A data management plan (DMP) ensures consistent and effective clinical data management practices throughout a clinical trial. The DMP describes all data management activities, roles, and responsibilities to promote standardized data handling. It provides an agreement between parties on data management deliverables. The DMP covers components like data flow, capture, setup, entry, transfer, processing, coding, safety handling, external data, and database locking. It serves to plan, communicate, and reference data management tasks. Developing a thorough DMP helps ensure quality and regulatory compliance in data collection and analysis.
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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.
Clinical Data Management (CDM) is a critical component of clinical research that involves the collection, cleaning, validation, and management of clinical trial data to ensure its accuracy, integrity, and compliance with regulatory requirements. The workflow of CDM typically consists of several key stages, each with specific activities and processes. Here is an overview of the typical workflow of CDM:
Study Startup:
Protocol Review: CDM teams begin by reviewing the clinical trial protocol to understand the study's objectives, endpoints, data collection requirements, and timelines.
Database Design: Based on the protocol, the team designs a data capture system or electronic data capture (EDC) system. This includes creating data entry forms, defining data validation checks, and setting up data dictionaries.
Data Collection:
Case Report Form (CRF) Design: CDM professionals design electronic or paper CRFs to collect data during the trial. CRFs capture specific data points required by the protocol.
Data Entry: Data is entered into the CRFs, either electronically by site personnel or through paper CRFs.
Data Validation: CDM teams implement validation checks to ensure data quality and consistency. Data validation checks may include range checks, consistency checks, and logic checks.
Query Management: Queries are generated when data discrepancies or inconsistencies are identified. CDM teams send queries to investigational sites for resolution.
Data Cleaning and Quality Control:
Data Cleaning: Data are cleaned to resolve discrepancies, discrepancies, and inconsistencies. This involves querying data discrepancies with clinical trial sites.
Data Review: CDM teams review data to ensure completeness and accuracy, and any outstanding queries are resolved.
Quality Control: Quality control processes are applied to verify the integrity and accuracy of data.
Database Lock:
Once the data are cleaned, reviewed, and validated, the database is locked, indicating that no further changes can be made to the data. Database lock is a critical step before data analysis begins.
Data Export and Analysis:
Data is exported from the database and provided to biostatisticians and researchers for statistical analysis. This analysis is conducted to determine the study's outcomes, efficacy, and safety profile.
Data listings, summaries, and tables are generated for regulatory submissions, reports, and publications.
Final Study Reporting:
After data analysis, CDM teams contribute to the preparation of final study reports, which provide a comprehensive overview of the trial's results, data quality, and regulatory compliance.
Archiving and Documentation:
Clinical trial data, documentation, and databases are archived to ensure their long-term availability for regulatory audits and future reference.
Regulatory Submission: CDM teams provide support for regulatory submissions.
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.
Clinical Data Management (CDM) is a critical component of clinical research that involves the collection, cleaning, validation, and management of clinical trial data to ensure its accuracy, integrity, and compliance with regulatory requirements. The workflow of CDM typically consists of several key stages, each with specific activities and processes. Here is an overview of the typical workflow of CDM:
Study Startup:
Protocol Review: CDM teams begin by reviewing the clinical trial protocol to understand the study's objectives, endpoints, data collection requirements, and timelines.
Database Design: Based on the protocol, the team designs a data capture system or electronic data capture (EDC) system. This includes creating data entry forms, defining data validation checks, and setting up data dictionaries.
Data Collection:
Case Report Form (CRF) Design: CDM professionals design electronic or paper CRFs to collect data during the trial. CRFs capture specific data points required by the protocol.
Data Entry: Data is entered into the CRFs, either electronically by site personnel or through paper CRFs.
Data Validation: CDM teams implement validation checks to ensure data quality and consistency. Data validation checks may include range checks, consistency checks, and logic checks.
