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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
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
METRICS FOR EVALUATION OF
 REGULATORY 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
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.
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.
MERSI PRINCIPLES



Transparency Principle: One of the primary reasons
for controversies associated with regulatory science is
the assumption of regulators and regulatory scientists
that the public is incapable of comprehending the unique
structure of regulatory science. If a scientific issue is
complex, it is the responsibility of regulatory scientists to
explain the subject to the public in a language that is
understandable to its recipients.



                                                                6
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.
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.
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.
PILLAR: CLASSIFICATION OF
    SCIENTIFIC INFORMATION
Evolving 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.
PILLAR: CLASSIFICATION OF
    SCIENTIFIC INFORMATION
Evolving 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.
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.
PILLAR: RELIABILITY OF
     SCIENTIFIC INFORMATION
Independent 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
PILLAR: RELIABILITY OF
     SCIENTIFIC INFORMATION
Consensus 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
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.”
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.
REGULATORY SCINCE ETHICS

Principle 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.
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
EXAMPLES
•   NAPAP
•   The Stage of Reg. Sci. at the EPA
•   The stage of Reg. Sci. at the FDA
•   Response to questions from the audience

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Reg sci

  • 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 OF REGULATORY 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 PRINCIPLES Transparency Principle: One of the primary reasons for controversies associated with regulatory science is the assumption of regulators and regulatory scientists that the public is incapable of comprehending the unique structure of regulatory science. If a scientific issue is complex, it is the responsibility of regulatory scientists to explain the subject to the public in a language that is understandable 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 INFORMATION Evolving 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 INFORMATION Evolving 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 INFORMATION Independent 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 INFORMATION Consensus 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 ETHICS Principle 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