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Clinical Data Management (CDM)
Process Overview
11/20/2017Katalyst Healthcares & Life Sciences
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2
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11/20/2017Katalyst Healthcares & Life Sciences
Clinical data management includes theentry, 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 managementof
clinical trial data.
Review and approval of new drugs by Regulatoryagencies is
dependent upon the integrityof clinical trial data which is the
core purpose of CDM.
Overview
3
Overview
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After this chapter you will be able to understand:
• Overview of Clinical Data Management
• Process flow of data managementactivities
• Activities performed during the course of a trial
• Analysis and reporting process overview
• Roles and responsibilitiesof all personals involved in CDM
Objectives
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✓ The average numberof 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 discrepancyor a Database update can lead to Database
unlock
Do You Know
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Abbreviations
6
CRF Case Report Form
DB Database
QC Quality Control
DMP Data Management Plan
CSR Clinical Study Report
UAT User Acceptance Testing
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Definition of Clinical Trial
It is a systematicstudy of new drug(s) in human subject(s) togenerate
data for discovering and/orverifying the clinical, pharmacological
(pharmacokineticand Pharmacodynamics), and/oradverse effects with
the objectiveof determining safety and /or efficacy of the a new drug.
711/20/2017Katalyst Healthcares & Life Sciences
Clinical Trial Phases
 Phase I Trials —Involvea 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 effectivenessof
the drug and to determine the common short-term side effects and
risks associated with the drug
 Phase III Trials —Involves thousandsof patients to generate
statisticallysignificantdata about safety, efficacy, and an overall
benefit/risk profile
 Phase IV Trials —Certain post marketing studies to find out
additional informationabout the drug's risks, benefits, and its optimal
use.
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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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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
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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
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Definition of Data
 Data with reference to CDM means the Patient Informationwhich is
collected during Clinical trial.
 Data is collected to establish whether the objective of the Clinical Trial
is met
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Objectives of CDM
13
Data Collection
Data integration
System / Data
Validation
Paper, Electronicand Remote
data capture
Integration of data received
from all sources in a single
DB. Ensures consistencyand
correctness
System validation done via
UAT, QC and Programming
Data Validation via Edit
check programs and
manual review
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Scope of CDM
 Main scope of CDM is to Collect, Validateand Analyze the clinical data
 Design and developmentof data collection instrumentsuch as Paper
CRF, Electronic CRF, Clinical database etc
 Design and developmentof tools for Validation such as Edit Checks,
User AcceptanceTesting etc
 Design and developmentof tools for Analyzing data such as DDR/DDS
(Derived Dataset Requirement/Specification) etc.
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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 Managementensures:
 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
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Inter-dependent groups in CDM
Data Cleaning
BiostatisticsProgramming
Clinical Data
Management
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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
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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
submissionpackage is assembled and complete
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Data
Acquisitio
n
Site / Investigator
Programmers
Coders
Safety
Study
Team/Client
Monitor / CRA
DM Communication & Interfaces
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CDM Activities –Phase-wise
11/20/2017Katalyst Healthcares & Life Sciences
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Study Start-up Process
Protocol
CRF Design
Database
Design
Validation/
Derivation
Procedures
Activated
database ready
to accept
production data
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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 Validationand 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-Manuallyenter 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 -Identifyand 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
DictionaryCoders -Code medical terms collected during clinical
trial.
Example: Medicationsand 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
compliancewith industryand governmentregulations.
25
Electronic
Data Capture
Paper Data
Capture
Remote Data
Capture
Data
Capture
11/20/2017Katalyst Healthcares & Life Sciences
Difference between Data Capture Tools
26
The difference between Paper, Electronicand 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
11/20/2017Katalyst Healthcares & Life Sciences
CRF –DEMO Snap shot
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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 completenessof the documents
 Tracking missing documents
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Data Entry & Verification
Data Entry Processes isof 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 entrywith blind verification, where two people enter the
data independentlyand 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 entrywith interactiveverification where the second entry
operator resolves discrepancies between 1st & 2nd entry and is aware of the
first entered values
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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 compliancewith protocol
 Inclusion/exclusioncriteria not met
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Data Review –Edit Checks
 Consist of computer checks on the data to assure the validityand
accuracy of the data
 Validatedata manuallyagainst predetermined specifications
 Primarily used to check the efficacy data unique to the current study
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Edit Checks Types
Range checks
 To identify inaccurateor 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 (***).
