The large volumes of data and biosignals produced by the ICU overwhelm doctors and nurses, and do little to help them set priorities for the activities required in these units.
It has been a longstanding challenge to integrate patient data from EMRs (Electronic Medical Record systems) with EDC (Electronic Data Capture) systems for clinical studies and trials.
The challenges include:
Low adoption rates of EMRs in physician practices
Lack of interoperability tools provided by vendors to extract data from EMRs
Lack of standardized payload (content) and method of delivering (transport) from different EMRs to the EDC systems
All subjects of clinical studies not being part of the same health system and therefore same EMR
Lack of automated methods for identifying the same patient between EMRs and EDC systems
Inability to map and translate the EMR data into CRFs (case report forms) of the EDC systems
These hurdles have been so high that the task has rarely been attempted in earnest, let alone accomplished in any significant way. That is until recently. How are these challenges being overcome today? What changes have allowed this integration to be to considered and implement today? The answer is: lots!
DIA 2015 - EMR/EHR Clinical Data Intergration with EDC SystemsClinCapture
It has been a longstanding challenge to integrate patient data from EMRs (Electronic Medical Record systems) with EDC (Electronic Data Capture) systems for clinical studies and trials.
Integration between disparate systems can be done in many ways. Any two systems can be integrated given enough time and money. However, if there is to be wide-scale integration between applications used by clinicians at their practice or in the hospital, it requires the formation and use of standards for the structure and content of data as well as the transport of data between two systems.
A historic problem has been the lack of EMR adoption, particularly in physician offices. Thankfully, this is improving dramatically, something I will touch on later.
There is also a historic problem that Case Report Forms and the databases that contain them in EDC systems are routinely not designed from the start with standardized labels, content or structure. More adoption of the CDISC standards, such as C-DASH (clinical data acquisition standards harmonization) which dictates structure and content, and ODM (operational data model) which is an XML rendering of the CDASH CRFs.. If you take anything away from this talk, please ensure any data capture you do within an EDC system going forward meets the ODM model.
Patient matching between systems is important. There is a whole industry for Community and Master Patient Indexes to link records in disparate systems to the same patient. This gets even more complex when the patients are to be kept anonymous or the studies are blinded.
Lastly, moving data across systems is a challenge. There are two primary methods – 1) asynchronous file transfer in conjunction with an ETL, or 2) APIs where one system is inquiring in real time into another application for data. The latter is usually regarded as a more robust integration, but without standard APIs these are one off solutions. The former, using ETL, requires the sending and receiving applications be able to communicate
ehCOS SmartICU: An innovative solution for Intensive Care Units using Big Data Predictive Analytics. More information: http://www.ehcos.com/en/products/ehcos-icu/
Xcellerate Data Review allows data managers to detect instances and sources of missing data, high query rates, delayed data entry and other data quality issues that impact trial data integrity.
Application of data science in healthcareShreyaPai7
Data Science is a field that is widely applied in most other domains on a regular basis. The huge amount of data generated regularly calls for sophisticated methods of analysis so that the best interpretatiosn can be drawn from them. Healthcare is one such field in which data science is being used extensively.
The large volumes of data and biosignals produced by the ICU overwhelm doctors and nurses, and do little to help them set priorities for the activities required in these units.
It has been a longstanding challenge to integrate patient data from EMRs (Electronic Medical Record systems) with EDC (Electronic Data Capture) systems for clinical studies and trials.
The challenges include:
Low adoption rates of EMRs in physician practices
Lack of interoperability tools provided by vendors to extract data from EMRs
Lack of standardized payload (content) and method of delivering (transport) from different EMRs to the EDC systems
All subjects of clinical studies not being part of the same health system and therefore same EMR
Lack of automated methods for identifying the same patient between EMRs and EDC systems
Inability to map and translate the EMR data into CRFs (case report forms) of the EDC systems
These hurdles have been so high that the task has rarely been attempted in earnest, let alone accomplished in any significant way. That is until recently. How are these challenges being overcome today? What changes have allowed this integration to be to considered and implement today? The answer is: lots!
DIA 2015 - EMR/EHR Clinical Data Intergration with EDC SystemsClinCapture
It has been a longstanding challenge to integrate patient data from EMRs (Electronic Medical Record systems) with EDC (Electronic Data Capture) systems for clinical studies and trials.
Integration between disparate systems can be done in many ways. Any two systems can be integrated given enough time and money. However, if there is to be wide-scale integration between applications used by clinicians at their practice or in the hospital, it requires the formation and use of standards for the structure and content of data as well as the transport of data between two systems.
A historic problem has been the lack of EMR adoption, particularly in physician offices. Thankfully, this is improving dramatically, something I will touch on later.
