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Transforming ORA’s Operations and Organization and Advancing Product
Quality
Douglas Stearn Director
Office of Enforcement and Import Operations Food and Drug Administration
FDA Inspections Summit
Bethesda, MD November 6, 2015
ORA’s Transformation
FDA/ORA’s Drivers of Change
Program Alignment
Implementing Legislation and Center Initiatives
ORA’s Strategic Priorities
Program Alignment - Commitments
1. Establish Commodity-Based and Vertically Integrated Regulatory Programs
2. Increase Specialization
3. Enhance Training
4. Revamp Agency Work Planning
5. Improve Compliance Policy and Enforcement Strategies
6. Enhance Import Operations
7. Advance Lab Optimization
8. Address Delayering/Streamlining
ORA Organizational Chart - Current ACRA
Deputy ACRA &
Partnerships & Policy
IT Staff
Communication, Quality Systems Management &
Project Management
Executive Secretariat
Office of Partnerships
Office of Policy
Assistant Commissioner for Operations
Human & Animal Food Operations
Office of Enforcement & Import Operations
Medical Products &
Tobacco Operations
Office of Regulatory Science
Audit Staff Northeast
Region
Central Region Southeast
Region
Southwest Region
Pacific Region
Office of Criminal Investigations Office of Resource Management
ORA Operations - Current Structure Operations
Central Region
Baltimore District
Cincinnati District
Chicago District
Detroit District
Minneapolis District
New Jersey District
Philadelphia District
Detroit Laboratory
Forensic Chemistry Center
Philadelphia Laboratory
Northeast Region
New England District
New York District
Northeast Regional Laboratory
Winchester Engineering Analytical Center
Southeast Region
Atlanta District
Florida District
New Orleans District
San Juan District
San Juan Laboratory
Southeast Regional
Laboratory
Southwest Region
Dallas District
Denver District
Kansas District
Southwest Imports District
Arkansas Regional Laboratory
Denver Laboratory
Kansas Laboratory
Pacific Region
Los Angeles District
San Francisco District
Seattle District
Pacific Regional Laboratory Northwest
Pacific Regional Laboratory Southwest
San Francisco Laboratory
Human & Animal Food Operations
Medical Products & Tobacco Operations
Enforcement & Import Operations
Regulatory Science
Audit Staff
ORA Operations - Future Structure
Operations
Pharmaceutical Quality Operations
Director, Alonza Cruse
Four Management
Teams
Biologics Operations
Director, Anne Reid Acting
Two Management
Teams
Medical Devices Operations
Director, Jan Welch
Three Management
Teams
BIMO Operations
Two Management
Teams
Tobacco Operations
Human and Animal Food Operations
Director, Joann Givens
12 Management Teams
Audit Staff
What does this mean for me?
Inspectorate specialized by program
Expanded technical expertise
Increased ability to keep pace with changes in manufacturing
Goal of reduced timeframes for decision-making through both streamlining as well as team-based approaches
Quality Focus for FDA
Principles for change
More clear standards for review and inspection
More clear enforcement policies
Same standards for all drugs: lifecycle approach
Specialization and team review: integration of review and inspection for a quality assessment
Clinically relevant standards
Surveillance using quantitative metrics
Overall QMS and evaluation system
FDASIA-User Fees
The first 4 titles relate to user fees:
Gives FDA authority to collect user fees from industry
Steady & reliable income to bring new products to market safely & quickly
Prescription Drug User Fee Amendments (PDUFA)
Medical Device User Fee Amendments (MDUFA)
Generic Drug User Fee Amendments (GDUFA)
Biosimilar Products User Fee Amendments (BsUFA)
Quality Focus for Industry
Commitment to quality
Essential… from the top down and bottom up
Cannot settle on “meeting regulators standards”
Must meet YOUR standards to reliably produce high quality products
Elements
proactively identify & promptly correct issues
design/qualify robust operations
maintain equipment and facilities
Implement robust quality management systems
Significant impacts to the public’s health
Cost of poor quality – $$$$$$$$$$$$$
Cost to patients – shortages, adverse events, etc.
