven or Reproducible Evolving SI, others do less or much less.
  • 11. PILLAR: CLASSIFICATION OF SCIENTIFIC INFORMATIONEvolving Science• Association-Based Evolving SI: Sometimes called correlation or observation studies, the information in this class is not based on Proven SI or Reproducible Evolving SI.• Hypothesized SI: This class consists of an organized response to an observation, an idea, etc.• SI-Based Judgment: This class consists of decisions without having the needed SI including basic principles, the necessary data, and other scientific requirements.• Speculation: This class consists of information that cannot meet standards described in any of the above classes.
  • 12. PILLAR: RELIABILITY OF SCIENTIFIC INFORMATION• Personal Opinions:• Expression of views by individuals regardless of their training, experience, and social agenda, are included in this group. In a free society, every individual has the right to state an opinion regardless of the reliability of SI.• Gray Literature• This category consists of written information prepared by government agencies, advocacy groups, and others that has not been subjected to an independent peer review. This is the favorite category of those who want to promote an idea.
  • 13. PILLAR: RELIABILITY OF SCIENTIFIC INFORMATIONIndependent Peer Review/Scientific Assessment• Whereas Peer Review evaluates an exiting document Scientific Assessment prepares a document.• Scientific Assessment is common in regulatory science• In both cases: – Qualification of the Reviewers – Their Independency ( Lack of Conflict of Interest) – Review Criteria – Oversight of the Process
  • 14. PILLAR: RELIABILITY OF SCIENTIFIC INFORMATIONConsensus Processed SI• This category consists of SI intended to resolve scientific disputes and is particularly useful in regulatory science as, in most cases, regulatory science information is at best Partially Reproducible Evolving SI and includes assumptions, judgments, default data, and related areas.• The process used for this category is identical to that used for Independent Peer review
  • 15. PILLAR: OUTSIDE THE PURVIEW OF SCIENCE• The inclusion of ideology, societal objectives, policy, beliefs, faith, or any other non-scientific objective in assessing the validity of SI in Outside the Purview of Science . The scientific foundation of a policy is identical if it is performed, let us say, in the U.S., Russia, China, Saudi Arabia, Brazil or Cuba. In contrast, the conclusions derived from science can be significantly different in countries identified above.• According to Ruckelshaus Effect “… all scientists should make it clear when they are speaking as scientists— ex cathedra—and when they are recommending policy they believe should flow from scientific information.”
  • 16. Assessment of Predictive Models• Applied science: Models that are entirely based on Proven Science or Reproducible Evolving science are applied science.• Primary Predictive Models: The foundation of a large number of models used in Regulatory science Proven Science or Reproducible Evolving Science, they also use assumptions, judgments, and other tools to develop or apply the model.• Secondary Models: These models use primary models as their foundation. They are likely to be Scientific Judgment.• Tertiary and Lower Models: These models use secondary models as their foundation. These models are at best Speculation or more likely Fallacious Information.
  • 17. REGULATORY SCINCE ETHICSPrinciple I: A scientific issue is settled when anyone with the necessary scientific skills, required equipment, and facilities can reproduce it.Principle II: Those who prepare a regulatory science document must provide to the affected community assumptions, judgments, and similar parts in a language understandable to a knowledgeable non- specialist.Principle III: Regulatory science information must exclude societal objectives thus violating the MERSI Pillar “Areas outside the Purview of Science”.Principle IV: Regulatory science information is only then acceptable if it has been subjected to independent peer review and the review criteria include compliance with principles I, II, and III of regulatory science ethics.
  • 18. EVOLUTION OF REG. SCI. AT US AGENCIES• Initial Phase: The agency is given deadlines without having the needed SI• Exploratory Phase: The agency attempts to develop the process to live within the requirements of MERSI• Standard Operation: The agency operates in accordance with requirements of MERSI
  • 19. EXAMPLES• NAPAP• The Stage of Reg. Sci. at the EPA• The stage of Reg. Sci. at the FDA• Response to questions from the audience