View this recorded webinar to hear an overview of the Guidance Document on Electronic Source Data in Clinical Investigations and its practical implementation.
eSource to eTrial - Integrating Technology and Data to Innovate Clinical Deve...Nick Hargaden
The authors describe a case study for a sponsor showing the synergies found by combining eSource via Clinical Ink's SureSource system and risk based monitoring (RBM) analytics via Algorics' Acuity system. First presented at the Risk Based Trial Management conference in Philadelphia on 5th November 2015
Scientific & systematic collection of data for clinical study is called as Clinical Data Management-
Clinical Data Management-Web Based Data Capture EDC & RDC , Oracle
SAS
Office software
UW Catalyst data collection (University of Washington)
REDCAP (Research electronic data capture)
OPENCLINICA
STUDY TRAX
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.
Scientific & systematic collection of data for clinical study is called as Clinical data management .
EDC
RDC
HISTORY
EVOLUTION OF CLINICAL DATA CAPTURE
CRITERIA FOR IDENTIFYING AN EDC
REGULATORY GUIDELINE ON EDC
EDC ISSUES
VALIDATING ELECTRONIC SOURCE DATA
The impact of electronic data capture on clinical data managementClin Plus
electronic data capture (EDC)-based clinical trials offer operational and cost-effective approaches for ongoing data entry via the Internet for clinical sites; medical monitoring; monitoring by clinical research associates including initial review. Pharmaceutical, biotechnology, and medical device industry, as well as academia and the government, have all begun to adopt EDC as a new data management tool.
eSource to eTrial - Integrating Technology and Data to Innovate Clinical Deve...Nick Hargaden
The authors describe a case study for a sponsor showing the synergies found by combining eSource via Clinical Ink's SureSource system and risk based monitoring (RBM) analytics via Algorics' Acuity system. First presented at the Risk Based Trial Management conference in Philadelphia on 5th November 2015
Scientific & systematic collection of data for clinical study is called as Clinical Data Management-
Clinical Data Management-Web Based Data Capture EDC & RDC , Oracle
SAS
Office software
UW Catalyst data collection (University of Washington)
REDCAP (Research electronic data capture)
OPENCLINICA
STUDY TRAX
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.
Scientific & systematic collection of data for clinical study is called as Clinical data management .
EDC
RDC
HISTORY
EVOLUTION OF CLINICAL DATA CAPTURE
CRITERIA FOR IDENTIFYING AN EDC
REGULATORY GUIDELINE ON EDC
EDC ISSUES
VALIDATING ELECTRONIC SOURCE DATA
The impact of electronic data capture on clinical data managementClin Plus
electronic data capture (EDC)-based clinical trials offer operational and cost-effective approaches for ongoing data entry via the Internet for clinical sites; medical monitoring; monitoring by clinical research associates including initial review. Pharmaceutical, biotechnology, and medical device industry, as well as academia and the government, have all begun to adopt EDC as a new data management tool.
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).
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.
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.
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
Successful Selection and Implementation of EDC (Electronic Data Capture) System Eleazar Noel
1. Selecting Electronic Data Capture Tools
2. Determining the EDC Budget
3. Usability and flexibility of the system
4. Implementation of EDC System in Clinical Trials
Find out the best practices for implementing Electronic Data Capture systems in clinical trials http://bit.ly/2beFVmV
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.
eSource: A Clinical Data Manager's Tale of Three Studieswww.datatrak.com
‘eSource: A Clinical Data Manager’s Tale of Three Studies’ highlights the challenges and benefits of eSource studies, and a look to the potential future. With the continuing adoption of eClinical solutions in clinical research, the need to understand, address, and utilize the time and cost savings benefits of eSource will grow increasingly important.
Computer capture in Clinical Data Managementbhunjawa
Computer Capture is a process to collect the data in electronic form. It is very important process in Clinical Data Management, Clinical Research Industry.
clinical data management in clinical research, helpful for pharmacy, nursing, medical, health care providers, clinical research organization, PharmD, CROs, Clinical trial industry, human biomedical research.
A presentation given at the Duke Margollis Health Policy meeting in 2015 and providing insights into the current challenges related to EHR data quality. Proposes a new approach - OneSource.