How mature is your quality system? Level 1: Small problems ultimately
snowball into larger ones, and
management becomes aware only when
there is a crisis.
Level 2: Nearly always reactive, but there
is willingness to change. Patchwork
corrections are the norm.
Level 3: More proactive. Increasingly
surfaces major issues and makes lasting
systemic improvements.
Level 4: Routinely acts preventively, and
institutionalizes (rewards) meaningful
process and system improvements.
1
2
3
4
Data Integrity
Data Integrity
Reliable for its purpose: meeting standards to assure complete, consistent, and accurate data
Examples
What of state of mind?
Easier to emerge than you might think . . .
Not necessarily criminal
Not necessarily involving many people
Not necessarily easy to detect
The trinity: rationalization, justification, and denial
Why Data Integrity Matters
Oversight in this area is foundational
Lack of data integrity in one area raises questions about other data and records
Inability to rely upon data raises questions about the ability to assure safety and efficacy
Internal Oversight
A quality system should
prevent errors and defects
assure ongoing state of control
facilitate vigilance, timely action, and early warning of emerging quality issues
Data integrity breaches undermine these abilities
External Oversight
Regulators rely on firm data in
Inspections
Reviewing firm correspondence
Application review
Data integrity breaches undermine these reviews
Antecedents
The Generic Drug Scandal
Numerous prosecutions
Legislation and policy approaches
Prosecutorial approaches
Looking at data integrity with CGMP
Application integrity policy
Debarment
Data Integrity Issues Today and Tomorrow
Prosecution
Criminal objectives: deterrence and retribution
Common statutory approaches
Title 18
False statements within FDA jurisdiction
Obstruction of agency proceeding
Mail and wire fraud
FDCA felonies: “intent to defraud or mislead” extends to FDA
Difficulties of Overseas Prosecutions
Subpoena power in investigations
Cooperation of foreign authorities
Compulsory power at trial
Evidentiary Issues
Jurisdictional Issues
Extradition
The offense (FDASIA 718 (extraterritoriality))
Collateral Consequences
Debarment
Stems from conviction
Clear focus on development work in ANDAs
Applies more broadly as well
Prevents services to applicants
Medicare exclusion and corporate integrity agreements
CGMP Issues
Multiple provisions incorporate data collection and recordkeeping
Process leads to inaccurate or unreliable data
Renders product adulterated
Generally deemed material
Harder to investigate and to remedy
Warning letters and enforcement actions
Application Issues
Implicit requirement of reliability
Not necessarily found fraudulent
Not necessarily found inaccurate
FDA can reject data
Application integrity policy – a subset
Applies to review (rather than rejection)
Applies to a pattern by applicant
Preventing and Limiting Problems
Culture should reinforce rigor of procedures and unacceptability of short cuts
Accountability in systems and procedures
Management knows who did what when
Accountability in electronic data is key
Data should be attributable, legible, contemporaneously recorded, original or a true copy, and accurate (ALCOA)
Remediation – Step One
A comprehensive evaluation of data integrity deficiencies generally would include
The extent of the inaccuracy of any reported data
Plan to investigate deficient practices
Examination of management involvement, procedures, and contract agreements
FDA expects detailed, thorough plans addressing people and systems
Remediation – Step Two
A risk assessment of potential effect on drug product quality
Issues
Affected products in marketplace
Potential impact on patients
Nature of preventative controls
Remediation – Step Three
A management strategy that includes CAPA
Potential issues: customer contacts, recalls, revising procedures, implementing new controls, training, etc.
Expectation will be for increased accountability and preventative systems in future
Inspection
A focus on implementation of corrective actions
Mismatch may show problems are not fully addressed
Closing Thoughts
Potentially high stakes consequences
Not always easy to see
Difficult to remediate
Better safe than sorry: controls can prevent and limit data integrity breaches