Query Management: Queries are generated when data discrepancies or inconsistencies are identified. CDM teams send queries to investigational sites for resolution.
Data Cleaning and Quality Control:
Data Cleaning: Data are cleaned to resolve discrepancies, discrepancies, and inconsistencies. This involves querying data discrepancies with clinical trial sites.
Data Review: CDM teams review data to ensure completeness and accuracy, and any outstanding queries are resolved.
Quality Control: Quality control processes are applied to verify the integrity and accuracy of data.
Database Lock:
Once the data are cleaned, reviewed, and validated, the database is locked, indicating that no further changes can be made to the data. Database lock is a critical step before data analysis begins.
Data Export and Analysis:
Data is exported from the database and provided to biostatisticians and researchers for statistical analysis. This analysis is conducted to determine the study's outcomes, efficacy, and safety profile.
Data listings, summaries, and tables are generated for regulatory submissions, reports, and publications.
Final Study Reporting:
After data analysis, CDM teams contribute to the preparation of final study reports, which provide a comprehensive overview of the trial's results, data quality, and regulatory compliance.
Archiving and Documentation:
Clinical trial data, documentation, and databases are archived to ensure their long-term availability for regulatory audits and future reference.
Regulatory Submission: CDM teams provide support for regulatory submissions.
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.
Clinical Data Management: Best Practices and Key ConsiderationsClinosolIndia
Clinical data management (CDM) is a critical component of clinical research, involving the collection, processing, and analysis of data generated during clinical trials. Implementing best practices and considering key considerations is essential for ensuring data quality, integrity, and regulatory compliance. Here are some important considerations and best practices in clinical data management:
Data Standardization: Standardizing data collection and documentation across study sites is crucial for ensuring consistency and facilitating data analysis. Develop standardized data collection forms, case report forms (CRFs), and electronic data capture (EDC) systems that capture relevant data elements in a consistent manner.
Data Validation and Quality Control: Implement robust data validation procedures to ensure the accuracy and completeness of collected data. Conduct thorough quality control checks, including data validation checks, range checks, and consistency checks, to identify and resolve data discrepancies or errors.
Data Security and Privacy: Ensure data security and protect participant privacy by implementing appropriate measures such as data encryption, secure data transfer protocols, access controls, and adherence to applicable data protection regulations like GDPR or HIPAA.
Data Monitoring and Cleaning: Regularly monitor data collection processes to identify and address data discrepancies, missing data, or outliers. Implement data cleaning procedures to identify and resolve data errors, inconsistencies, and outliers that may impact the integrity and reliability of the study data.
Data Traceability and Audit Trail: Maintain a comprehensive audit trail that captures all changes and activities related to data entry, data modifications, and data review. This ensures data traceability and facilitates data validation and regulatory inspections.
Standard Operating Procedures (SOPs): Develop and adhere to well-defined SOPs for data management activities. SOPs should cover all aspects of data collection, processing, validation, cleaning, and archiving, ensuring consistency and adherence to regulatory requirements.
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.
Study setup_Clinical Data Management_Katalyst HLSKatalyst HLS
Introduction to Study Setup in Clinical Data Management in Clinical Trials of Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
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
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 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.
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.
Clinical Data Management: Best Practices and Key ConsiderationsClinosolIndia
Clinical data management (CDM) is a critical component of clinical research, involving the collection, processing, and analysis of data generated during clinical trials. Implementing best practices and considering key considerations is essential for ensuring data quality, integrity, and regulatory compliance. Here are some important considerations and best practices in clinical data management:
Data Standardization: Standardizing data collection and documentation across study sites is crucial for ensuring consistency and facilitating data analysis. Develop standardized data collection forms, case report forms (CRFs), and electronic data capture (EDC) systems that capture relevant data elements in a consistent manner.
Data Validation and Quality Control: Implement robust data validation procedures to ensure the accuracy and completeness of collected data. Conduct thorough quality control checks, including data validation checks, range checks, and consistency checks, to identify and resolve data discrepancies or errors.