Role of computer in clinical developmentDivyaShukla61
computers have always played a crucial role in our daily lives, Here i have presented its role in Clinical development.Hope you understand easily from my presentaion.
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).
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.
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.
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
Successful Selection and Implementation of EDC (Electronic Data Capture) System Eleazar Noel
1. Selecting Electronic Data Capture Tools
2. Determining the EDC Budget
3. Usability and flexibility of the system
4. Implementation of EDC System in Clinical Trials
Find out the best practices for implementing Electronic Data Capture systems in clinical trials http://bit.ly/2beFVmV
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.
eSource: A Clinical Data Manager's Tale of Three Studieswww.datatrak.com
‘eSource: A Clinical Data Manager’s Tale of Three Studies’ highlights the challenges and benefits of eSource studies, and a look to the potential future. With the continuing adoption of eClinical solutions in clinical research, the need to understand, address, and utilize the time and cost savings benefits of eSource will grow increasingly important.
Computer capture in Clinical Data Managementbhunjawa
Computer Capture is a process to collect the data in electronic form. It is very important process in Clinical Data Management, Clinical Research Industry.
clinical data management in clinical research, helpful for pharmacy, nursing, medical, health care providers, clinical research organization, PharmD, CROs, Clinical trial industry, human biomedical research.
A presentation given at the Duke Margollis Health Policy meeting in 2015 and providing insights into the current challenges related to EHR data quality. Proposes a new approach - OneSource.
Role of computer in clinical developmentDivyaShukla61
computers have always played a crucial role in our daily lives, Here i have presented its role in Clinical development.Hope you understand easily from my presentaion.
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.
Sharing and standards christopher hart - clinical innovation and partnering...Christopher Hart
Acknowledging the increasing need for cooperation and collaboration in data sharing and access. Describing the complexity that this can bring. Then describing some of the ways to simplify that.
Originally presented at Terrapin's Clinical innovation and partnering world March 8-9 2017.
http://www.terrapinn.com/conference/innovation-and-partnering/index.stm
A Pharma/CRO Partnership in the Design and Execution of Paperless Clinical Tr...Target Health, Inc.
DIA 2019 presentation by Dr. Jules Mitchel with Michelle Eli (Lilly) and Tom Haag (ex-Novartis) based on their experience with Lilly collaborating on Target Health's paperless clinical trial system.
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.
In the course of any clinical trial, there are risks associated with specific activities and tasks. This webinar will highlight some of these key risk areas and provide guidance on combining technology with best practices to help mitigate risks.
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.
Leverage Your EDC Solution to Mitigate Risk in Clinical Researchwww.datatrak.com
Every clinical trial is built upon a study protocol - the cornerstone of any trial. A well-defined and written study protocol provides the blueprint for the study, defining its purpose and goals. Studies have become more complex, creating more complicated study design, which can lead to making adherence more challenging for the study team and participants. The potential risk that some aspect of the study could be done incorrectly or not comply is inherent in all studies, but particularly present in complex research.
In order to help mitigate risk, advances in technology and the tools available today provide ways for us to mitigate some of the risk introduced in our clinical trials. While the study protocol is a cornerstone for the clinical trial, electronic data capture (EDC) applications have evolved in the broadest sense into technology solutions that provide us with a variety of tools to help mitigate risk.
Defining a Central Monitoring Capability: Sharing the Experience of TransCele...www.datatrak.com
Central monitoring, on-site monitoring, and off-site monitoring provide an integrated approach to clinical trial quality management. TransCelerate distinguishes central monitoring from other types of central data review activities and puts it in the context of an overall monitoring strategy. Any organization seeking to implement central monitoring will need people with the right skills, technology options that support a holistic review of study-related information, and adaptable processes. There are different approaches actively being used to implement central monitoring. This article provides a description of how companies are deploying central monitoring, as well as samples of the workflows that illustrate how some have implemented it. The desired outcomes include earlier, more predictive detection of quality issues. This paper describes the initial implementation steps designed to learn what organizational capabilities are necessary.
