Overall CDM Process
Introduction ď Ź
CDM is consistently being recognized as a primary part of clinical development team & in some instances leads this team!
Evolution
CDM has evolved from a data entry process into a diverse process “to provide clean data in a useable format in a timely manner” “provide a database fit for use” “ensuring data are clean & database is ready to lock” Now CDM manages
entry of CRF data merging of non-CRF data systems & processes designed to identify bad data generate & track CRFs & queries determine protocol violators interact with site personnel to resolve data issues
CDM as a Science
Factors contributing to CDM as a subject
New technologies Growth predictions Globalization Need for a supporting infrastructure
Role of CDM in overall drug development organization is continuing to evolve Relationships with other organizations are continuing to be defined & developed CDM is a very visible & strong organization now Considered as an integral, respected, highly valued member of clinical development team
Importance of CDM CDM is a vital vehicle in Clinical Trials to ensure integrity & quality of data being transferred from trial subjects to a database system ď Ź To provide consistent, accurate, & valid clinical data ď Ź To support accuracy of final conclusions & report
GCP Guidelines
All clinical research data should be recorded, handled, & stored in a way that allows its accurate reporting, interpretation & verification. (ICH GCP 2.10, 4.9, 5.5, 5.14 & ICH E9 3.6 & 5.8)
Systems with procedures that assure quality of every aspect of research should be implemented. (GCP 2.13)
Quality assurance & quality control systems with written standard operating procedures should be implemented & maintained to ensure that research are conducted & data are generated, documented & recorded, & reported in compliance with protocol, GCP & applicable regulatory requirements. (GCP 5.1.1)
GCP Guidelines
If data are transformed during processing, it should always be possible to compare original data & observations with processed data (ICH GCP 5.5.4) Sponsor should use an unambiguous subject identification number or code that allows identification of all data reported for each subject. (ICH GCP 5.5.5) Protocol amendments that necessitate a change in design of CRF, subject diaries, study worksheets, research database & other key aspects of CDM processes need to be controlled. (ICH E9 2.1.2) Common standards should be adopted for a number of features of research such as dictionaries of medical terms, definition & timing of main measurements, handling of protocol deviations. (ICH E9 2.1.1)
Clinical Data Management ď Ź
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CDM refers to management of data capture & data flow processes in conduct of a clinical research It begins with design of data capture instrument & data collection, continues with data QC procedures to assure quality of all aspects of process, & ends with database finalization
Objectives of CDM To ensure: That collected data is complete & accurate so that results are correct That trial database is complete & accurate, & a true representation of what took place in trial That trial database is sufficiently clean to support statistical analysis, & its subsequent presentation & interpretation
Clinical Development Process
Financial Management
Data Collection and Management Trial Management
Site Management
Clinical Program Management
Regulatory Submission Site Systems
Pharmacovigilance Source:Bio-IT 2004
Clinical Development Process Financial Mgmt Drug Investigator & Vendor Payments Mgmt Contract Mgmt
Data Processing Protocol Coding Authoring Lab Load Site Planning Site Site Recruitment Mgmt Site & Drug Logistics
Site Payments & Reports Patient Site & Lab Recruitment Comm’s Patient Scheduling
Schedule Mgmt Resource Monitoring Mgmt Process Metrics Reg Planning & Tracking Stats & eSubmit Reporting Doc Mgmt
Site Selection Trial Portfolio Benchmark Mgmt Trial Simulation Regulatory Reporting Saftey Coding Mgmt Medical Information
Source:Bio-IT 2004
Multidisciplinary Team 1. 2. 3. 4. 5. 6. 7. 8. 9.
Clinical Investigator Site coordinator Pharmacologist Trialist/Methodologist Biostatistician Lab Coordinator Reference lab Project manager Clinical Research Manager/Associate 10. Monitor
11. Regulatory affairs 12. Clinical Data Management 13. Clinical Safety Surveillance Associate (SSA) 14. IT 15. IT/IS personnel 16. Trial pharmacist 17. Clinical supply 18. Auditor/Compliance
CDM Process Subject
CRF DCF Investigator
Monitor
Sample
CRF
DCF
Lab Results
Central Laboratory
Statistician
Data Manager
NDA Clinical Data Regulatory Authority Clinician
21 Jan 2006
Role of DM in Clinical Research DATA MANAGEMENT
PROGRAMMING
BIOSTATISTICS
Data Flow Chart Set up database, with built in range checks for validating data at the data entry stage
Log in CRFs received via Courier or CRF images received via telephone line
Create data entry forms (linked to database) with formats similar to those of CRF pages
Data Entry & Validation using built-in range checks on an ongoing basis
Final Data Quality Audit plus statistical quality control procedures
Interim Data Quality Audits
Database Lock
Query Resolution & Database Correction
Program complex data edits separately
Periodic Conversion of database for applying data edit checks
Run edits on converted data
Review edit lists & send queries to Sites after manual review
Paper based data collection sample or test data
analysis results
Core Lab or Events Committee performs analysis Clinical Data
Patient enrolled in trial
Research completes
CRF
Coordinator paper CRF
Monitor / CRA Source Document Verification
CRF/core lab data mailed to Data Entry Group Clinical Trials Database
iterative query resolution process (paper faxed or mailed)
Data queries issued and resolved
Data Entry QA Database verified to CRFs
Clean
data
Biostatistician Data Analysis
Data Entry Data entered into database
Electronic data collection sample or test data
analysis results Core Lab or Event Committee perform analysis
Clinical Data
Patient enrolled in trial
Research Coordinator completes electronic CRF
CRF submitted electronically
Electronic query resolution
Monitor Source Document Verification
CRA Real-time review of data
Clean data
Biostatistician Data Analysis
Clinical Trials Database
Acquisition or Collection of Clinical Trial Data
Data Capture Instrument
CRF Design
Paper forms (‘No Carbon Required’ :NCR) Remote Data Entry Electronic data transmission from Central lab Central web based system & Other technologies
