An brief introduction to the clinical data management process is described in this slides. These slides provides you the information regarding the data evaluation in the clinical trials , edit checks and data review finally data locking,then the data is submitted to the concerned regulatory body.
An overview of ICH-GCP guidelines of clinical trials.
Good clinical practice (GCP): a standard for the design , conduct, performance, monitoring, auditing, recording, analyses and reporting of clinical trials that provides assurance that the data and reported results are credible and accurate and that the rights, integrity, and confidentiality of trial subjects are protected.
ICH-GCP is an International Conference on Harmonization Good Clinical Practice.
The guideline was developed with consideration of the current good clinical practices of the European union, Japan, and the United States, as well as those of Australia, Canada, the Nordic countries and the world health organization
When a new drug/device/surgical procedure/treatment or other potential medical innovation is developed it must be thoroughly tested to ensure that it is safe and does what it is supposed to be.
This presentation will provide a basic overview of clinical research process.
“CSR is a detailed regulatory document which gives the information about the methods and results (related to efficacy and safety) of a clinical trial. CSRs are created as a part of the process of submitting applications to the Regulatory Authorities for new medical treatments and for its approval. CSRs can be full, abbreviated, synopsis, supplementary, observational etc as per the results and requirements”.
Table of contents
-Definition of CRF
-What is CRF
-Types & Methods of filling of CRF
-CRF Input team
-CRF Approval team
-Review team
-Facts about CRF
-Purpose of CRF
-CRF Development process & Guidelines
-Elements of CRF
-CRF Design
-CRF completion checklist
-CRF Design tools
-CRF use
-GCP connection
An overview of ICH-GCP guidelines of clinical trials.
Good clinical practice (GCP): a standard for the design , conduct, performance, monitoring, auditing, recording, analyses and reporting of clinical trials that provides assurance that the data and reported results are credible and accurate and that the rights, integrity, and confidentiality of trial subjects are protected.
ICH-GCP is an International Conference on Harmonization Good Clinical Practice.
The guideline was developed with consideration of the current good clinical practices of the European union, Japan, and the United States, as well as those of Australia, Canada, the Nordic countries and the world health organization
When a new drug/device/surgical procedure/treatment or other potential medical innovation is developed it must be thoroughly tested to ensure that it is safe and does what it is supposed to be.
This presentation will provide a basic overview of clinical research process.
“CSR is a detailed regulatory document which gives the information about the methods and results (related to efficacy and safety) of a clinical trial. CSRs are created as a part of the process of submitting applications to the Regulatory Authorities for new medical treatments and for its approval. CSRs can be full, abbreviated, synopsis, supplementary, observational etc as per the results and requirements”.
Table of contents
-Definition of CRF
-What is CRF
-Types & Methods of filling of CRF
-CRF Input team
-CRF Approval team
-Review team
-Facts about CRF
-Purpose of CRF
-CRF Development process & Guidelines
-Elements of CRF
-CRF Design
-CRF completion checklist
-CRF Design tools
-CRF use
-GCP connection
Have full fleged clinical trial data management systems which bring them a good amount of business and revenue.
CDM is a fundamental process which controls data accuracy of each trial besides helping the timelessness to be achieved.
It helps in linking clinical research co-ordinator = who monitor all the sites & collects the data.
it Links with biostatisticians = who analyze, interpret and report data in clinically meaningful way.
Electronic Data Capture & Remote Data CaptureCRB Tech
CRB Tech is one of the best leading Software Development Company in Pune. We are offering Software Development Services as well as IT Training including Java, Dot Net, SEO and Clinical Research training in pune.
Visit:www.acriindia.com
ACRI is a leading Clinical data management training Institute in Bangalore India.
ACRI creates a value add for every degree. Our PGDCRCDM course is approved by the Mysore University. Graduates and Post Graduates and even PhDs have trained with us and got enviable positions in the Clinical Research Industry. ACRI supplements University training with Industry based training, coupled with hands-on internships and projects based on real case studies. The ACRI brand gives the individual the confidence and expertise to join the ever-growing workforce both in the country and abroad.
Everything related to CDM. Importance of CDM, Flow Activities in Clinical Trials, Data Management Plan, Database Designing, Data Management tools, Essential Characters of the database, Standard Global Dictionaries, Data Review and Validation, Query Generation, Database Lock, Technology in CDM, and Professionals of CDM.