Technology Considerations to Enable the Risk-Based Monitoring Methodologywww.datatrak.com
TransCelerate BioPharma Inc developed a methodology based on the notion that shifting monitoring processes from an excessive concentration on source data verification to comprehensive risk-driven monitoring will increase efficiencies and enhance patient
safety and data integrity while maintaining adherence to good clinical practice regulations. This philosophical shift in monitoring processes employs the addition of centralized and off-site mechanisms to monitor important trial parameters holistically, and it uses adaptive on-site monitoring to further support site processes, subject safety, and data quality. The main tenet is to use available data to monitor, assess, and mitigate the overall risk associated with clinical trials. Having the right technology is critical to collect and aggregate data, provide analytical capabilities, and track issues to demonstrate that a thorough quality management framework is in place. This paper lays out the high-level considerations when designing and building an integrated technology solution that will aid in scaling the methodology across an organization’s portfolio.
How To Optimize Your EDC Solution For Risk Based Monitoringwww.datatrak.com
This presentation presents best training practices to leverage EDC technology and risk-based monitoring to effectively and efficiently monitor clinical research.
Our focus is on the practical process of preparing your team to optimize the tools made available through an EDC solution.
This presentation is applicable to CRA’s, clinical project managers, clinical data managers, regulatory compliance professionals, and those involved in the design and implementation of risked-based monitoring plans.
Use this template to create your Risk Based Monitoring guideline. Make sure you review this in conjunction with the Risk Based Monitoring in Practice presentation for the best possible result.
After reviewing the FDA regulations on Risk Based Monitoring, review the details on how to put the principles into action! We include two reference documents to help you get started... and to make it a success.
Niki Kutac, Director Product Management, delivered this presentation at the ACRP 2014 Conference where it was rated the #1 Session of the Event. Learn how to implement gamification to produce the desired end result.
Utilizing a Unified Platform to Bridge Geographical and Departmental Gaps Whi...www.datatrak.com
Presentation discusses:
The Drug Development Process
The Drug Development Paradox
Regulations and Guidelines
Standards - CDISC
Leveraging Technology
Resource Management
The FDA Guidance of a Risk-Based Approach to Monitoring as Viewed By CDMwww.datatrak.com
Historical Perspectives in CDM
Overview of the Draft Guidance
A Risked-Based Approach
Challenges to a Risk-Based Approach
Supporting a Risked-Based Approach
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
2. Your Speakers
► Maura Bearden
• Maura is a graduate of the University of North Carolina at
Chapel Hill and has been with DATATRAK in a variety of
Clinical Data Management roles since 2012. Ms.
Bearden’s expertise is in the streamlining of study start-up
tactics, data management and customer service.
► Bill Gluck, Ph.D.
• Dr. Gluck has over 30 years of expertise in clinical
research, with experience in sponsors, CROs, and with
DATATRAK in a variety of roles. Dr. Gluck is also the
Program Director for the Clinical Trials Research and
Medical Product Safety/Pharmacoviligance programs at
Durham Technical Community College. Dr. Gluck earned
his Bachelor of Science Degree at the University of
Scranton and Master and Ph.D. degrees from North
Dakota State University.
2
3. Agenda
► Key Dates in Time: eSource
► Overview of the Guidance Document on
Electronic Source Data in Clinical Investigations
► Why eSource?
► Practical Applications – eSource: A CDM’s Tale
of Three Studies
• Challenges of eSource Studies
• Benefits of eSource Studies
• Future of eSource
► Summary
3
4. Dr. Bill Gluck
Vice President Clinical Knowledge
DATATRAK International
eSource: Guidance Overview
5. Genesis of eSource: Key Dates in
Time
► 1968 – LL Weed, New England Journal of
Medicine 278:593-600
► 1980’s-present – Evolution of IRT, EDC,
ePRO/eCOA technologies
► 1997 – Regulatory definitions begin to evolve
• CDISC and an industry-led standardization movement
begin
► September 2013 – Guidance for Industry on
Electronic Source Data in Clinical Investigations
5
6. Guidance Document Addresses the
Following
► Identification and specification of authorized
source data originators
► Creation of data element identifiers to facilitate
examination of the audit trail by sponsors, FDA,
and other authorized parties
► Ways to capture source data into the eCRF
using either manual or electronic methods
► Clinical investigator(s) responsibilities with
respect to reviewing and retaining electronic
data
► Use and description of computerized systems in
clinical investigations
6
7. eSource studies pertain to clinical trials where
direct data entry into an electronic data capture
system (EDC) is used in contrast to paper
source studies where data are transcribed from
a paper source into EDC.