Consistencychecks
 To highlight area where the data in the databaseare inconsistent
 E.g. Adverse Eventstop date is always after AE start date
Presence checks
 To ensure completenessof data
 E.g. SEX is missing
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Data Query
 A query is an official communication to the investigative site to
question on a discrepant data on the case report form.
 Subsequentchanges in the data must be supported by signed Data
Clarification Form (DCF). EDC Query
Data Clarification Form (DCF)
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Medical Coding
It is a process which involvesgrouping or classifying new and amended
terms like medications, adverse events, medical history medical
procedures, diagnoses, disease conditionswith reference to known
standard terms as mentioned in medical dictionary
Importanceof coding :
 The use of medical coding dictionaries for medical term data such as
adverse event, medical history, medications & treatments/procedures
are valuable from the standpointof 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, analyzeand report collected data.
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Medical Coding Dictionaries
Coding Dictionaries:
MedDRA
Medical Dictionary for Regulatory Activities, is a standardized dictionaryof
medical terminology
WHO: WHOART, drugs
World Health Organization Adverse Reaction Terminology
ICD
International Classificationof Diseases
FDA-COSTART
Coding Symbols for a Thesaurus of Adverse Reaction Terms
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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 SeriousAdverse Event:
Any adverse event that leads to:
 Results in death
 Is life-threatening
 Requires inpatient hospitalizationor
 Prolongationof existing hospitalization
 Results in persistentor significantdisability / incapacity
 Is a congenital anomaly / birth defect
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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 acceptablediscrepanciesdocumented. All SAEs entered into
the clinical trial database are also entered into the drug safety databaseand
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 subsequentaggregate reporting
which occurs well after database lock.
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Study Closeout Process
38
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
11/20/2017Katalyst Healthcares & Life Sciences
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 pointsare met:
 Data is complete i.e., No missing data
 Data is consistent
 Data is accurate
 Data is reliable
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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
11/20/2017Katalyst Healthcares & Life Sciences
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.
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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.
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Quality Assurance
Quality Assurance:
“All those planned and systematicactions that are established to ensure
that the trial is performed and the data are generated, documented
(recorded), and reported in compliancewith Good Clinical Practice
(GCP) and the applicable regulatory requirement(s).
Involves Inspectionsand Audits
 Inspection is by Governmental Agencies, Health Authorities and the
Drug Regulatory Authorities
 Auditing is by pharmaceutical, devices companies, CROs, and others
4311/20/2017Katalyst Healthcares & Life Sciences
Audits Types
Internal audit (first party audit):
 Carried out by service provider’s Audit Department toensure
implementing, maintaining and improvementof the system audited.
Customeraudit (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.
4411/20/2017Katalyst Healthcares & Life Sciences
Benefits of Internal Audit
 Audit of processes to identifysystemic 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
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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.
 Statisticiansuse the programmed reports and listingsand analyze the
data as per a pre approved statistical plan.
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A & R –Tables & Listings snap shot
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Roles & Responsibilities
Medical Writers – Generate Clinical Study Report, using the statistical
analysis and other study documents thus summarizing the overall
findings and conclusionsof a clinical trial. The CSR is used for
submissionto the regulatory authorities
4811/20/2017Katalyst Healthcares & Life Sciences
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
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Slide No. 71 • QS CRS Quality
Services / Svend Martin Fransen
• 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
11/20/2017Katalyst Healthcares & Life Sciences
Slide No. 72 • QS CRS Quality
Services / Svend Martin Fransen
• 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
11/20/2017Katalyst Healthcares & Life Sciences
Slide No. 73 • QS CRS Quality
Services / Svend Martin Fransen
• 03.Oct.2002
FDA 21CFR11 inspection questions
(source: : 21CFR11 ComplianceReport, 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 validationactivities?
 Does the validation include: “Pass/fail, signature, date/timestamp”;
and “objectiveevidence - screen prints or page printouts with a link
to the direction that generated the output.”?
11/20/2017Katalyst Healthcares & Life Sciences
Questions
74 11/20/2017Katalyst Healthcares & Life Sciences
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
75 11/20/2017Katalyst Healthcares & Life Sciences
In this session we have understood the following points:
● What is Clinical Research?