Have full fleged clinical trial data management systems which bring them a good amount of business and revenue.
CDM is a fundamental process which controls data accuracy of each trial besides helping the timelessness to be achieved.
It helps in linking clinical research co-ordinator = who monitor all the sites & collects the data.
it Links with biostatisticians = who analyze, interpret and report data in clinically meaningful way.
Electronic Data Capture & Remote Data CaptureCRB Tech
CRB Tech is one of the best leading Software Development Company in Pune. We are offering Software Development Services as well as IT Training including Java, Dot Net, SEO and Clinical Research training in pune.
Visit:www.acriindia.com
ACRI is a leading Clinical data management training Institute in Bangalore India.
ACRI creates a value add for every degree. Our PGDCRCDM course is approved by the Mysore University. Graduates and Post Graduates and even PhDs have trained with us and got enviable positions in the Clinical Research Industry. ACRI supplements University training with Industry based training, coupled with hands-on internships and projects based on real case studies. The ACRI brand gives the individual the confidence and expertise to join the ever-growing workforce both in the country and abroad.
Everything related to CDM. Importance of CDM, Flow Activities in Clinical Trials, Data Management Plan, Database Designing, Data Management tools, Essential Characters of the database, Standard Global Dictionaries, Data Review and Validation, Query Generation, Database Lock, Technology in CDM, and Professionals of CDM.
Clinical Data Management Plan_Katalyst HLSKatalyst HLS
Introduction to Data Management Plan in Clinical Data Management in Clinical Trials of Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
Study start up activities in clinical data managementsoumyapottola
Study start-up (SSU) is so much more than a one-time document management exercise. It’s a global, strategic operation that can get new drugs approved faster – and it’s ripe for innovation – from Site Selection to Site Activation and Site Training.
Many SSU tech solutions deployed by sponsors don’t deliver the results promised because they add burden without benefits to clinical research sites. The result? Site staff simply avoid using them.
When that happens, document exchange and tracking falls back to paper, email and Excel formats – with CRAs holding the processes together. The tools that were supposed to solve a problem become part of the problem – and consume preThe implementation and conduct of a study can be a complex process that involves a
team from various disciplines and multiple steps that are dependent on one another. This
document offers guidance for navigating the study start-up processcious clinical trial budget.
A successful clinical study start-up is a crucial first step and an important factor for the overall success of the trial. For this reason, SCRO has experienced study start-up teams, offering customized services depending on your needs, whether it be fuWhile the definition varies across companies, study startup typically includes the process of identifying and qualifying sites, collecting essential documents at the study and site level, and submitting these documents for ethics approval. Successful study startup requires coordination between sites, sponsors, and contract research organizations (CROs) to achieve critical milestones in a compliant manner.ll-service or single activities.
How to achieve better time management in EDC start up
Clinical data management requires strict time management processes, especially in study start up within an electronic data capture (EDC) system. Three steps that clinical data management teams can take to outline the planning and executing of each task that needs to be considered are as follows:
Make a List: Create a daily or weekly task list and schedule when each task will be completed. This strategy will assist you in maintaining focus and staying organized.
Set realist goals: Be realistic about what you can finish in the amount of time you have. When setting unrealistic goals, failure is almost certain to follow.
Explore time-saving techniques: Examples of techniques that could help save time include grouping similar tasks together or using a timer to stay focused.
To help get started, here is a list of EDC considerations for Study Start-Up deadlines:
Protocol finalization and study enrollment
Split go-live considerations
eCRF Specification meetings (this will ensure proper collaboration and minimize any back-and-forth communication)
EDC add-on modules (which will be required and need validation?)
ePRO/eCOA used with licensed questionnaires.
IRB requirements for add-on modules (eConsent/ePRO)
Clinical Data management is one of the vital part of clinical research.
Clinical research is research on drugs,devices ,medicines that has to be adminstered for various diseases and illness,to check the efficacy and safety in human voluteers or patients.