Data Security and Privacy: Ensure data security and protect participant privacy by implementing appropriate measures such as data encryption, secure data transfer protocols, access controls, and adherence to applicable data protection regulations like GDPR or HIPAA.
Data Monitoring and Cleaning: Regularly monitor data collection processes to identify and address data discrepancies, missing data, or outliers. Implement data cleaning procedures to identify and resolve data errors, inconsistencies, and outliers that may impact the integrity and reliability of the study data.
Data Traceability and Audit Trail: Maintain a comprehensive audit trail that captures all changes and activities related to data entry, data modifications, and data review. This ensures data traceability and facilitates data validation and regulatory inspections.
Standard Operating Procedures (SOPs): Develop and adhere to well-defined SOPs for data management activities. SOPs should cover all aspects of data collection, processing, validation, cleaning, and archiving, ensuring consistency and adherence to regulatory requirements.
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.
Study setup_Clinical Data Management_Katalyst HLSKatalyst HLS
Introduction to Study Setup in Clinical Data Management in Clinical Trials of Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
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
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 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.
Database design in the context of Clinical Data Management (CDM) is a crucial aspect of organizing and managing clinical trial data effectively and efficiently. A well-designed database ensures that data collected during a clinical trial is accurate, consistent, and accessible, facilitating data analysis, reporting, and regulatory submissions. Clinical Data Management involves various steps, including data collection, validation, cleaning, and reporting
Dale W. Usner, Ph.D., President of SDC, co-authored the article "The Clinical Data Management Process," which was published in the November/December 2014 issue of Retina Today.
The article reviews the clinical data management (CDM) process in its entirety - from protocol review and CRF design through database lock. Describing the roles of various CDM team members and tips for efficient data management practices, "The Clinical Data Management Process" provides a comprehensive yet concise summary of this essential function in clinical trial research, specifically with respect to retina trials.
What’s inside the DMP?
It includes all elements of Data management process
It specifies:
• What is the work to be performed?
• Who is responsible for work?
• Which SOP’s or guidelines will be applicable?
• What documentation and output will be collected or produces from trial?
Topics to cover in DMP
• CRF/eCRF creation
• Database design and structure
• Edit Check specification
• Study database testing and release
• Data or paper workflow
• Reports and Metrics
• Query management
• Managing lab data
• Management of other non-crf data
• Coding of reported terms
• Handling of SAE’s
• Transferring data
• Study database lock
DMP provides:
• Clear history for long term studies which has to go through complex lifecycle
• Provides location for documenting details on computer system to collect trial data recommended by FDA guidance document.
• As per the FDA guidance document: for “computerised system used in clinical investigation.”
• The section IV. F recommends:
• For each study the documentation should identify what software and hardware will be used to create, modify, maintain, archive, retrieve or transmit clinical data.
• This is not submitted to FDA but retained as part of study record.
• It needs to be made available for inspection by FDA
• Some companies have detailed DMP’s while some have concise with pointer to reference documents
Authorisation of DMP
• For internal CDM groups the lead, Clinical data manager, or senior data managers for study creates documents and signs it.
• Companies having contract between CDM group and other groups will have their representatives reviewing and DMP along with lead DM.
Revision of DMP
• During the course of an average phase II and phase III study, some critical data management process or a key computer application may change.
• DMP can be revised whenever there is a significant change.
• Any revision in DMP needs to be reviewed and verified by authorizing official.
DMP’s with CRO
• Sponsor may outsource CRO for some or all parts of DMP can be used.
• CRO’s may have more comprehensive DMP as compared to sponsor and most of the times the CRO’s DMP is used.
• An experienced DM from sponsor is supposed to review the DMP by sponsors.
• CRO collectively works with sponsor for any revisions in DMP.
• Sponsor should provide resources for creating DMP.
