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Science Board FDA’s New Bioresearch Monitoring Initiative. Dr. Janet Woodcock Deputy Commissioner for Operations Food and Drug Administration November 4, 2005. “BiMo” = Bioresearch Monitoring Program. - PowerPoint PPT Presentation
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Science Board FDA’s New Bioresearch Monitoring
Initiative
Dr. Janet WoodcockDeputy Commissioner for OperationsFood and Drug AdministrationNovember 4, 2005
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“BiMo” = Bioresearch Monitoring Program
Cross-cutting Agency program — all centers, Office of Regulatory Affairs, Office of the Chief Counsel, Office of the Commissioner
– Standard-setting– Inspections– Review and compliance/enforcement with good laboratory
practices (GLP) standards in animal safety studies– Good clinical practices (GCP) standards in human trials of
FDA-regulated products Human subject protection (HSP) closely associated
with BiMo, accomplishes IRB inspections and sets standards
3
Objectives of BiMo Program
Protect human subjects in trials of FDA-regulated products
Ensure high-quality and integrity of data used to:– Support marketing applications– Support regulatory decision making– Provide evidence base for clinical use of
regulated products
4
Status of FDA’s New BiMo Initiative
Begun December 2004 Steering committee charter approved by FDA
Management Council Currently scoping out dimensions of issues Part of FDA’s Critical Path Initiative
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BiMo Initiative — Cross Cutting
Co-Chairs: Janet Woodcock M.D. and David LePay M.D.
Scientific Lead: Rachel Behrman, M.D.Project Manager: Terrie Crescenzi
Representatives from all centers and relevant offices
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BiMo Program Is Very Important Proper conduct of trials to ensure human safety Trust and confidence in animal safety studies, clinical
research, and product development process depend on the integrity of process and supporting data
Regulatory program provides assurance of integrity but can inhibit innovation — ideally will be facilitative
Regulatory program must modernize as practices change
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Evolution of Clinical Trial Practices During Last Few Decades
New trial methods and designs New methods of data collection and processing
(e.g., electronic data capture) New arrangements between sponsors and various
contractors, among investigators, among institutions, among IRBs, and rise of free-standing for-profit study centers
Great number of studies in children and other vulnerable populations
Approaches to studies using existing human specimens
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Evolution of Clinical Trial Practices
Delegation to parties not directly regulated by the FDA
Larger trials where contribution of single site may be small, but where study-wide systems of data control and management may be very significant
Centralized and/or for-profit IRBs Increased globalization Increase in implanted/complex medical device trials
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Does FDA’s Current Regulatory Program Fit Today’s Realities?
Must facilitate effective IRB oversight of evolving clinical trials arena to facilitate
– IRB oversight of human subject protection – FDA oversight of IRB function
Must provide regulatory guidance and perhaps new regulatory scheme that encompasses modern trial arrangements and participants/contractors
Need common standards and regulatory requirements for electronic data handling — both domestic and international
10
Does Regulatory Program Fit Realities? (cont.)
Must be able to accommodate globalization of clinical trials
Must ensure comprehensive approach to protection of vulnerable populations
Need to provide additional guidance to all parties regarding various procedures and special circumstances
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Internal Challenges for BiMo/HSP Program
Highly decentralized function – Units of varying size in review centers– Field force — only a few experts in any given
district– Very small centralized group in OC
Non-automated environment Relative lack of guidance and standards
12
Additional Challenges: Multiplicity of Stakeholders
Patients and doctors Investigators/clinical research community Data managers Industry sponsors FDA review staff Compliance/enforcement staff HHS and other government agencies/depts.
13
Issues in Human Subject Protection
IRB System– Must modernize adverse event reporting to IRBs to
accommodate major trend toward multicenter trials (Held Part 15 Hearing last summer)
– Use of central IRBs — issued draft guidance Using a Centralized IRB Process, final guidance in clearance
14
Issues in Human Subject Protection (cont.)