It helps in determining dose and dosages of a particular drug or treatment regimen.CR also helps in label expansion of investigational drug. Furthermore it helps in checking any adverse event in post marketed drug which increases the potability of drug among population of various geographical regions.There are various guidelines and regulatory bodies from several parts of world . Each country has its own regulatory body both at state and central level,eg.CDSCO for India,TGA for Australia,USFDA for USA,MCC for South Africa ,UNCST for Uganda,EMEA for European Union,MHRA for UK.Thus CDM plays important role in maintaining accuracy,consistencies,validity reliabilty of available data.It also in decreasing redundancy of duplicate and inconsistent data.It is required to resolve issues pertaining to inaccuracy , signal detection in pharmacovigilance. CDM is completed in three steps set up,conduct ,close out.Database used i n cdm are DBMS ,MS -Access,OC-RDC.Data managers,operators,programmers,developers are include in the process.CDMS Clinical data management system ,clinical system validation.
Revelatory Trends in Clinical Research and Data ManagementSagar Ghotekar
Revelatory Trends in Clinical Research and Data Management
Clinical data management is a heart and important part of a clinical trials, the outcome to generate quality data and accounting of records to protect clinical trial participants data leads to highest quality and integrity of clinical trials.
Data Management and Analysis in Clinical Trialsijtsrd
Data management and analysis play a critical role in the successful conduct of clinical trials. Proper collection, validation, and handling of data are essential for ensuring the reliability and integrity of study findings. Data management involves the design and implementation of data capture tools, such as electronic case report forms eCRFs, to efficiently collect and store clinical data. Additionally, data analysis is a crucial step that involves applying statistical methods to extract meaningful insights from the collected data. This paper provides an overview of the key components of data management and analysis in clinical trials, highlighting the importance of adherence to data standards, ensuring data quality, and maintaining data security. Effective data management and analysis not only lead to robust study outcomes but also contribute to the overall advancement of medical knowledge and patient care. S. Reddemma | Chetana Menda | Manoj Kumar "Data Management and Analysis in Clinical Trials" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-4, August 2023, URL: https://www.ijtsrd.com/papers/ijtsrd59667.pdf Paper Url:https://www.ijtsrd.com/pharmacy/pharmacology-/59667/data-management-and-analysis-in-clinical-trials/s-reddemma
Clinical data management (CDM) is a covered part in the clinical trial and most commonly used tools for the purpose of effectivity of clinical research
Data Validation in Clinical Data ManagementClinosolIndia
Data validation is a crucial component of Clinical Data Management (CDM) to ensure the accuracy, completeness, and consistency of clinical trial data. It involves the systematic and rigorous examination of data to identify and address errors, inconsistencies, or discrepancies. Effective data validation enhances the integrity of the clinical trial data and is essential for regulatory compliance and the generation of reliable results. Here are key aspects of data validation in CDM
Clinical Data Management Interview Question Part 1ClinosolIndia
Embarking on a career in Clinical Data Management requires a thorough understanding of the intricacies involved in handling and processing clinical trial data. In this presentation, we explore key interview questions that shed light on the critical aspects of CDM, helping both aspiring professionals and seasoned experts stay abreast of industry trends and expectations.
Database Designing in Clinical Data ManagementClinosolIndia
When designing a Clinical Data Management (CDM) database, several key considerations should be taken into account to ensure efficient data capture, storage, and retrieval. Here are some important aspects to consider in CDM database design:
Define Study Requirements:
Understand the specific requirements of the study and the data to be collected. This includes variables, data types, formats, and any specific rules or calculations required for data validation and derivation. Consult with the study team and stakeholders to determine the necessary data elements.
Data Model Design:
Develop a data model that represents the structure and relationships of the data. Use standard data models, such as CDISC (Clinical Data Interchange Standards Consortium) standards, as a foundation. Define entities (e.g., patients, visits, assessments) and attributes (e.g., demographics, lab results) and establish relationships between them.
Data Dictionary:
Create a comprehensive data dictionary that provides a detailed description of each data element, including its name, definition, data type, length, format, allowable values, and any validation or derivation rules. The data dictionary serves as a reference for data entry and validation checks.
Database Schema:
Design the database schema based on the data model and data dictionary. Identify the tables, fields, and relationships needed to store the data. Determine primary and foreign keys to establish relationships between tables. Normalize the schema to reduce redundancy and improve data integrity.
Data Capture Forms:
Design user-friendly data capture forms to facilitate efficient and accurate data entry. Align the form layout with the data model and data dictionary. Include necessary data validation checks and provide clear instructions or prompts for data entry.