A Data Management Plan (DMP) describes data that will be acquired or produced during research; how the data will be managed, described, and stored, what standards you will use, and how data will be handled and protected during and after the completion of the project.
What are the steps involved in clinical data management?
Clinical Data Management (CDM) is a critical phase in clinical research which results in collection of reliable, high-quality and statistically sound data. It consists of three phases i.e. start up, conduct and close out.
The CDM team first creates a Case Report Form (CRF), which is the first step in translating generated protocol activities. These information fields must have a clear definition and must be consistent throughout.
Clinical trial is intended to find answers to the research question by means of generating data for proving or disproving a hypothesis. The quality of data generated plays an important role in the outcome of the study. Often research students ask the question, “what is Clinical Data Management (CDM) and what is its significance?” Clinical data management is a relevant and important part of a clinical trial. All researchers try their hands on CDM activities during their research work, knowingly or unknowingly. Without identifying the technical phases, we undertake some of the processes involved in CDM during our research work.
CDM is the process of collection, cleaning, and management of subject data in compliance with regulatory standards. The primary objective of CDM processes is to provide high-quality data by keeping the number of errors and missing data as low as possible and gather maximum data for analysis.[1] To meet this objective, best practices are adopted to ensure that data are complete, reliable, and processed correctly. This has been facilitated by the use of software applications that maintain an audit trail and provide easy identification and resolution of data discrepancies. Sophisticated innovations[2] have enabled CDM to handle large trials and ensure the data quality even in complex trials.
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Post Graduate Diploma in Clinical Research
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
a supreme Data Management (DM) solution geared towards full data transparency as well as
delivering the highest level of quality within the defined timelines and in adherence to study budgets,
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.
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.
Who needs fast data? - Journal for Clinical Studies KCR
How “no news” during the life of a trial is bad news, and what data management (among other things) can do to help when ensuring access to fast data? Get to know this and more about smart e-solutions in the newest article of Kaia Koppel, Associate Director, Biometrics & Clinical Trial Data Execution Systems at KCR, in the recent issue of Journal for Clinical Studies (p.40-21).
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.
Importance of data standards and system validation of software for clinical r...Wolfgang Kuchinke
We present our evaluation of existing data standards for clinical trials. For this purpose a survey about the importance of data standards for clinical trials centers and EDC software companies were conducted. Electronic data capture in clinical trials uses a computerized system designed for the collection of clinical data in electronic form in Case Report Forms (CRF). It also covers medical data captured during clinical trials, safety data related to clinical trials, and patient reported outcome. The degree of implementation of standards, like CDISC ODM in available EDC software products was evaluated. Failure to establish data standards will make it difficult or impossible to connect data between different systems for efficient clinical study execution. The next step after purchasing a software solution is the computer system validation. Validation is about bringing computerized systems into regulatory compliance and making them compliant with GCP, GLP and GMP and other regulations (e.g. data protection). The basis standard for validation is provided by the GAMP Good Practice Guide, which provides a framework of best practices to ensure that computer systems are suitable for use and compliant with the legislation. The newest version uses a risk-based approach to computer system validation A system is evaluated and assigned to a predefined category based on its intended use and complexity. For validation one should define how all elements of the computer system are supposed to work (functional requirements), develop corresponding scripts and test routines to validate it is functioning as it should.
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
Evaluation of the importance of standards for data and metadata exchange for ...Wolfgang Kuchinke
Electronic Data Capture (EDC) in clinical research can ensure high-quality, clean data capture. Especially easy is the capture of repeating measurement like Adverse Events.
Here, a project is describes that evaluates the importance of data and metadata exchange for clinical research with the focus on EDC systems, standards that are relevant and the Computer System Validation (CSV) of EDC systems.
The project creats process descriptions, as well as necessary documents and checklists for any GCP-compliant system validation (Computer System Validation, CSV), like the Traceability Matrix.