● What is Clinical Data Management?
● Importanceof CDM
● CDM work flow
● Roles and Responsibilities across all processes
● Activities performed by Data Managers in Clinical Research
Summary
76 11/20/2017Katalyst Healthcares & Life Sciences
• Practical Guide to Clinical Data Management; Second Edition: by
Susanne Prokscha
• COMPUTERIZED SYSTEMS USED IN CLINICAL TRIALS, U.S.
Departmentof Health and Human Services, Food and Drug
Administration
• http://en.wikipedia.org/wiki/Clinical_trial
Source
77 11/20/2017Katalyst Healthcares & Life Sciences
Thank You
&
Questions
11/20/2017
78
Contact:
Katalyst Healthcare’s & Life Sciences
South Plainfield, NJ, USA 07080.
E-Mail: info@KatalystHLS.com

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CDM_Process_Overview_Katalyst HLS

  • 1. Clinical Data Management (CDM) Process Overview 11/20/2017Katalyst Healthcares & Life Sciences 1
  • 2. Icons Used Questions Demonstration Hands on Exercise Coding Standards A Welcome Break Tools 2 ReferenceTest Your Understandin g Contacts Icons Used 11/20/2017Katalyst Healthcares & Life Sciences
  • 3. Clinical data management includes theentry, 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 managementof clinical trial data. Review and approval of new drugs by Regulatoryagencies is dependent upon the integrityof clinical trial data which is the core purpose of CDM. Overview 3 Overview 11/20/2017Katalyst Healthcares & Life Sciences
  • 4. After this chapter you will be able to understand: • Overview of Clinical Data Management • Process flow of data managementactivities • Activities performed during the course of a trial • Analysis and reporting process overview • Roles and responsibilitiesof all personals involved in CDM Objectives 4 11/20/2017Katalyst Healthcares & Life Sciences
  • 5. ✓ The average numberof 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 discrepancyor a Database update can lead to Database unlock Do You Know 5 11/20/2017Katalyst Healthcares & Life Sciences
  • 6. Abbreviations 6 CRF Case Report Form DB Database QC Quality Control DMP Data Management Plan CSR Clinical Study Report UAT User Acceptance Testing 11/20/2017Katalyst Healthcares & Life Sciences
  • 7. Definition of Clinical Trial It is a systematicstudy of new drug(s) in human subject(s) togenerate data for discovering and/orverifying the clinical, pharmacological (pharmacokineticand Pharmacodynamics), and/oradverse effects with the objectiveof determining safety and /or efficacy of the a new drug. 711/20/2017Katalyst Healthcares & Life Sciences
  • 8. Clinical Trial Phases  Phase I Trials —Involvea 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 effectivenessof the drug and to determine the common short-term side effects and risks associated with the drug  Phase III Trials —Involves thousandsof patients to generate statisticallysignificantdata about safety, efficacy, and an overall benefit/risk profile  Phase IV Trials —Certain post marketing studies to find out additional informationabout the drug's risks, benefits, and its optimal use. 811/20/2017Katalyst Healthcares & Life Sciences
  • 9. 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 9 11/20/2017 Katalyst Healthcares & Life Sciences
  • 10. 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 11/20/2017Katalyst Healthcares & Life Sciences
  • 11. 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 11/20/2017Katalyst Healthcares & Life Sciences
  • 12. Definition of Data  Data with reference to CDM means the Patient Informationwhich is collected during Clinical trial.  Data is collected to establish whether the objective of the Clinical Trial is met 1211/20/2017Katalyst Healthcares & Life Sciences
  • 13. Objectives of CDM 13 Data Collection Data integration System / Data Validation Paper, Electronicand Remote data capture Integration of data received from all sources in a single DB. Ensures consistencyand correctness System validation done via UAT, QC and Programming Data Validation via Edit check programs and manual review 11/20/2017Katalyst Healthcares & Life Sciences
  • 14. Scope of CDM  Main scope of CDM is to Collect, Validateand Analyze the clinical data  Design and developmentof data collection instrumentsuch as Paper CRF, Electronic CRF, Clinical database etc  Design and developmentof tools for Validation such as Edit Checks, User AcceptanceTesting etc  Design and developmentof tools for Analyzing data such as DDR/DDS (Derived Dataset Requirement/Specification) etc. 1411/20/2017Katalyst Healthcares & Life Sciences
  • 15. 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 Managementensures:  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 1511/20/2017Katalyst Healthcares & Life Sciences
