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FDA Regulatory Perspective: Data Integrity
Steve Wilson, Dr.P.H., CAPT USPHSDeputy Director, Division of Biometrics II, CDER/FDA
NIH Roadmap ProgramFeasibility of Integrating & Expanding Clinical Research
Networks 4th Steering Committee Meeting
Friday, May 12, 2006NIH Natcher Conference Center, Bethesda, MD
FDA’s Mission• The FDA is responsible for protecting the public
health by assuring the safety, efficacy, and security of human and veterinary drugs, biological products, medical devices, our nation’s food supply, cosmetics, and products that emit radiation.
• The FDA is also responsible for advancing the public health by helping to speed innovations that make medicines and foods more effective, safer, and more affordable; and helping the public get the accurate, science-based information they need to use medicines and foods to improve their health.
Data Integrity• The quality of correctness, completeness,
wholeness, soundness and compliance with the intention of the creators of the data.
• It is achieved by preventing accidental or deliberate but unauthorized insertion, modification or destruction of data in a database.
• Data integrity is one of the six fundamental components of information security.
http://www.pcmag.com/encyclopedia_term/0,2542,t=data+integrity&i=40792,00.asp
Data Integrity• 21 CFR 11 ( In final rule “integrity”
is used 50 times!)• Electronic Submission• Gateway• EDR SOPs
21 CFR 11 -- IntegrityFor electronic records and submissions to have the
same integrity as paper records, they must be developed, maintained, and used under circumstances that make it difficult for them to be inappropriately modified. Without these assurances, FDA’s objective of enabling electronic records and signatures to have standing equal to paper records and handwritten signatures, and to satisfy the requirements of existing statutes and regulations, cannot be met.
Data QualityData are of high quality "if they are fit
for their intended uses in operations, decision making and planning” (J.M. Juran)
http://en.wikipedia.org/wiki/Data_quality
FDA Regulatory Perspective: Data Quality
Steve Wilson, Dr.P.H., CAPT USPHSDeputy Director, Division of Biometrics II, CDER/FDA
NIH Roadmap ProgramFeasibility of Integrating & Expanding Clinical Research
Networks 4th Steering Committee Meeting
Friday, May 12, 2006NIH Natcher Conference Center, Bethesda, MD
DisclaimerViews expressed in this
presentation are those of the speaker and not, necessarily, of the Food and Drug Administration
• Center for Biologics Evaluation and Research (CBER) • Center for Devices and Radiological Health (CDRH) • Center for Drug Evaluation and Research (CDER) • Center for Food Safety and Applied Nutrition (CFSAN) • Center for Veterinary Medicine (CVM) • National Center for Toxicological Research (NCTR)• Office of the Commissioner (OC)• Office of Regulatory Affairs (ORA)
Organization: FDA
Outline• Background• Data Quality
– A Bimo perspective– A Review perspective
• Changing Landscape– The Critical Path – Data standards & electronic submissions– PRO and ePRO– Organizational Changes
• Bimo Initiative• CDER’s new Office of Translational Science
(OTS)• Connections/References
Science, Statistics and Science, Statistics and Experimental DesignExperimental Design
• Science is concerned with understanding variability in nature
• Statistics is concerned with making decisions about nature in the presence of variability
• Experimental design is concerned with reducing and controlling variability in ways which make statistical theory applicable to decisions about nature.
Winer, et.al., Statistical Principles in Experimental Design, New York, 1962, 1971, 1991
Data Quality• Guidance for Industry: Computerized
Systems Used in Clinical Trials, April 1999
• Data should be (ALCOA)– attributable – legible– contemporaneous– original – accurate
Responsibility• The sponsor is responsible for
implementing and maintaining quality assurance and quality control systems with written SOP’s to ensure that trials are conducted and data are generated...
• ... Quality control should be applied to each stage of data handling to ensure that all data are reliable and have been processed correctly…
Section 5.1, “Quality Assurance and Quality Control,” Good Clinical Practice Consolidated Guideline -- ICH E6
The LawSection 505(k)(2) of the Food, Drug, and
Cosmetic Act mandates FDA shall have access to and copy and verify the required clinical
study records.