Proposed rule: Institutional Review Board — Registration Requirements, published (with OHRP), FDA reviewing comments
FDA finalizing interim rule: 21 CFR 50.54 Subpart D — Additional Safeguards for Children in Clinical Investigations of FDA Regulated Products
Other rules and guidances in preparation
15
Issues in Human Subject Protection (cont.)
Risk-based approach optimization– Real-time inspection vs. retrospective– Risk-based algorithm for targeting inspections– Better technology approaches for tracking
compliance
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Current Issues in Clinical Trials Area — Regulations
Finalizing rule: Foreign Clinical Studies not Conducted Under an IND (21 CFR 312.120
Will propose rule on reporting information related to falsification of clinical data
Developing revised rules on treatment use and charging under an IND
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Current Issues in Clinical Trials Area — Guidance
Guidance on use of data monitoring committees
Guidances on conduct of clinical trials Reviewing comments on guidance
Computerized Systems Used in Clinical Trials
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Current Issues In Clinical TrialsArea — Data Quality
Need – Common definition of data quality– Methods to assess– Assessment of current system for data quality– Continuous improvement
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A Shared Goal — High-Quality Clinical Trial Data
Support integrity of clinical research enterprise
Support confidence of public/patients in human studies
Provide evidentiary base for product approvals and medical practices
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Clinical Trial Data Quality — A Shared Responsibility
Investigator/site Sponsor FDA ?Academia; journal editors
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Investigator/Site Responsibilities
Embodied in GCPs Accurate protocol compliance, observations,
timing, and data entry Importance of study personnel ? Patient adherence
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Sponsor Responsibilities
Clear and achievable study plans and protocols
Investigator and site training Monitoring and auditing “Data clean up”
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FDA Responsibilities
Regulatory oversight of trial protocols and adverse events
Site inspections: “Bioresearch monitoring” Review of data: paper-based or electronic data audit Guidance: Framework for best practices and
compliance with regulations Enforcement: sanctions against sloppy performers or
fraud
24
Additional System-Wide Issues — Automation and Standardization
Computer program validation and integrity (FDA Part 11, etc.)
Data and format standardization– Standard format CRF (case report form)– Standardized terminologies– Standardization is best tool for decreasing
variation
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Definition of High-Quality Data?
100 % Accurate Fit for use Meets protocol — specified parameters Arbitrary “acceptable levels of variation” per
explicit protocol specification?
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Definition of High-Quality Data — Considerations
Allow risk management approach Probability the “x” level of variation could
affect conclusions/sensitivity analysis Are all questions equally important? (Concomitant meds)
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General Definition of Quality
Meets needs of customer– Sponsor– Regulator– Ultimately, patient and provider
What, exactly, are customer’s needs? How to actually assess quality?
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Frequent Operational Definition of Quality
Control variability Acceptable variability differs by use/customer (specification) ? Trade offs among efficiency, productivity,
and control of variability Need tools to assess and quantify
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Generally — Quality is a System Property
Difficult to inspect “quality in” — i.e., monitoring, auditing
Need to build “quality in” (e.g., analogous to quality in other industries)
How to obtain within the healthcare system What combination of FDA programs — education,
guidance, collaboration, inspection, enforcement — will achieve the best results?
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FDA Role in Overall System for Data Quality
Oversee whole enterprise — ensure that the system is working
Evaluate level of data quality problems across all studies/development programs
Not able to directly oversee each study — use risk management approach
– High risk (experience, country, complexity, sponsor-investigator) Quality assurance, not quality control
31
Are There Opportunities for Improvement in Current System?
Large number of resources expended on ensuring data quality
Overall system has not been explicitly examined
FDA currently evaluating; will need to include many others in process
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Probable Opportunities
Automation, e.g. linked networks (e.g. CA BIG project)
Standardization Establish common definitions of data quality Systems-based approach at FDA
33
BiMo Initiative Work Plan
Continue to gather information from internal and external stakeholder groups
Identify short-term deliverables and complete (e.g. guidances)
Define desired states and develop longer term plan for achievement
Conduct workshops and create other opportunities for public input