Clinical Data Management Process Overview_Katalyst HLS

Clinical Data Management (CDM)
Process Overview
2/21/2017Katalyst Healthcares & Life Sciences
1

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Questions
Demonstration
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2
ReferenceTest Your
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g
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Clinical data management includes the entry, verification, validation
and quality control of data gathered during the conduct of a clinical
trial.
Clinical Data Management is involved in all aspects of processing the
clinical data. It involves working with a range of computer applications,
database systems to support collection, cleaning and management of
clinical trial data.
Review and approval of new drugs by Regulatory agencies is
dependent upon the integrity of clinical trial data which is the
core purpose of CDM.
Overview
3
Overview

After this chapter you will be able to understand:
• Overview of Clinical Data Management
• Process flow of data management activities
• Activities performed during the course of a trial
• Analysis and reporting process overview
• Roles and responsibilities of all personals involved in CDM
Objectives
4 2/21/2017Katalyst Healthcares & Life Sciences

 The average number of discrepancies created during the course of a
Phase 3 study ranges from 3,000 to 30,000
 The turn around time to action a discrepancy from the time of
generation is 2-3 days
 A single open discrepancy or a Database update can lead to Database
unlock
Do You Know

Abbreviations
6
CRF Case Report Form
DB Database
QC Quality Control
DMP Data Management Plan
CSR Clinical Study Report
UAT User Acceptance Testing

Definition of Clinical Trial
It is a systematic study of new drug(s) in human subject(s) to generate
data for discovering and/or verifying the clinical, pharmacological
(pharmacokinetic and Pharmacodynamics), and/or adverse effects with
the objective of determining safety and /or efficacy of the a new drug.

Clinical Trial Phases
 Phase I Trials —Involve a small group (20 to 100) of healthy volunteers
to discover if the drug is safe in humans
 Phase II Trials —Involve 100 to 500 patients who actually have the
disease. Clinical studies are conducted to evaluate the effectiveness of
the drug and to determine the common short-term side effects and
risks associated with the drug
 Phase III Trials —Involves thousands of patients to generate
statistically significant data about safety, efficacy, and an overall
benefit/risk profile
 Phase IV Trials —Certain post marketing studies to find out
additional information about the drug's risks, benefits, and its optimal
use.

Why Clinical Trials?
 Species difference
 Some effects seen only in humans
 Correlation of effects in animals and human –not always possible
 To assess if the treatment is safe and effective in humans
Man is final experimental animal to be tested
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2/21/2017
Katalyst Healthcares & Life Sciences

Multidisciplinary Roles in Clinical
trial
1. Clinical Investigator
2. Site coordinator
3. Pharmacologist
4. Trialist/Methodologist
5. Biostatistician
6. Lab Coordinator
7. Reference lab
8. Project manager
9. Clinical Research Manager/Associate
10. Monitor
10
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
19. Study Physician

Clinical Data Management -
Overview
11
Investigator Monitor
Central
Laboratory
Data Manager
Statistician
Clinician
Regulatory
Authority
Subject
CRF
DCF
CRF DCF
Sample
Lab
Results
Clinical
Data
NDA
DCF

Definition of Data
 Data with reference to CDM means the Patient Information which is
collected during Clinical trial.
 Data is collected to establish whether the objective of the Clinical Trial
is met

Objectives of CDM
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Data Collection
Data integration
System / Data
Validation
Paper, Electronic and Remote
data capture
Integration of data received
from all sources in a single
DB. Ensures consistency and
correctness
System validation done via
UAT, QC and Programming
Data Validation via Edit
check programs and
manual review

Scope of CDM
 Main scope of CDM is to Collect, Validate and Analyze the clinical data
 Design and development of data collection instrument such as Paper
CRF, Electronic CRF, Clinical database etc
 Design and development of tools for Validation such as Edit Checks,
User Acceptance Testing etc
 Design and development of tools for Analyzing data such as DDR/DDS
(Derived Dataset Requirement/Specification) etc.