  • 16. 16 Inter-dependent groups in CDM Data Cleaning BiostatisticsProgramming Clinical Data Management 11/20/2017Katalyst Healthcares & Life Sciences
  • 17. 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 1711/20/2017Katalyst Healthcares & Life Sciences
  • 18. 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 submissionpackage is assembled and complete 1811/20/2017Katalyst Healthcares & Life Sciences
  • 21. 21 Study Start-up Process Protocol CRF Design Database Design Validation/ Derivation Procedures Activated database ready to accept production data 11/20/2017Katalyst Healthcares & Life Sciences
  • 22. 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 Validationand 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 2211/20/2017Katalyst Healthcares & Life Sciences
  • 23. 23 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 11/20/2017Katalyst Healthcares & Life Sciences
  • 24. 24 Study Conduct –Roles and Responsibilities Data Entry/Data Loaders-Manuallyenter 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 -Identifyand 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 DictionaryCoders -Code medical terms collected during clinical trial. Example: Medicationsand Adverse events
  • 25. 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 compliancewith industryand governmentregulations. 25 Electronic Data Capture Paper Data Capture Remote Data Capture Data Capture 11/20/2017Katalyst Healthcares & Life Sciences
  • 26. Difference between Data Capture Tools 26 The difference between Paper, Electronicand 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 11/20/2017Katalyst Healthcares & Life Sciences
  • 27. CRF –DEMO Snap shot 27 11/20/2017Katalyst Healthcares & Life Sciences
  • 28. 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 completenessof the documents  Tracking missing documents 2811/20/2017Katalyst Healthcares & Life Sciences
  • 29. Data Entry & Verification Data Entry Processes isof 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 entrywith blind verification, where two people enter the data independentlyand 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 entrywith interactiveverification where the second entry operator resolves discrepancies between 1st & 2nd entry and is aware of the first entered values 2911/20/2017Katalyst Healthcares & Life Sciences
  • 30. 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 compliancewith protocol  Inclusion/exclusioncriteria not met 3011/20/2017Katalyst Healthcares & Life Sciences
  • 31. Data Review –Edit Checks  Consist of computer checks on the data to assure the validityand accuracy of the data  Validatedata manuallyagainst predetermined specifications  Primarily used to check the efficacy data unique to the current study 3111/20/2017Katalyst Healthcares & Life Sciences
  • 32. Edit Checks Types Range checks  To identify inaccurateor 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 (***). Consistencychecks  To highlight area where the data in the databaseare inconsistent  E.g. Adverse Eventstop date is always after AE start date Presence checks  To ensure completenessof data  E.g. SEX is missing 3211/20/2017Katalyst Healthcares & Life Sciences
  • 33. Data Query  A query is an official communication to the investigative site to question on a discrepant data on the case report form.  Subsequentchanges in the data must be supported by signed Data Clarification Form (DCF). EDC Query Data Clarification Form (DCF) 3311/20/2017Katalyst Healthcares & Life Sciences
  • 34. Medical Coding It is a process which involvesgrouping or classifying new and amended terms like medications, adverse events, medical history medical procedures, diagnoses, disease conditionswith reference to known standard terms as mentioned in medical dictionary Importanceof coding :  The use of medical coding dictionaries for medical term data such as adverse event, medical history, medications & treatments/procedures are valuable from the standpointof 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, analyzeand report collected data. 3411/20/2017Katalyst Healthcares & Life Sciences
  • 35. Medical Coding Dictionaries Coding Dictionaries: MedDRA Medical Dictionary for Regulatory Activities, is a standardized dictionaryof medical terminology WHO: WHOART, drugs World Health Organization Adverse Reaction Terminology ICD International Classificationof Diseases FDA-COSTART Coding Symbols for a Thesaurus of Adverse Reaction Terms 3511/20/2017Katalyst Healthcares & Life Sciences
  • 36. 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 SeriousAdverse Event: Any adverse event that leads to:  Results in death  Is life-threatening  Requires inpatient hospitalizationor  Prolongationof existing hospitalization  Results in persistentor significantdisability / incapacity  Is a congenital anomaly / birth defect 3611/20/2017Katalyst Healthcares & Life Sciences