Data Validation and Quality Checks:
Incorporate data validation checks to ensure data accuracy and completeness. Implement range checks, format checks, consistency checks, and logic checks to identify and prevent data entry errors. Include data quality control processes to identify and resolve data discrepancies or anomalies.
Security and Access Controls:
Implement appropriate security measures to protect the confidentiality, integrity, and availability of the data. Define user roles and access levels to control data access and modification. Employ encryption, authentication, and audit trails to ensure data security and compliance with regulatory requirements.
Data Extraction and Reporting:
Consider the need for data extraction and reporting capabilities. Design mechanisms to extract data from the database for analysis or reporting purposes. Implement data export functionalities in commonly used formats, such as CSV or Excel, or integrate with reporting tools or systems.
As an expert provider of a wide spectrum of clinical development support services, KCR has developed
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all the while ensuring the meeting of all Good Clinical Practice (GCP) and ICH requirements. Read our DM brochure and learn more about KCR DM capabilities.
Integrating Clinical Operations and Clinical Data Management Through EDCwww.datatrak.com
When electronic data capture was first introduced there was a great deal of discussion surrounding how the technology would alter the roles of those in clinical operations and clinical data management. Through the review of a case study, we will explore how EDC is used as a tool to more tightly integrate clinical operational staffs with those in clinical data management resulting in a more streamlined process from study initiation to database lock.
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
Dr Sujoy Dasgupta presented the study on "Couples presenting to the infertility clinic- Do they really have infertility? – The unexplored stories of non-consummation" in the 13th Congress of the Asia Pacific Initiative on Reproduction (ASPIRE 2024) at Manila on 24 May, 2024.
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
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micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
2. What is Clinical
Data Management
Clinical Data Management is
involved in all aspects of
processing the clinical data,
working with a range of computer
applications, database systems to
support collection, cleaning and
management of subject or trial
data.
3. • Clinical Data Management is the
collection, integration and validation of
clinical trial data
• During the clinical trial, the investigators
collect data on the patients' health for a
defined time period. This data is sent to
the trial sponsor, who then analyzes the
pooled data using statistical analysis.
4. Why CDM
• Review & approval of new drugs by
Regulatory Agencies is dependent upon a
trust that clinical trials data presented are
of sufficient integrity to ensure
confidence in results & conclusions
presented by pharma company
• Important to obtaining that trust is
adherence to quality standards &
practices
• Hence companies must assure that all
staff involved in the clinical research are
trained & qualified to perform data
management tasks
5. Key Members
• Project Manager /Data Manager
• Database Administrator
• Database Programmer / Developer
• Clinical Data Associate
The Key members involved in Data Management:
8. 1. Clinical Investigator
2. Site coordinator
3. Trial Pharmacists
4. Biostatistician
5. Lab Coordinator
6. Project manager
7. Clinical Research
Manager/Associate
8. Monitor
9. Ethics committee
10. Regulatory affairs
11. Clinical Data Management
12. Pharmacovigilance
13. IT/IS personnel
14. Clinical supply
15. Auditor/Compliance
Multidisciplinary Teams in Clinical Trials
9. Responsibilities of CDM
Study Setup
• CRF design and development (paper/e-CRF)
• Database build and testing
• Edit Checks preparation and testing
Study Conduct
• Data Entry
• Discrepancy Management
• Data Coding (using MedDRA and WHODDE dictionaries)
• Data review (Ongoing QC)
• SAE Reconciliation
• Data Transfer
Study Closeout
• SAE Reconciliation
• Quality Control
• Database Lock
• Electronic Archival
• Database Transfer
12. CRF Design/Review
A representation of the study as outlined in the protocol is made
(including CRF completion guidelines if necessary). Therefore a final
protocol needs to be available before this activity can be initiated.
CRF design usually takes about three rounds: First draft (rough without
detail but correct content), second draft (as good as we can get it) and
final version. We need input from our sponsor to correct draft versions
and to approve the final version.
QADATA EDC
• Traditional Paper Based Case Report Forms
• e-CRF (Electronic Case Report Form)- Study information directly
entered into computer.