Research networks are made aware of the necessity and importance of using EDC systems and conducting the computer system validation for regulatory compliance. The important role of CDISC standard, the standard for collection, exchange, submission to authorities and archiving of data from clinical studies is discussed in detail.
Similar to Clinical Data Management Plan_Katalyst HLS (20)
Introduction to Aggregate Reporting in Drug Safety & Pharmacovigilance in Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
Contact:
"Katalyst Healthcares & Life Sciences"
South Plainfield, NJ, USA
info@KatalystHLS.com
Overview of Validation in Pharma_Katalyst HLSKatalyst HLS
Introduction to Validation Concepts in Pharma, Bio-Pharma, Medical Device, Cosmetics, Food, Beverages industry.
Contact:
Katalyst Healthcare’s & Life Sciences
South Plainfield, NJ, USA 07080.
E-Mail: info@KatalystHLS.com
Introduction to Aggregate Reporting in Drug Safety & Pharmacovigilance in Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
Contact:
"Katalyst Healthcares & Life Sciences"
South Plainfield, NJ, USA
info@KatalystHLS.com
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
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- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
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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
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
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.
Title: Sense of Taste
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 structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
These lecture slides, by Dr Sidra Arshad, offer a quick overview of physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Anti ulcer drugs and their Advance pharmacology ||
Anti-ulcer drugs are medications used to prevent and treat ulcers in the stomach and upper part of the small intestine (duodenal ulcers). These ulcers are often caused by an imbalance between stomach acid and the mucosal lining, which protects the stomach lining.
||Scope: Overview of various classes of anti-ulcer drugs, their mechanisms of action, indications, side effects, and clinical considerations.
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.
2. A data management plan ensures compliance with good clinical data
management practices throughout the entire clinical trial.
Data Management plan is a document which defines all data management
activities, to promote consistent, efficient and effective data management
practices for each individual study.
Data management plan not only describes data management activities, but also
provide an agreement among all parties concerning responsibilities and
deliverables related to clinical data management.
Data Management Plan : Overview
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3. • After completing this training you will be able to:
– Understand how a Data Management Plan is created in compliance with
good clinical data management practices
– Describe all study specific data management activities, roles and
responsibilities
– Understand how DMP acts as central reference for the supporting
documentation and processes used during the life cycle of the study
Data Management Plan : Objectives
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4. The DMP describes the database structure and the procedures that will be used for
system testing and validation and also for data entry, edit checks, data coding, data
queries and query resolution.
• It serves as a document for planning, communication and reference tools for clinical
study teams
• It provides continuity for data management activities when personnel changes
occur
• It also provides a record of the data handling activities to be performed for a given
study along with the timelines
• It also define Roles & responsibility of the different stake-holders involved in DM
Activities
What is Data Management Plan?
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5. • The DMP components will be made available to all members of the Study
team throughout the study
• This document is a global reference, is to be read thoroughly once and used as
a reference on an ongoing basis
• The components once created will be distributed to the study team for review
and approval
• The DMP components are living documents and will be updated as study
circumstances evolve, and will only be complete when the study has been
terminated or closeout activities are completed
• The Lead Data Manger is responsible for creating the components of the DMP
DMP Creation and Distribution
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6. DMP Components vary from 1 study/client to another.