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. It helps :
 To provide consistent, accurate & valid clinical data
 To support accuracy of final conclusions & report
Clinical Data Management ensures:
 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

16
Inter-dependent groups in CDM
Data Cleaning
BiostatisticsProgramming
Clinical Data
Management

DM role in Clinical Research
 CDM has evolved from a mere data entry process to a much diverse process
today
• The data management function provides all data collection and data
validation for a clinical trial program
• Data management is essential to the overall clinical research function, as
its key deliverable is the data to support the submission
• Assuring the overall accuracy and integrity of the clinical trial data is the
core business of the data management function
• It provides data and database in a usable format in a timely manner
• It ensures clean data and a ‘ready to lock’ database

DM role in Clinical Research
• At the study level, data management ends when the database is locked
and the Clinical Study Report is final
• At the compound level (of the drug), data management ends when the
submission package is assembled and complete

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Data
Acquisitio
n
Site / Investigator
Programmers
Coders
Safety
Study
Team/Client
Monitor / CRA
DM Communication & Interfaces

20
CDM Activities –Phase-wise

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Study Start-up Process
Protocol
CRF Design
Database
Design
Validation/
Derivation
Procedures
Activated
database ready
to accept
production data

Study Set-up –Roles and Responsibilities
 CRF Designers -Design CRF as per protocol
 DB designers -Design DB as per protocol OR CRF OR CRF Specs and
activate the same
 Programmers -Program Validation and Derivation procedures, and
activate the same
 Data Managers -Review the CRF prior to activation, test the database
prior to activation, write the validation and derivation
procedures/checks and test the same prior to activation

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Study Conduct Process
Activated DB
Data Entry /
Loading (CRF
& external
data)
Discrepancy
Management
Query
Generation
Safety Data
Recon.
Coding terms
Resolution &
update of DB
Manual
Check/ QC

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Study Conduct –Roles and
Responsibilities
Data Entry/Data Loaders-Manually enter the data (in case of paper
studies),
load data in case of electronic studies) and external data (Example:
lab, ECG,
subject diaries etc.)
Data Managers -Identify and resolve discrepancies, issue queries to
site
& resolve them, carry out manual checks, lab review and CRF tracking
Safety Data Managers -Perform the safety reconciliation by
comparing the
clinical database with the safety database
Dictionary Coders -Code medical terms collected during clinical
trial.
Example: Medications and Adverse events

Data Capture
Regardless of whether you’re running a small, single Phase I trial or many,
complex Phase III trials you look for ways to ensure that your organization
is collecting and managing clinical data reliably, efficiently and in
compliance with industry and government regulations.
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Electronic
Data Capture
Paper Data
Capture
Remote Data
Capture
Data
Capture

Difference between Data Capture Tools
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The difference between Paper, Electronic and Remote data
capture is :
Paper
 Data is entered on
Paper Case Report
Form
 Data Entry
associate will
enter the data in
to the Clinical
Data base
 No real time
access to the data
Electronic
• Data is captured in
electronic Case
Report Form
• Investigator enters
the data into the
database
• Real time access to
the data
Remote data entry/ capture
• Data is captured in
electronic Case Report
Form
• RDE systems allow
research staff to enter data
directly at the medical
setting, useful when a
multicenter study is being
conducted with many
institutions participating
• Not web based thus no real
time access to the data

CRF –DEMO Snap shot

CRF Tracking
 Receipt and Tracking of CRF
 The tracking process encompass verification of the arrival date & its
acknowledgement & its progress through the process
 Checking of quality and completeness of the documents
 Tracking missing documents

Data Entry & Verification
Data Entry Processes is of two types as follows:
1.Single Pass Data Entry
→ Single entry with a manual review
→ Single entry without manual review
2.Double Pass Data Entry
→ Double data entry with blind verification, where two people enter the
data independently and any discrepancies between first and second entry are
resolved by the third person based on the verification report on records that
failed data entry verification
→ Double entry with interactive verification where the second entry
operator resolves discrepancies between 1st & 2nd entry and is aware of the
first entered values

Data Review
Why Data Review?
 To ensure complex medical data are reviewed and assessed to detect any
discrepancy in the data.
Discrepancy Examples:
 Empty fields
 Incorrect Range
 One value greater/less than/equal to another
 Dates not in logical sequence
 Inconsistent header information
 Any missing visits or pages
 Visits not in compliance with protocol
 Inclusion/exclusion criteria not met

Data Review –Edit Checks
 Consist of computer checks on the data to assure the validity and
accuracy of the data
 Validate data manually against predetermined specifications
 Primarily used to check the efficacy data unique to the current study

Edit Checks Types
Range checks
 To identify inaccurate or invalid data & statistical outliers
 To ensure that data outside of permitted range are to be clarified and
verified
 E.g. Systolic blood pressure (***) is outside the Critical Range (***).
Consistency checks
 To highlight area where the data in the database are inconsistent
 E.g. Adverse Event stop date is always after AE start date
Presence checks
 To ensure completeness of data
 E.g. SEX is missing

Data Query
 A query is an official communication to the investigative site to
question on a discrepant data on the case report form.
 Subsequent changes in the data must be supported by signed Data
Clarification Form (DCF). EDC Query
Data Clarification Form (DCF)

Medical Coding
It is a process which involves grouping or classifying new and amended
terms like medications, adverse events, medical history medical
procedures, diagnoses, disease conditions with reference to known
standard terms as mentioned in medical dictionary
Importance of coding :
 The use of medical coding dictionaries for medical term data such as
adverse event, medical history, medications & treatments/procedures
are valuable from the standpoint of minimizing variability in the way
data are reported and analyzed.
 To provide control & consistency, a variety of medical coding
dictionaries may be used to process, analyze and report collected data.