Data Source & Data Definition
Identify Data Source
Study Sites Reference Lab ECG/RDE
Data Definition
Identify data required (data items, study variables) Define variables Source Data Verification (SDV) Edit Checks
Validation Processes
Testing of Screen vs DB structure Validation of Range Date Format Coding field discrepancies Testing of second entry verification file comparison batch verification Design specifications of software Criteria for acceptance or rejection of software Results documentation Review & approval documents
Data Validation/Edit Check
Consist of computer checks on data to assure validity & accuracy of data Validate data against predetermined specifications Primarily used to check efficacy data unique to current study
Validation Checks
Range checks To identify inaccurate or invalid data & statistical outliers To ensure that data outside of permitted range are to be clarified & verified
Consistency checks
To highlight area where data in database are inconsistent
Presence checks
To ensure completeness of data
CRF Design
Design CRF along with protocol to assure collection of only data protocol specifies Guidelines to collect data through independent means Design CRF with primary safety & efficacy endpoints in mind as main goal of data collection Establish & maintain a library of standard forms CRF to be available for review at clinical site prior to approval Use NCR paper or other means to assure exact replicas of paper collection tools
CRF Development & Tracking
CRF completion guideline is printed as parts of CRF Training sessions are conducted for investigators & SC during study initiation meeting Receipt & Tracking of CRF Tracking process encompass verification of arrival date & its acknowledgement & its progress through process
CRF Scanning
CRF are scanned soon after receipt in CRF Tracking System & archived electronically as backup into an image database by designated CDC Benefits: Effortless
access to CRF images It provides a single source for most up to date copy of CRF Ensures that original entries were not overwritten during clinical CRF / data review
EDC Processes
Develop e-CRFs along with Monitoring, Statistics, Regulatory affairs, & Medical teams Ensure
Collection of safety data User-friendly screens Flexibility of data entry Validation procedures Query management tools Audit trails Data transfers Integration of laboratory & other non-CFR data
Data Storage
Backup copies to be taken frequently Paper documents should be scanned & electronically archived Database design specifications Raw data Audit trail Original study documents Procedural Variation Documentation Database Closure Site copies of data Final data - ASCII, SAS Transport, pdf, CDISC ODM Model
External Data
Vendor-specific training Vendor Audit Data clarification process Utilize standards such as HL7, CDISC Data editing & verification procedures File formats Data transmission Database updates Data storage & archiving
Coding
Auto-encoder Dictionaries Process for change in dictionary or version Same version to be used for combined studies Training Process for submitting changes to dictionaries
Data Dictionaries
MedDRA
WHO: WHOART, drugs
World Health Organization Adverse Reaction Terminology
ICD
An International Conference on Harmonization (ICH) initiative, is a standardized dictionary of medical terminology
International Classification of Diseases
FDA COSTART
Coding Symbols for a Thesaurus of Adverse Reaction Terms
Data Cleaning
Purpose, characteristics & complexity of study Critical variables
Documentation of
primary & secondary safety & efficacy subject identifiers Procedures Guidelines working practices references
Testing the process
Data Cleaning
CRF completion/data entry instructions Timelines for
data entry running data checks replicating data.
Database quality criteria Quality control plan
Image Review (a pre-entry review) ď Ź
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CRF image also known as working copy CRF is reviewed for accuracy, completeness & consistency of data Any queries or discrepancy identified during Image Review were annotated Look for problems with legibility, incorrectly completed fields, missing data & scientifically invalid or obviously inconsistent data
Data Review
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Clinical data review by designated medical reviewer Ensure complex medical data are reviewed & assessed to detect any clinical nuances in data
Data Query ď Ź
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A query is raised when a discrepancy or an inconsistency is noted or annotated during image review & during computer editcheck. Subsequent changes in data must be supported by signed Data Clarification Form (DCF) or authorized Data Handling Convention
Declaring Clean File ď Ź
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Clean File for final database is declared when all clean data have been transferred After declaring Clean File, editing on database will only be allowed with proper documentation
Data Closure
All data have been received & processed All queries have been resolved External data are reconciled SAEs are reconciled Coding list review Review for logic & consistency Final review Quality audit of data Error rate Updating documents
Data Closure
Blind Data Review
Data Listing
Generate hardcopy listing of data for clinical study report
Data Transfer
After clean file is declared, blind data review prior to final analysis
Transfer of data to another site Sponsor, Statistician, Regulatory, eg eSubmission
Electronic data archive
Archiving Electronic repository of Clinical data Metadata Administrative data Reference data CRF or eCRF images in PDF form Program files Validation records Regulatory documents Audit trail Data structures Edit checks Transfer specifications
QA
Compliance of procedures to Regulations Written procedures Error rates for variables used in primary & secondary safety & efficacy Monitor aggregate data Site audits Inspections (CRF-to-database) Data quality impact analysis Quality Policy Standardized or validated data collection & handling processes Error prevention Process monitoring
QC Edit Data Coding Checks Double & Data Data Review Image Entry System SDV by Review Validation CRA By Clinical IT
CRF to Database Inspection
The Quality of overall data is thus increased because sooner a data capture problem is detected & corrected, higher quality of final data