On a broader level, information on the following areas need to be collected within the
DMP:
— Data Flow
— Data Capture
— Study Setup
— Data Entry
— Data Transfer
— Data Processing/ Management
— Coding
— Safety Data (Serious Adverse Events)
— External data
— Any milestones if applicable or Database Lock and Unlock process
— Archival of Clinical Data
— Reports
— Quality
DMP Components
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7. Data Flow
7
This process flow will cover the following points
• Data from source documents> Data entry in Trial database
• Autoquery/DM review/Monitor/CRA review
• Query issue>site response>query resolution/re-query
• Source data verification, if applicable
• CRF freeze
• CRF sign off
• CRF and database lock
• Process for Database unlock
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8. Regardless of whether you’re running a small, single Phase I trial or many,
complex Phase III or phase IV 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
Data Capture
8
DATA
CAPTURE
Paper Data
Capture
Remote Data
Capture
Electronic
Data Capture
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9. Types of Data Capture
9
• Paper Case Report forms/Case Report Form
• Remote Data Capture (RDC): Paper CRFs are used however the data entry and
storage is done at the site or at a central location for multiple sites within a
geographic region
• Electronic Data Capture (EDC): Study information is entered directly into a
computer without any paper trail
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10. This covers all the documents that are required for setting up/building a study:
• CRF Creation Guidelines: Provide guidance to CRF designer on creation of eCRF.
• CRF data standards: Provides details of standard to be used while designing a CRF
to CRF designer.
• Annotated CRF: Blank CRF with marking, or annotations that coordinate each data
point in the eCRF form with its corresponding dataset name.
• Paper Case Report Form: Data collection tool used in clinical trials to support
investigators and coordinators in capturing all protocol-required information.
• CRF Completion guidelines: Provides detailed guidelines to the site staff to fill in
the paper CRFs. Guidelines help to bridge the gap between the study protocol and
the users in regards to CRF completion, correction, signing and handling
procedures.
Study Set Up
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11. • Monitoring Plan: Provides detailed guidelines to Monitor/CRA on how to
review CRFs and provides reference to Study specific monitoring plan where
monitoring method(s), intervals between on-site visits, and other details
associated with monitoring are provided.
• Database design manual/eCRF specification: Provides guidance to Clinical
Programmers by the DM on the Edit Checks for each data point on the CRF
• Edit Check Specifications: Describes all checks (manual and electronic) that
will be applied to the study data to ensure that data is fit for reporting
purposes
Study Set Up
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12. This session of the DMP describe the data entry guidelines which will be
followed throughout the study conduct
Data Entry
Data Entry Guidelines: Describes the process to enter data into the Database
Data Entry
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13. For external data transfers, the DMP should describe the data type (e.g.,
safety lab data), the entity providing or receiving the data and any
applicable agreements, the format, the frequency of transfers, and contact
information for all those involved with the data transfer
Data Transfer
• Data Load Specification: Variable/element specifications used in the study
• Type of the Data to be received: for example PK, Biomarker, ECG, etc
• Source of the data: Recipient of data (site, sponsor, data safety monitoring
board (DSMB),statisticians, etc.)
• Reference Ranges: Reference range used in the study in case of local Lab
• Quality control processes to be followed: Validation steps performed to
maintain the integrity of the data
Data Transfer
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14. This section of the DMP describes the Data Management documents used to
ensure that the data is accurate and clean throughout the course of the study.
This review allows data analysis to be performed at pre-defined study
timelines as defined in the study protocol.
This section enlist:
- the essential requirements on Data review
- Provides variables for cleaning or provides reference of Data review
plan/Data Review guidelines where instructions on data cleaning activities are
captured for DM/CRA/Monitor/safety review.
- This should also mention how queries are tracked
Eg. DM review: If action taken is Concomitant medication on AE form, check if
Medication form is updated.