Medical Coding Dictionaries
Coding Dictionaries:
MedDRA
Medical Dictionary for Regulatory Activities, is a standardized dictionary of
medical terminology
WHO: WHOART, drugs
World Health Organization Adverse Reaction Terminology
ICD
International Classification of Diseases
FDA-COSTART
Coding Symbols for a Thesaurus of Adverse Reaction Terms

Safety Data Reconciliation
What is AE : Adverse event means any untoward medical occurrence
associated with the use of a drug in humans, whether or not considered
drug related.
What is a Serious Adverse Event:
Any adverse event that leads to:
 Results in death
 Is life-threatening
 Requires inpatient hospitalization or
 Prolongation of existing hospitalization
 Results in persistent or significant disability / incapacity
 Is a congenital anomaly / birth defect

Safety Data Reconciliation
Reconciliation: It is the comparison of particular data points related to SAEs
that appear in both the Safety and Clinical Databases and must be cleaned
100%, with all acceptable discrepancies documented. All SAEs entered into
the clinical trial database are also entered into the drug safety database and
are reconciled to ensure the consistency between specified data points.
Reason for performing Reconciliation:
 It is necessary because SAE data is considered CRITICAL DATA in both ,
the safety and clinical databases. Critical data is made up of dosing,
demography, adverse event and final subject summary pages, all of which
are data points that make up the cases that are reported to the safety
database
 It is essential to understand that these data are submitted to Regulatory
Agencies both at end of study and for subsequent aggregate reporting
which occurs well after database lock.

Study Closeout Process
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Discrepancy
Management
Query
generation
Resolution
and/or update
of DB
Manual
check/QC/CR
F tracking
DB lock and
freeze
Safety Data
Recon.
Coding terms

Declaring Clean File & Database Lock
 Clean File means that the data generated from clinical trial is clean & ready
for Database Locking/freezing
 Clean File can be declared for a study when all required data management
activities (as per the Data Management Plan) have been completed and
documented appropriately
 This is a procedure which is done at the end of clinical trial after the last
query is resolved & prior to DB locking/Freezing
This procedure ensures the following points are met:
 Data is complete i.e., No missing data
 Data is consistent
 Data is accurate
 Data is reliable

Validated clean data will be transferred to a final
database
Prior to locking the study, the following steps are
completed:
Checklist for Database Lock
40
All expected CRFs are entered
All CRFs have been Verified by the CRA
All data discrepancies are resolved
Final validations are executed with no remaining unresolved discrepancies
All lab data, external and internal (e.g. PK, ECG), are loaded and reconciled
All lab normals are present, loaded and complete
Adverse event coding is complete and approved by the study MD
All other medical coding is complete
The Statistician confirms that the data meet previously agreed acceptance criteria
The Statistician and CDM agree that the database is ready for locking
All approvals are obtained on the Database Lock/Freeze/Unfreeze Approval form

Unlock Scenarios
Can a Database be unlocked?
Ans: Yes
When can Unlocking be Done?
 Unlocking of the database is carried out only if corrections to the critical errors
(such as Adverse Event, Medication, Lab, etc.) are required.
 For e.g. -Updates to serious adverse events data may require edits to the data.
 A request to unlock the study usually requires review of detailed reasons by
higher level management before the database administrator removes the locks.
 Appropriate quality control, review and approval will again be required to
unlock the study.

Quality Control
 Quality Control (QC): Periodic operational checks within each functional
department to verify that clinical data are generated, collected, handled, analyzed,
and reported according to protocol, SOPs, and GCP.
Example: QC activities performed during the data management process:
 Double Data Entry: Accuracy of the initial data entry is verified by an independent
entry of the same data and a subsequent comparison of both sets of data for non-
agreement.
 Edit Checks/ Manual Review: The reality of the data is checked with a
preprogrammed logic check program and a subsequent manual review
 Final QC: The database entries are then QC'dversus the CRFs
 Tables, Listings and Graphs (TLG) inspection: The TLGs that are generated as
part of a statistical analysis of the data are also inspected to ensure their accuracy.

