Introduction to Data management services

Investigator Monitor
Involved
Laboratories
Data Manager
Statistician
Clinician
Regulatory
Authority
Subject
Diary
CRF
DCF
CRF DCF
Sample
Lab
Results
Clinical
Data
NDA
It’s all about data

What is CDMS?
• A clinical data management system or CDMS
is used in clinical research to manage the data
of a clinical trial
• It is set up to help with processing data from
source through validation checks, analysis,
reporting and storage;
• Also useful for Coding (particularly for AEs and
Medications)
– MEDRA (Medical Dictionary for Regulatory Activities)
– WHOART (WHO Adverse Reactions Terminology)

Institutional Approach
• Setting up a specific CDMS requires institutional
decision making at policy level
• Whatever the choice, it comes with a cost
• Requires infrastructure and equipment set up
• Requires minimum core competencies
• Dedicated time for learning and development
• Opportunities to try out

Preferred Software characteristics
• Standards based
• Well known  many skilled practitioners available
• Readily mastered and modified
• Should run on any platform
• Should be affordable for small groups in resource
constrained countries

Why an open source approach?
• Potential advantages of Open Source solution
– Cheaper
– More amenable to change
– No vendor lock in
– More able to be integrated with other systems
– Likely to be well documented
– Designed to be multilingual
– Open source software works eg R, Apache, MySQL
– Used by major IT players eg Google, HP & IBM
– Has been argued provides better software
• saved the Human Genome Project according to Lincoln Stein

Introducing OpenClinica
Free, open source, web-based software for EDC built by
Akaza Research
Features:
– Management of diverse clinical studies through a unified interface
– Clinical data entry and validation
– Data extraction
– Study oversight, auditing, and reporting

Designing a database in OC; requirement and flow of data.
Define CRFs in Excel Temp.
CRF Design, validation and
import
Submit data Module; Web-
based Data entry and validation
OC - DataBase
Clinical Case Report Forms (CRF)
Creating Data Bases in OpenClinica

A part of CRF Excel Template: “Some tricks”.
Data Base Creating in OpenClinica

Defining CRF on Excel Template
ITEM_NAME - This is the unique label or variable name for this data element.
DESCRIPTION_LABEL - give an explanation of the data element and the value(s) it captures.
UNITS - the units that the value of this data element should be captured in.
GROUP_LABEL - grouped items will display as a row within a table.
COLUMN_NUMBER - allow adjacent items or items with the same parent to be aligned
together.
RESPONSE_OPTIONS_TEXT - list of the text values of the responses for this response set
as a comma-delimited string.
RESPONSE_VALUES_OR_CALCULATIONS - comma-delimited list of the encoded values.
DATA_TYPE - data type; ST, INT, REAL, DATE.
VALIDATION - validation expression to run an edit check on this item
VALIDATION Expression - Expression Type:
1) regexp - Supports Java-style regular expressions. regexp: /regular expression/ e.g
regexp: /[A-Z]{3}/, requires a three-letter string (all uppercase)
2) func - Supports built-in library of basic integer functions. func: func(args) e.g func:
range(1, 10), func: eq(1), func: gte(10.5) etc.
Creating Databases in OpenClinica

• Developed using Java J2EE framework
• Application Server- Tomcat 5.x
• Uses JDBC with JSP based front-end.
• Database PostgreSQL 8.x or Oracle 10g
– custom ports to DB2, SQL Server, or MySQL also
possible
– Has 74 related tables
The Back End of OpenClinica

• Organization of clinical research by study protocol and site.
• Dynamic generation of web-based CRFs in portable Excel templates.
• Management of longitudinal data for recurring patient visits
• Data import/export tools for migration of clinical datasets.
• Interfaces for data query and retrieval across subjects, time, and clinical
parameters
• Compliance with regulatory guidelines e.g. 21 CFR Part 11
• Built on robust and scalable technology infrastructure interoperable with
relational databases
Important Features of OpenClinica

Done in excel using a blank CRF template
provided by Openclinica
Designing CRFs

Introduction to Data management services

The excel sheet is then uploaded onto OpenClinica
Uploading CRFs

• Backups implemented via a scheduled command
running as a batch file that writes out the data
and metadata for each of the studies databases
adding Timestamp information to the filename.
PgDump utility Creates a backup file
on the secondary HDD on the main
server. File automatically copied to
NAS1
NAS1
Database
Database
server
The Back Up Setting

• Installing Application Stack I.E. Postgresql, Apache
Jarkata Tomcat,J2SE runtime environment and
Deploying OpenClinica
• Using a suitable Postgres database GUI(e.g.
pgadmin III) create a new blank database on the
database server
• Run the pg_restore command on the server and
select the backup file to restore
Restore Process

• OC is deployed a as Openclinica.war file “Web Application
archive“. It is a JAR(JAVA ARCHIVE) file used to distribute a collection of Java
Server Pages, servlets, Java classes, XML files, tag libraries and static Web pages
(HTML and related files) that together constitute a Web application.
• Standard Installation Process is well documented inside
an instructions file that ships with the application.
• To deploy separate instances, rename the
Openclinica.war to [studyname].war
• Deploy as a normal OC application using the standard
procedure and effect changes in database credentials
inside the datainfo.properties of the deployed web
Application.
Deploying O/C for Multiple Sites

• Policy determination needed
• Required human and material resources allocated
• When know-how is established, utilization requires
only 5 main steps:
– Designing
– Creating CRF’s
– Event definitions
– Data Entry
– Data Extraction
Working with OpenClinica

• O/C by design, is compliant to the most stringent
regulatory requirements
• O/C is designed to be compliant to FDA 21 CFR Part 11-
Electronic Records; Electronic Signatures
• These are guidelines that govern the use of electronic
records and signatures ; and can be summarized in two
broad categories:
– Technology best practice
– Policy and procedures best practice
GCP Regulations and OpenClinica

• Audit trail must be independently generated
• Ensure that system maintains a “irrefutable link” between documents,
metadata and the electronic signature.
• Establish clear electronic signature manifestations for all electronic
records.
• Validate the system.
• Establish role-based access and control.
• Establish password and identification controls.
• Series of signings.
• Avoid hybrid systems, where practical.
• Do not over customize technology solutions.
Technology Best Practices

• Establish corporate internal policies and guidelines for:
– Validation and procedures
– Disaster recovery
– Revision and change control procedures
– System access and security procedures
– Training procedures
– Document control procedures
• Develop a clear, comprehensive migration strategy.
• Understand the impact of “open” or “closed” system
definitions.
• Establish retention policies based on current predicate rule
requirements.
Policy & Procedures Best Practices

Introduction to Data management services

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