The ProgramThe Bioresearch Monitoring (BIMO) Program
was established in 1977 to verify the data submitted in support of marketing applications
and to provide oversight of the conduct of studies with regulated products.
Ketek – The “Fraud” Word Infected Data
– Fraud, Errors Taint Key Study of Widely Used Sanofi Drug
– Despite Some Faked Results, FDA Approves Antibiotic; One Doctor's Cocaine Use
– Company Defends Safety
By ANNA WILDE MATHEWS Wall Street Journal, May 1, 2006; Page A1
online.wsj.com/article_print/SB114644463095840108.htm
Our Responsibility for the Our Responsibility for the Quality of Clinical Trials Data Quality of Clinical Trials Data
Trust, but Verify
Worrying About Data Quality: NDA Review
• Erroneous values• Missing values• Imputation• Adjudication• Deviations from protocol• “Unconscious Bias” • Fraud
Data Integrity/Quality A BIMO Perspective
• FDA calls its program of on-site inspections for GCP and GLP its “Bioresearch Monitoring Program” or “BIMO”
• The program includes inspections of:– Clinical Investigators– Sponsors, monitors, CROs– Institutional Review Boards– Bioequivalence Laboratories and Facilities– GLP Facilities (nonclinical studies)
• Each Center has its own BIMO groupWoollen, 2002
DSI’s Program Responsibilities
• Good Laboratory Practices • In vivo Bioequivalence • Good Clinical Practices
– Institutional Review Boards (IRBs)– Clinical Investigators– Sponsor-Monitors, CROs
Program Objectives• To verify the quality and integrity
of bioresearch data• To protect the rights and welfare
of human research subjects
GCP Inspections:Routine vs. Directed
• Routine– Inspections assigned for NDA/PMA’s
• Directed– Problems identified at IND/IDE stage– Complaints to FDA
• FDA, other Agencies• Sponsors/monitors• Institutions/IRB’s• Subjects/Public
CDER-GCP Bioresearch Monitoring (BIMO) Program
• Clinical Investigator Inspection Program• Sponsor/Monitor/CRO Inspection Program• IRB/RDRCThese “on-site” inspection programs collectively allow
the agency to determine:– Adherence to applicable FDA regulations– Validity of data from studies in support of pending
marketing applications (Data Integrity)– Whether the rights and safety of subjects have been
protected (Safety)
J. Rhoads, 2005
CDER BIMO Inspections (FY 2004)
CI = 351BEQ=
136IRB = 120GLP = 68S-M = 17
Total = 692
J. Rhoads, 2005
When a Submission is Received:
• Review Division Invites DSI staff for filing meeting• Team effort in selecting sites for inspection based
on “risk based approach”– Impact to review of the study
• Site(s) influencing significance on outcome • Outliers, e.g., site with large proportion of treatment
responders• Drop-outs; Adverse events; Protocol violations; large
N#– Impact to the clinical trial process
• Volume of work performed by the Clinical Investigator• Past inspectional history
• Inspection request assignment to the field offices (ORA)
• PDUFA Time Clock! J. Rhoads, 2005
Criteria for Assigning International Inspections
International sites may be audited• if there are insufficient domestic data;• only foreign data are submitted to support
an application;• domestic and foreign data show conflicting
results pertinent to decision-making; or• there is a serious issue to resolve, e.g.,
suspicion of fraud, scientific misconduct, significant human subject protection violations.