Quality Assurance
Quality Assurance:
“All those planned and systematic actions that are established to ensure
that the trial is performed and the data are generated, documented
(recorded), and reported in compliance with Good Clinical Practice
(GCP) and the applicable regulatory requirement(s).
Involves Inspections and Audits
 Inspection is by Governmental Agencies, Health Authorities and the
Drug Regulatory Authorities
 Auditing is by pharmaceutical, devices companies, CROs, and others

Audits Types
Internal audit (first party audit):
 Carried out by service provider’s Audit Department to ensure
implementing, maintaining and improvement of the system audited.
Customer audit (second party audit):
 Carried out by client to evaluate the service providers’ performance and
compliance for standards.
External audit (third party audit):
 Carried out by regulators or external auditors contracted by sponsor to
ensure implementing and documenting according to standards.

Benefits of Internal Audit
 Audit of processes to identify systemic problems
 Identify the root of a problem and plan for corrective and preventive
actions
 Review of employee training records
 Compliance with SOPs and regulatory requirements
 Documented evidence that QC was appropriately conducted on the
output of each internal process
 Achieve better allocation of resources

Roles & Responsibilities
 Programmers extract data and map the same into specific formats
(reports and listings) as specified by the sponsor to aid the statistical
analysis.
 Statisticians use the programmed reports and listings and analyze the
data as per a pre approved statistical plan.

A & R –Tables & Listings snap shot

Roles & Responsibilities
Medical Writers – Generate Clinical Study Report, using the statistical
analysis and other study documents thus summarizing the overall
findings and conclusions of a clinical trial. The CSR is used for
submission to the regulatory authorities

Slide No. 49 • QS CRS Quality
Services / Svend Martin Fransen
• 03.Oct.2002
21CFR11, Overview
 Substantive rule from 20 August 1997
 Applies to any e-record in any FDA regulated work
including legacy systems
 Criteria for e-records and e-signatures:
 Trustworthy and reliable
 E-signatures = hand-written signatures
 Minimum requirements / fraud prevention

• 03.Oct.2002
Systems not Applications
• All definitions and
clauses in 21 CFR 11
refer to systems
• Application is not
mentioned
• IT part of the GXP
environment.
• Do they know?
Working environment
Computer based system
Computer system
Application
-software
Platform
- hardware
- system SW
Controlled function
Instructions,
Manuals, etc.
Equipment
COMPUTER RELATED SYSTEM

• 03.Oct.2002
21 CFR Part 11, Basics
• Electronic records equivalent with paper records
• Storage, retrieval and copying in full retention period
• Submitting to FDA
• Protection of electronic records
• Security (physical and logical)
• Validation
• Audit trail (who did what, when including reason where req.)
• Permission to use of electronic signature
• Equivalent with handwritten signatures
• Name, date and meaning
• Linking of signature to record
• Unique for an individual

• 03.Oct.2002
FDA 21CFR11 inspection questions
(source: : 21CFR11 Compliance Report, Vol.2, No. 4).
 Who is allowed to input data?
 Who is allowed to change data?
 How can you tell who entered the data?
 How do you know which data had been changed?
 When do you lock down the data input?
 Can you do the following actions?
“Show me some data, show me you can see the history of the data,
show me you control the data life cycle.”
 Is the system validated and are the requirements met?
 Can you show me the results of the validation activities?
 Does the validation include: “Pass/fail, signature, date/time stamp”;
and “objective evidence - screen prints or page printouts with a link
to the direction that generated the output.”?

Questions

1. When do the CDM activities start.
2. What is the first activity performed by CDM in
Study Start-up?
3. What are the modes of data collection?
4. What are the different ways of Validating data?
5. What does CSR stand for?
Test Your Understanding

In this session we have understood the following points:
● What is Clinical Research?
● What is Clinical Data Management?
● Importance of CDM
● CDM work flow
● Roles and Responsibilities across all processes
● Activities performed by Data Managers in Clinical Research
Summary

• Practical Guide to Clinical Data Management; Second Edition: by
Susanne Prokscha
• COMPUTERIZED SYSTEMS USED IN CLINICAL TRIALS, U.S.
Department of Health and Human Services, Food and Drug
Administration
• http://en.wikipedia.org/wiki/Clinical_trial
Source

Thank You
&
Questions
2/21/2017
78
Contact:
Katalyst Healthcare’s & Life Sciences
South Plainfield, NJ, USA 07080.
E-Mail: info@KatalystHLS.com

Clinical Data Management Process Overview_Katalyst HLS

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