  • 37. 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 acceptablediscrepanciesdocumented. All SAEs entered into the clinical trial database are also entered into the drug safety databaseand 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 subsequentaggregate reporting which occurs well after database lock. 3711/20/2017Katalyst Healthcares & Life Sciences
  • 38. Study Closeout Process 38 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 11/20/2017Katalyst Healthcares & Life Sciences
  • 39. 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 pointsare met:  Data is complete i.e., No missing data  Data is consistent  Data is accurate  Data is reliable 3911/20/2017Katalyst Healthcares & Life Sciences
  • 40. 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 11/20/2017Katalyst Healthcares & Life Sciences
  • 41. 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. 4111/20/2017Katalyst Healthcares & Life Sciences
  • 42. 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. 4211/20/2017Katalyst Healthcares & Life Sciences
  • 43. Quality Assurance Quality Assurance: “All those planned and systematicactions that are established to ensure that the trial is performed and the data are generated, documented (recorded), and reported in compliancewith Good Clinical Practice (GCP) and the applicable regulatory requirement(s). Involves Inspectionsand Audits  Inspection is by Governmental Agencies, Health Authorities and the Drug Regulatory Authorities  Auditing is by pharmaceutical, devices companies, CROs, and others 4311/20/2017Katalyst Healthcares & Life Sciences
  • 44. Audits Types Internal audit (first party audit):  Carried out by service provider’s Audit Department toensure implementing, maintaining and improvementof the system audited. Customeraudit (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. 4411/20/2017Katalyst Healthcares & Life Sciences
  • 45. Benefits of Internal Audit  Audit of processes to identifysystemic 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 4511/20/2017Katalyst Healthcares & Life Sciences
  • 46. 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.  Statisticiansuse the programmed reports and listingsand analyze the data as per a pre approved statistical plan. 4611/20/2017Katalyst Healthcares & Life Sciences
  • 47. A & R –Tables & Listings snap shot 47 11/20/2017Katalyst Healthcares & Life Sciences
  • 48. Roles & Responsibilities Medical Writers – Generate Clinical Study Report, using the statistical analysis and other study documents thus summarizing the overall findings and conclusionsof a clinical trial. The CSR is used for submissionto the regulatory authorities 4811/20/2017Katalyst Healthcares & Life Sciences
  • 49. 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 11/20/2017Katalyst Healthcares & Life Sciences
  • 71. Slide No. 71 • QS CRS Quality Services / Svend Martin Fransen • 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 11/20/2017Katalyst Healthcares & Life Sciences
  • 72. Slide No. 72 • QS CRS Quality Services / Svend Martin Fransen • 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 11/20/2017Katalyst Healthcares & Life Sciences
  • 73. Slide No. 73 • QS CRS Quality Services / Svend Martin Fransen • 03.Oct.2002 FDA 21CFR11 inspection questions (source: : 21CFR11 ComplianceReport, 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 validationactivities?  Does the validation include: “Pass/fail, signature, date/timestamp”; and “objectiveevidence - screen prints or page printouts with a link to the direction that generated the output.”? 11/20/2017Katalyst Healthcares & Life Sciences
  • 75. 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 75 11/20/2017Katalyst Healthcares & Life Sciences
  • 76. In this session we have understood the following points: ● What is Clinical Research? ● What is Clinical Data Management? ● Importanceof CDM ● CDM work flow ● Roles and Responsibilities across all processes ● Activities performed by Data Managers in Clinical Research Summary 76 11/20/2017Katalyst Healthcares & Life Sciences
  • 77. • Practical Guide to Clinical Data Management; Second Edition: by Susanne Prokscha • COMPUTERIZED SYSTEMS USED IN CLINICAL TRIALS, U.S. Departmentof Health and Human Services, Food and Drug Administration • http://en.wikipedia.org/wiki/Clinical_trial Source 77 11/20/2017Katalyst Healthcares & Life Sciences
  • 78. Thank You & Questions 11/20/2017 78 Contact: Katalyst Healthcare’s & Life Sciences South Plainfield, NJ, USA 07080. E-Mail: info@KatalystHLS.com