J. Rhoads, 2005
After an Inspection• Form FDA 483: Inspectional Observations
– Left with CI at close of inspection– Immediately available via FOI
• Establishment Inspection Report (EIR)– Prepared by field investigator after
inspection– Includes exhibits supporting observed
deficiencies
J. Rhoads, 2005
After an Inspection• Clinical Inspection Summary to the
Review Division– Summary of all inspections assigned for an
application– Recommend accept or reject data– Provided to review division in advance of
PDUFA action goal date• Letter to the inspected party
– emphasize deviation from regulations, if any.– Copied to the review division– include “DSI note to Review Div. Medical
Officer”J. Rhoads, 2005
Regulatory/Administrative Follow-up
• Rejection of study
• Disqualification• Prosecution
J. Rhoads, 2005
Clinical Investigator Deficiencies
CDER Inspections - FY 2004
0%
10%
20%
30%
40%
50%
60%
NAI Protocol Record Consent DrugAcct
AEs
ForeignDomestic
34%28%
55%
29%
48%
7%
21%
5%
Foreign n = 71*Domestic n = 243*
2%
17%
4%10%
*% does not includeBiologic inspectionsJ. Rhoads, 2005
Some GCP Challenges and Initiatives
• Increased international inspections• Risk-based approach to inspection
site selection • Accountability of study staff/site
management organizations in clinical research
• Linked real-time inspections (CI/Sponsor/IRB)
J. Rhoads, 2005
NDA/BLA Review: MedicalNDA/BLA Review: Medical• Exclusion of patients from primary analyses• Reliance on unplanned subset analyses• Lack of consistency of results within and across
studies• Patient entry errors (cancelled patients, ineligible
patients)• Non-evaluable patients• Missing data• Inconsistent or clearly inaccurate data• Extensive or non-random corrections to case report
forms• Missing source documents• Possibility for bias in patient treatment or patient
assessments• ……
Robert DeLap,Robert DeLap, PhRMA Meetings, PhRMA Meetings, Washington DC, October 26, 1994Washington DC, October 26, 1994
NDA/BLA Review: NDA/BLA Review: StatisticalStatistical• Assess compliance with protocol / blinded analysis
plans• Assist DSI in planning investigator audits• Check appropriateness of statistical models and
conclusions. • Verify results reported in the NDA.• Modify models and assess robustness/sensitivity of
the results. • Modify data sets and reanalyze.• Examine the trial and data for bias:
– Results by center – Baseline predictors– Important subgroups (sex, age, race, etc,)
• Assess impact of audits
The reduction in sudden deaths, said the FDA, had been exaggerated. Some patients who died according to Dr. Robert Temple Director of FDA’s Cardio-Renal Drug Products Division, had been excluded for “minor protocol violations”; and most of the excluded patients turned out to have been taking anturane … Nearly all the miss-classifications turned out to favor the hypothesis that anturane prevents sudden deaths.
“Unconscious Bias” and Readjudication
Lancet, August 9, 1980, p. 306
Case Study #1
“Unconscious Bias” and Readjudication
The reason for these doubts is that Ciba Geigy, which had a stake in the outcome, not only paid the bills (around four million dollars) but also was deeply involved in the daily processing and collection of data before turning over the information to an independent policy committee.”
Lancet, August 9, 1980, p. 306
Case Study #1
Analyzing Potential FraudTreatment-by-Center Interaction: p = 0.056
CENTER
Mea
n C
hang
e fro
m B
asel
ine
1 2 3 4 5 6 7 8 9
-3
-2
-1
0
1
2
Drug X
Placebo12 10 19 1 7 19 5 17 1
7 5 9 0 4 10 3 9 0
?
Case Study #2
Analyzing Potential Fraud (con.)