Data
Processing/Management
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15. This section of the DMP give the details about how the Coding and Safety data will
be
handled during the study conduct
Coding Procedures
• Terms to be coded: Indicate which terms will be coded, e.g. Adverse Events, Medications and
Medical History, and in which modules they are found
• Dictionaries used: Indicate which dictionaries (and version numbers) will be used
• Coding method and Responsibilities: Indicate the method and responsibility of a coder
• Coding Tools: Name of the tool used for the study for coding activity
Safety Data
• Handling Safety Data: Indicates the frequency at which SAE reconciliation will be performed, for
e.g. (monthly, weekly etc)
• Handling SAE queries: Indicate the process of how the SAE queries will be handled during the
study conduct
Coding and Safety Data
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16. This section of the DMP give the details about how external data will be
handled during the study conduct
• External data type: Type of data collected & maintained by external vendor
• External data vendors: The point of contact, TPV details etc will be provided
• Data transfer specifications: The attributes of the data which will be received
by the vendor
• Frequency of reconciliations: The rounds of review of to be done & Frequency
of the external data review
• Any primary or secondary reconciliation variables
• Escalation path: How to follow up for unresolved issues
• Trackers & Metrics if any: If any template to be followed or metrics to be
generated post reconciliation
• Quality control: Any QC involved in the External data reconciliation will be
included here
External data handling
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17. This section of the DMP give the details about the process to lock and
unlock the database.
• This section provides details on how and when to have interim and final
database lock by listing the different endpoints in the study. Also provides
reference to DB lock checklist that need to be used to ensure all the activities
related to lock are completed.
Interim locks can be used to track the level of cleanliness for the study.
• It lists the milestones that need to be included in DB lock timelines.
• It provides details on which level the lock should be performed eg. Datapoint/
CRF/casebook
• It also provides the process to be followed when DB need to be unlocked,
Database lock and Unlock
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18. This session of the DMP gives the information regarding the organization’s procedures for
archiving the electronic records and list of available reports for dissemination throughout
the life of the study
Archival of Data
• Method of archiving original documents: Describe when and how the archival process
followed for original documents. e.g. CRFs
• Method to archive documents or data related to account and database access management:
document process when and how the archival process occur for account and database related
access
• Method to access and retrieve the audit trail-Access management and retrieval process
Reports: Details about lists of available reports available of a particular study for use or
DM/CRA/etc
Archival of Data and Reports
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19. This session of the DMP give the details regarding the quality assurance
(QA) plans and
quality control (QC) process steps
Quality
• QC Plan: Helps in fulfilling both regulatory and GCP requirement by creating
the plan and detailing what documents will record the conduct of the study
• Percentage of patients to be involved in QC: Sample size
• Data points that will be audited: data point to be checked during quality check
• Acceptable error rate: acceptable allowable error rate
• Action plan for resolution of audit: Details about process to handling post
QC/QA findings
Quality
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20. This section speak about the related documents such as quality control plan sent
along
with the DMP as appendix
• Study Specific Data handling document/Study Decision log - Dynamic
• Self Evident corrections (SEC)
• Quality control plan
• CRF Completion Guidelines (CCGs)
• Study Design/eCRF Specification
• Database Testing Plan
• Edit Check Specifications
• Data Entry Guidelines
• Data Flow Activities
DMP Documents/Elements
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21. • Protocol
A Clinical Trial Protocol is a document that describes the objective(s), design,
methodology, statistical considerations, and organization of a clinical trial.
The protocol also contains a study plan on which the clinical trial is based. The
protocol describes, among other things, details on patient population; the
schedule of tests, procedures, medications, and dosages/ devices; and the
length of the study.
DMP Documents/Elements
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22. • Study specific Data handling Document/Study Decision log
Details decisions made in agreement with the study team, around the
handling of certain data items whose resolution either no longer requires a
DCF to be sent to the site and is specific to the study
• Self Evidence Corrections
Details permissible corrections or changes that can be made to subject data
without issuing a Data Clarification Form (DCF) to the Site. These are
changes that use data that already exists in the CRF and/or source documents
attached to the CRF, e.g., laboratory report and do not impact the meaning of
the data
DMP Documents/Elements
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23. • Quality Control Plan
Describes the process to perform a quality review or audit in order to ensure
consistent quality of the database
• CRF completion Guidelines
Provides detailed guidelines to the site staff to fill in the paper CRFs
• Study Design/eCRF Specification
Provides specifications for each data point to design database
Details decisions made in agreement with the study team, around the design of the
Case Report Form and study database
DMP Documents/Elements
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24. • Database Testing Plan
Contains the plan and checklist to Qc the database that has been built
• Edit check Specifications
Describes all edit checks that will be applied to the study data to ensure that
data is clean and fit for reporting purposes
• Data Entry Guide
Describes the process to enter data into the Database
DMP Documents/Elements
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25. Sample DMP documents will be discussed by the Trainer
(You can also use the search engine to look up more samples)
Lets see how these look?
