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

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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

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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

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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

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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.

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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

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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

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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

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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

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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

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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