Simply put (from the Guidance Document):
“Electronic source data are data initially recorded
in electronic format.”
7
8. Data Capture: Electronic Source Data
Origination
► List of authorized source data originators should be
developed and maintained by the sponsor and
made available at each clinical site
► Examples of Data Originators:
• Clinical investigator(s) and delegated staff
• Clinical investigation subjects or their legally authorized
representatives
• Consulting services
• Medical devices
• Electronic Health Records
• Automated laboratory reporting systems
• Other technology
8
9. Data Capture: Source Data Capture, Data
Element Identifiers, Modifications and
Corrections, and Use of Data Quality Checks
► Source Data Capture
• Direct entry of data into the eCRF
• Automatic transmission of data directly into the eCRF
• Transcription of data from paper or electronic sources
to the eCRF
• Direct transmission of data from the EHR to the eCRF
• Transmission of data from PRO instruments to the
eCRF
► Data Element Identifiers
► Modifications and Corrections
► Use of electronic prompts, flags, data quality
checks in the eCRF
9
10. Data Review
► Clinical Investigators
• Clinical Investigator(s) review and electronic signature
• Data exempt from investigator(s) review
► Modifications and Corrections During Review of
the eCRF
10
11. Retention of Records by Clinical
Investigator(s)
► Retain control of the records
• Completed and signed eCRF
• Certified copy of the eCRF
► Be able to provide inspectors with access to the
records that serve as electronic source data
► When transcription from paper occurs – the
paper is the source and must be retained
11
12. Data Access
► Viewing Data
• Sponsors, CROs DSMBs and other authorized
personal can view data before and after the clinical
investigator has signed the completed eCRF
– Allow for early detection of study-related problems
– Missing data
– Data Discrepancies
► CDMP should list individuals with authorized
access to the eCRF
12
13. Use and Description of Computerized
Systems
► Adequate controls must be in place
► Note: determination of whether a computer
system is suitable may not be under the control
of the clinical investigator or sponsor (EHRs for
example) – see 45 CRF Part 170
► Documentation – if computerized system are to
be used
• Protocol/CDMP/Investigational plan
• Description of security measures employed to protect
the data
• Description/Diagram of the electronic data flow
13
14. Why eSource?
► Companies are reluctant to move away from
paper-based source documentation
• It is very familiar and is today’s standard
• It is well documented and has a clear audit trail
• It has well documented security measures
► eSource
• Higher data integrity = Streamlined Data Review
Process
• Real-time accessibility
14
15. Maura Bearden
Clinical Data Manager
DATATRAK International
Practical Applications
eSource: A CDM’s Tale of Three
Studies
16. eSource Case Studies
► Three Different eSource Studies
► Study 1:
• Phase 2, 160 subjects and 24 sites
► Study 2:
• Phase 3, 400 subjects and 31 sites
► Study 3:
• Phase 2, 210 subjects and 20 sites
16
17. eSource Case Studies
► Analysis of three studies provides the
following information:
• Challenges of eSource Studies
• Benefits of eSource Studies
• Future of eSource
17
18. Challenges of eSource Studies
► Workflow process between monitoring and
data management
► Protocol-Specific system checks
► FDA Guidelines pertaining to data
originator elements for transcribed
assessments
► Site Compliance of FDA Guidance of
electronic source data
18
19. Challenge of Workflow Process
► Workflow process between
monitoring and data management
• Study: Cross-comparison of all three
studies
• Problem: How to document the review
between monitors and data
management
► Solution: Additional data review flag
19
20. Challenges of Protocol-Specific
Checks
► Protocol-Specific System Checks
• Study: Progression of all three studies
• Problem: Number of protocol-specific system
checks
► Solution: Identification of integral protocol
checks, help prompts and additional
electronic case report forms (eCRFs)
20
21. Challenges of FDA Guidelines
► FDA Guidelines pertaining to data
originator elements for transcribed
assessments
• Study: Study 3
• Problem: Coordinator entering information
into eCRF that is being read off by PI and the
conflict with the data originator in EDC.