Sym
pB
SympC
0 1 2 3
0 68 4 0 01 17 4 0 02 16 21 2 03 1 0 0 0
Total: 133
Center 1
SympC0 1 2 3
0 33 2 0 01 3 33 0 02 5 4 63 23 0 0 1 31
Total:177
Sym
pB
Center 8
Case Study #2
Analyzing Potential FraudSymptom Score
0
20
40
60
80
100
1 2 3 4 5 6 7 8 9
Center
Perc
ent o
f Val
ues
NoneMildModerateSevere
Case Study #2
Halcion: For-Cause AuditCase Study #3
From the Summary Basis for ApprovalFrom the Summary Basis for Approval
Protocol 6045 (investigators: Franklin, Howard, Reeves, Protocol 6045 (investigators: Franklin, Howard, Reeves, Simson): 129 insomniacs (aged 22-62 years) participated in Simson): 129 insomniacs (aged 22-62 years) participated in four double-blind 28-day studies comparing triazolam four double-blind 28-day studies comparing triazolam 0.5mg to placebo; Franklin and Reeves enrolled 78% of the 0.5mg to placebo; Franklin and Reeves enrolled 78% of the patients. Pooled data showed triazolam was significantly patients. Pooled data showed triazolam was significantly better than placebo at end of week 1 on efficacy better than placebo at end of week 1 on efficacy measures…measures…
Drowziness, dizziness, and impaired coordination were Drowziness, dizziness, and impaired coordination were significant side effects; 13/61 patients in drug group who significant side effects; 13/61 patients in drug group who dropped out due to side effects, 10/13 dropped out in the dropped out due to side effects, 10/13 dropped out in the first week; no abnormal changes in clinical significance first week; no abnormal changes in clinical significance were observed in lab analyses or vital signs.were observed in lab analyses or vital signs.
Halcion: For-Cause AuditEfficacy Analysis (Protocol 6045)Efficacy Analysis (Protocol 6045)
Investigator 8 Days 15 Days 28 Days
Franklin 0.0001 0.0001 0.0001Reeves 0.001 0.99 0.48Howard 0.6 0.45 0.45Simson 0.04 0.62 0.99
TOTAL 0.0001 0.0001 0.0001(-Franklin) 0.0001 0.34 0.11
Case Study #3
Fraud: Robert Fiddes “If ever there was a wonder boy in the lucrative
business of drug testing, it was Dr. Robert Fiddes. In just a few years, Fiddes transformed his sleepy
medical practice ... into a research juggernaut, recruiting his patients for drug experiments at a breakneck pace. His success made him a magnet for an industry desperately scouring the nation for test subjects. Companies large and small showered him not only with almost 200 studies to conduct, but with millions of dollars in compensation for his work.”
Case Study #3
Kurt Eichenwald and Gina Kolata“A Doctor's Drug Studies Turn Into Fraud”New York Times, May 17, 1999
Fraud: Robert Fiddes“The abuses of this one doctor point to
weaknesses in the new system that has developed in recent years for testing experimental drugs. No longer does the pharmaceutical industry rely on career researchers at academic medical centers, whose professional reputations are forged on the quality of their data. Rather, the industry has turned to thousands of private-practice doctors, for whom testing drugs has become a sideline for making money.”
Kurt Eichenwald and Gina Kolata“A Doctor's Drug Studies Turn Into Fraud”New York Times, May 17, 1999
Case Study #3
When Things Go Wrong• Sensitivity Analysis
(Reanalyze)• Expand Audit (FDA, Sponsor,
Third Party)• Resubmission (delayed
approval)
Changing Landscape• The Critical Path • Data standards & electronic submissions• PRO and ePRO• Organizational Changes
– Bimo Initiative– CDER’s new Office of Translational Science
(OTS)• Connections
FDA Vision: e-Review
eSubSponsor
Document Mgmt System
Sponsor Data
Warehouse
FDAElectronicDocument
RoomServers
Desktop Tools (Acrobat, PPV,
JMP, Excel etc.)