14. How many CRFs do you need?
• Eligibility or Screening
• Randomisation
• Physical Exam / Vitals
• Medical History
• Follow-up Visit
• AE form/ SAE form
• Concomitant therapy form
• Laboratory test form
• Status Evaluation
15. Data Base Design
Data from a clinical trial will be
collected and stored in the CDMS
A database is simply a structured
set of data.
A collection of rows and columns.
--QAData CDMS
16. DBMS:
MS Access, MS Excel
Oracle Clinical
Clintrial
Phaseforward InForm
medidata Rave
17. CRF Annotation
• An annotated CRF is generally defined as a
blank CRF with markings, or annotations,
that coordinate each data point in the form
with its corresponding dataset name.
• Essentially, an annotated CRF
communicates where the data collected for
each question is stored in the database.
• CRF Annotation is the first step in
translating the CRFs into a database
application.
• CDM annotates the CRFs by establishing
variable names for each item to be entered.
• Reviewed by CDM and Statistician
18.
19. Validation Checklist:
Edit specifications list describes in detail which data
shall be checked and queried if necessary. The
programming of the checks occurs according to this
list. Before the programming starts, the sponsor will
be asked to give approval of this list.
Test subjects are entered in the database to test the
entry screens and the programming. The exact
number of test subjects is not standard, but every
check has to pass and fail (negative and positive
proof) at least once.
20. Database set up and testing
Database setup and testing are always performed in a secure,
non study data environment (test site). Only when a database
has been reviewed and fully tested, will it be set in
‘production’, a separate environment where only study data
will be entered.
Changes in structure or programming will always first be
performed and tested in the non study data environment
before they are made effective in the ‘production’ database.
21.
22.
23. Logistic way if it is paper based study.
EDC-electronic data capture if it is e-CRF.
Data Entry
Data entry is a process of
entering/transferring data from case
report form to the Clinical Data
Management System (CDMS).
Data Entry: 1) Single data Entry
2) Double Data Entry
CRF Tracking
Data Entry
24. Discrepancy Management
Discrepancy management is a process of
cleaning subject data in the Clinical Data
Management System (CDMS), it includes
manual checks and programmed checks.
Trivial discrepancies are closed as per self
evident correction method or Internal
rulings and discrepancies which require
response from the site are queried by
raising Data Clarification Forms (DCF).
25. Medical Coding
The medical coding for a study is done as per
the project specific protocol requirement. The
dictionaries used for a study are:
Adverse Events: MedDRA (Medical Dictionary
for Regulatory Activities)
Medications: WHODD (World Health
Organization – Drug Dictionary)
26. SAE Reconciliation
• Serious Adverse Event (SAE)
data reconciliation is the
comparison of key safety data
variables between Clinical Data
Management System (CDMS)
and Sponsor PV. Reconciliation is
performed to ensure that events
residing in both systems are
consistent.
27.
28. • Quality Should be maintained for overall study by performing
Quality checks at intervals for all data points (Critical & Non-
Critical) prior to database lock.
• QC helps to ensure that all the data processed is accurate,
clean and Correct.
Quality Control
29.
30. The database lock for a study is done to
ensure no manipulation of study data
during the final analysis.
Database lock for a study is done
once all data management activities are
completed. This includes the database
lock checklist which ensures the same.
Some of the activities included in
database lock checklist are All
discrepancies closed, DCFs received and
updated, coding complete, SAE
Reconciliation process complete etc.
Database Lock
31.
32. • CDM is a vital vehicle in Clinical Trials to ensure:
• The Integrity & quality of data being transferred from trial
subjects to a database system
• That the collected data is complete and accurate so that
results are correct
• That trial database is complete and accurate, and a true
representation of what took place in trial
• That trial database is sufficiently clean to support statistical
analysis, and its subsequent presentation and
interpretation
33. Importance of CMD
CDM has evolved from a mere data entry process to
a much diverse process today
• It provides data and database in a usable format
in a timely manner
• It ensures clean data and a ‘ready to lock’
database
34. CDM Professionals
• ICH.E6.5.5.1: Utilize qualified individuals
to:
• Supervise overall conduct of trial (Project
Manager)
• To handle and verify the data (Data
Manager)
• To conduct the statistical analysis
(Biostatistician)
• To prepare study reports (Medical Writer)
35. DM Role in Clinical Research
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
36. DM Role in Clinical Research
Data management starts with the creation
of the study protocol
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