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26. • Timeline included in the DMP or document referenced by the DMP lists
expected completion targets for all deliverables. For example, database
validation could be targeted for completion a specified number of weeks from
the time the protocol is finalized
• Timelines may vary based on parameters of the study, such as between paper-
based studies and those utilizing electronic data capture (EDC)
DMP Timelines
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27. • Work to be done and responsibilities are clearly stated at the start of the study
so that everyone knows what is expected
• Expected documents are listed at the start of the study so they can be
produced during the course of, rather than after, the conduct of the study
• Document helps everyone fulfill regulatory requirements.
• Data management tasks become more visible to other groups when the DMP
is made available to the project team
• Provides continuity of process and a history of a project.
• Particularly useful for long-term studies and growing data management
groups
DMP Benefits
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28. • What do you mean by DMP?
• Why is DMP essential in the CDM process?
• Name and explain any 5 Components in DMP?
• Name and explain any 3 DMP Documents?
• How may types of Data Capture are there? Name them
Test Your Understanding
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29. In summary the DMP Documents helps:
• Act as a backbone of overall Quality System of Data Management (DM)
• In study planning
• In having SOPs and Working Instructions in place
• Provide a focus for identifying work to be performed
• Provide details on the Roles and responsibilities
• Provide details of documentation or output to be collected
• In communicating with the entire study team
Summary
29 2/21/2017Katalyst Healthcares & Life Sciences
A primary goal of the DMP is to communicate to all stakeholders the necessary knowledge to create and maintain a high-quality database ready for analysis
All of the CDM process require documentation in a Data Management Plan. DMP is a crucial document and serves as a master document enlisting all the processes and quality of the clinical data Management of a clinical trial. And all the versions of the DMP and the DMP components will be made available throughout the study to all the individuals involved.
Many people are involved in handling data throughout the course of a clinical study, so it is imperative that all parties refer to the DMP for a consistent approach to the processes and guidelines for conducting data management activities.
The DMP should be created during the setup phase of each study and should contain information relating to all aspects of data management activities to be performed.
The DMP document addresses to answer any process related queries about the CDM activity of the trial as well help to adhere to the regulatory requirement. DMP may be amended and revised time to time during the course of the data Management.
The DMP is an auditable document often asked for by regulatory inspectors and should be written in a manner that is professional and of high quality. During an audit, the inspectors may also seek to ascertain the degree to which the project team adheres to the processes described in the DMP.
Each component of the DMP will be governed by an SOP as applicable which should be followed.
Annotated CRF: Gives the information about the structure of clinical data. Annotated CRF document the tables,
variable item names, forms, visits and any other objects. It also includes codelists. It should also contain images of the entry
screens (provided in PDF). This is the first step in translating the CRFs into a database application.
CRF completion guidelines: General and protocol specific guideline on how the sponsors are expecting forms to be completed at the investigative site CRF completion guidelines should ensure that all required fields are completed, and that
the data provided within these forms are logical within the scope of the study protocol. The CRF completion guidelines document is a tool that should be available to all members of the multidisciplinary team participating in a clinical trial, and
should be referenced to ensure accurate and consistent entry and interpretation of data. These guidelines help train site staff on proper form completion, and also aide Clinical Research Associates (CRAs) on how to review data on the completed forms.
Edit Check Specifications: Document created to identify a number of different types of data inconsistencies or potential data errors
Most edit checks are programmed into the database or CDMS and are triggered automatically when predefined conditions are not met