► Solution: additional review fields on eCRF
that correspond to authorized data
originator
21
22. Challenges of FDA Guidance
► Site Compliance of FDA Guidance of
electronic source data
• Study: Study 1
• Problem: Sites writing study information on
paper
► Solution: Note-to-File regarding paper
sources and retraining of site
22
23. Benefits of eSource Studies
► Higher Data Integrity
► Real-Time Data Availability
► Decreased Time for Data Management
Review
23
24. Higher Data Integrity Benefit
► Higher Data Integrity
• No queries needed to correct transcription
errors between paper source and EDC
• Protocol-specific edit checks in the system
and eCRF prompts prevent subjects who are
not qualified from being randomized in the
study
24
25. Real-Time Data Availability Benefit
► Real-Time Data Availability
• Allows for all information to be available at
any time
• Reduce review time querying site to enter
information
• Allows for real-time reports with all available
data
25
26. Decreased Time for Data Mngt
Review
► Decreased Time for Data Management
Review
• Reduced number of confirmation queries
• Limits data management review to cross-
checks and traditional data management
reviews
• Remote monitoring (increased importance)
26
27. The Future of eSource
► Familiarity and optimization of start-up and
workflow process of eSource studies
• Familiarity and optimization can be seen in an
analysis of study 2 and study 3.
–Decreased study deployment time
–Distinct data review responsibilities for data
managers and monitors
–Streamlining user errors
27
28. Conclusions
► eSource has been recognized as an accepted
means of capturing clinical data during clinical
investigations by the FDA
► The FDA has provided guidance to industry for
its implementation and use
► Case studies demonstrate the benefits of
eSource trials:
• Higher data integrity
• Real-Time accessibility
• Streamlined Data Management Review Time
28
30. Contact Information
► Maura Bearden
• Maura.Bearden@DATATRAK.com
► Bill Gluck, Ph.D.
• Bill.Gluck@DATATRAK.com
► General Questions about DATATRAK
• Dorothy.Radke@DATATRAK.com
► Find Us Online
• www.DATATRAK.com
• http://www.slideshare.net/DATATRAK
• @DATATRAKinc on Twitter
• https://www.linkedin.com/company/datatrak-
international
30
31. from Concept to Cure
with DATATRAK ONE
DATATRAK International
Cleveland, Ohio
Bryan, Texas
Cary, North Carolina
London, UK
888.677.DATA (3282) Toll Free
www.datatrak.com
®
®
Editor's Notes
eSource was first attributed to LL Weed:
1 - Introduced the concept of the problem oriented medical record into medical practice
2 - Concept allow a 3rd party to verify the diagnosis
In the 1980’s through to the present we have been able to leverage technology using application offerings such as randomization and drug inventory, ePRO and eCOA (electronic clinical outcome assessments)
In the latter portion of the 1990’s we started to see an industry-wide movement toward standardization. Knowing through the use of standards we would be better positioned to leverage technology and management data more efficiently. With that in 1997/1998 CDISC was formed and an industry-lead standardization movement was underway.
In 2013 the Guidance for Industry on Electronic Source Data in Clinical Investigations was published – unlike the original draft the published guidance is a procedural guideline
To briefly note some of the highlights from the guidance document – the guidance document addresses each of the above items
In order to move forward we will define eSource data….as noted in the slide.
Data originators typically include the clinical investigator and the site staff – data collecting instruments and other technology-based sources
It is interesting to note that the FDA does not intend to assess the compliance of EHRs with Part 11
Pretty much do the same comparison to why use EDC over paper data collection
Now that we have an understanding of what the FDA has provided industry from the guidance document, let’s look a how eSource has been implemented in three active clinical studies – Maura Bearden will define the types and sizes of the studies, some of the challengs faced durting the implementation process and how each challenge was overcome. Based on the preliminary data from the three studies she will also describe the benefits gains through the use of eSource and then before concluding the webinar Maura will provide some of her ideas about the future of eSource in clinical trials.