Sponsor FDAGateway Repository Review Environment
DocumentsCRTsListingsPatient ProfilesAnalysis Data
CRTs Oracle
Database
JanusData
Warehouse
Document
Share
WebSDMData
Load &Validation
WebSDMData
Viewer
“The Standards Business”Kush/CDISC (2005)
CDA
RCRIM Technical Committee
Protocol Representation
ADaM
U.S. Dept. of Health and Human Services(HHS)
Health Level 7 (HL7)
U.S. FDA
CDISC
NIH/NCI NLM
EFPIA
EMEA MHLW
PhRMAJPMA
CDC
Reference Information Model
RIM
LAB
eCTD
LOINC
SNOMEDMedDRA
ODMSDS
= Organization= Dictionary, Codelist = Standard = Model
= Document Standard, or Architecture
BRIDG Model
International Conference on Harmonization (ICH)
World Health Organization (WHO)
FDA/CDISCwww.cdisc.org
• Clinical Data Interchange Standards Consortium
• Workgroups– Operational Data Model (ODM)– Submission Data Standards (SDS) – Analysis Data Models (ADaM)– Protocol– Electronic Source Data Interchange (eSDI)– Lab Data
ODM: Clinical Data Structure
*StudyEventData~*SubjectData~
*Annotation
*StudyEventData~
*Annotation
*SubjectData~
*ItemGroupData~*ItemData~
?Signature
?AuditRecord
*Annotation
*ItemGroupData~
*FormData~
?ArchiveLayoutRef~
?Signature
?AuditRecord
*Annotation
?Signature
?AuditRecord
?InvestigatorRef~
?SiteRef~
?Signature
?AuditRecord
Kubick
ADaM: Analysis-level Metadata• ANALYSIS NAME – A unique identifier for this
analysis. May include a table number or other sponsor-specific reference.
• DOCUMENTATION – A text description documenting the analysis performed.
• REASON – The reason for performing this analysis. Examples may include Pre-specified, Data-driven, Exploratory, and Regulatory Request.
• DATASET – the name of the analysis dataset used should be linked to the analysis dataset used for this analysis. In most cases, this will be a single dataset. If multiple datasets are used, they should all be listed here.
• PROGRAM – Analysis programs using the DATASET above as input can be described or included here.
ePRO: Specific Concerns When Using Electronic PRO Instruments
• …sponsors should plan carefully to ensure that FDA regulatory requirements are met for sponsor and investigator record keeping, maintenance, and access.
• These responsibilities are independent of the method … apply to electronic PRO data.
• Sponsors are responsible for providing investigators with the information they need to conduct the investigation properly, for monitoring the investigation, for ensuring that the investigation is conducted in accordance with the investigational plan, and for permitting the FDA to access, copy, and verify records and reports relating to the investigation…
BIMO Initiative• Ref. “Modernizing Human
Subject Protection/Bioresearch Monitoring,” Rachel E. Behrman, Deputy Director, Office of Medical Policy & Lead, Cross-Center Initiatives Task Force presented at PhRMA Bimo Meeting, March 31, 2006
FDA’s HSP/BiMO Initiative• Part of FDA’s Critical Path
Initiative• Begun December 2004• Steering committee chartered –
includes representatives from all centers and relevant offices
• Scoped out dimensions of issues and formed working groups
R. Behrman, 2006
FDA’s Oversight Must Evolve • Must provide regulatory guidance and perhaps
new regulatory scheme that encompasses modern trial arrangements – Responsibilities of investigators– Data integrity
• Must facilitate effective IRB oversight of evolving clinical trials arena to facilitate– IRB oversight of human subject protection – FDA oversight of IRB function
• Need common standards and regulatory requirements for electronic data handling
• Must be able to accommodate globalization of clinical trials
• Must ensure comprehensive approach to protection of vulnerable populations
R. Behrman, 2006
Guiding Principles of FDA Initiative
• Collaborative efforts among government, academia, industry and patient groups
• Infrastructure and “toolkit” development, not product development
• Build support for academic science bases in relevant disciplines
• Build opportunities to share existing knowledge & database
• Develop enabling standardsR. Behrman, 2006
CDER/OTS• CDER’s new Office of Translational
Science• “Coming together”
– Office of Biostatistics (OB)– Office of Clinical Pharmacology (OCP)
• Focus for Critical Path activities at CDER
Comments/Connections• Parsimony: Guidance for Industry --
Cancer Drug and Biological Products —Clinical Data in Marketing Applications
• Critical Path: Case report form Standards• DQRI – Data Quality Research Institute• SCDM – Society for Clinical Data
Management
Thank [email protected]