There is also a historic problem that Case Report Forms and the databases that contain them in EDC systems are routinely not designed from the start with standardized labels, content or structure. More adoption of the CDISC standards, such as C-DASH (clinical data acquisition standards harmonization) which dictates structure and content, and ODM (operational data model) which is an XML rendering of the CDASH CRFs.. If you take anything away from this talk, please ensure any data capture you do within an EDC system going forward meets the ODM model.
Patient matching between systems is important. There is a whole industry for Community and Master Patient Indexes to link records in disparate systems to the same patient. This gets even more complex when the patients are to be kept anonymous or the studies are blinded.
Lastly, moving data across systems is a challenge. There are two primary methods – 1) asynchronous file transfer in conjunction with an ETL, or 2) APIs where one system is inquiring in real time into another application for data. The latter is usually regarded as a more robust integration, but without standard APIs these are one off solutions. The former, using ETL, requires the sending and receiving applications be able to communicate
ehCOS SmartICU: An innovative solution for Intensive Care Units using Big Data Predictive Analytics. More information: http://www.ehcos.com/en/products/ehcos-icu/
Xcellerate Data Review allows data managers to detect instances and sources of missing data, high query rates, delayed data entry and other data quality issues that impact trial data integrity.
Application of data science in healthcareShreyaPai7
Data Science is a field that is widely applied in most other domains on a regular basis. The huge amount of data generated regularly calls for sophisticated methods of analysis so that the best interpretatiosn can be drawn from them. Healthcare is one such field in which data science is being used extensively.
6 Software Testing Strategies for HIPAA ComplianceQASource
When entering the healthcare domain, it is integral that your team understands the specific regulations set forth by HIPAA so that they are included in your testing plan and strategy. As you test healthcare applications, remember the strategies outlined in this deck to ensure full compliance.
Seattle code camp 2016 - Role of Data Science in HealthcareGaurav Garg
Everyone loves to shake a stick at the healthcare industry for being backward. Fact is there is no lack of technology or data in healthcare.
Biggest challenge for healthcare providers is to identify what questions to ask the data. My team has implemented over 75 enterprise data warehouse projects in US healthcare industry. At the annual Seattle Code Camp, we discussed some of the examples of how data is used in the healthcare industry for compliance reporting (BI) and predictive analytics.
These slides are from Seattle Code Camp 2016, shares technologies, concepts and ideas for data science in the US healthcare industry.
LogiLab Electronic Lab Notebook (ELN) software acts as a middleware between the instrument and the LIMS through Method execution system and Laboratory execution system.
ehCOS: Global Pionner in the development of "Next-Generation Electronic Healt...everis/ ehCOS
Gartner, in "Market Trends: Vertical-Specific Software Will Be the Heart of New Global Healthcare Bodies" highlights two key aspects of the future EHR: Modular, Flexible, open, and ready to incorporate technological trends That will shape the coming decades. In this White papers, we explain why ehCOS CLINIC, has emerged as an new generation EHR today.
Leverage near real-time data with risk-based, adaptive site monitoring to identify issues and trigger targeted actions that proactively mitigate threats to a clinical trial's success.
Radiology turnaround time should be reduced, as the referring physician depends on the radiology report to provide the right treatment at the right time.
Radiology Workflow: Recognizing Clinical & Financial Benefits of Implementing...TriMed Media Group
Rutland Regional Medical Center in Vermont, is a 188-bed rural hospital that effectively weds high-tech imaging with patient-centric care. This high-tech hospital with a hometown touch utilizes an intuitive RIS-PACS-reporting solution in its radiology department that is delivering benefits across the health system. The ability to provide local, state-of-the-art imaging is convenient for patients and referring physicians. It keeps patients close to home, which, in turn, improves the medical center’s bottom line.
In the past decade, there has been a significant increase in the use of Data Monitoring
Committees (DMC) and Adaptive Designs (AD) in clinical trials. While the monitoring of safety
data by a formal committee is not required for all clinical trials, it has become the norm to have
a formal DMC conduct periodic safety reviews for any controlled trial that evaluates treatments
intended to prolong life or reduce risk of major adverse health outcomes, or for trials that
compare rates of mortality or major morbidity. Confirmatory, pivotal, and adaptive design trials
have more complex operational issues requiring an external and independent DMC. The DMC
may have access to unblinded interim data, be required to make expert recommendations
about how the trial should continue, and then ensure that planned adaptations are
implemented as outlined in the protocol without involving the sponsor or exposing it to
unblinded data or results.
This added complexity creates a challenge and a question: how can the DMC, statisticians, and
sponsor effectively communicate, share blinded and unblinded data, perform analyses, and
implement adaptations without introducing operational bias or compromising the integrity of
the trial? One solution is to utilize a sophisticated computer system that can provide the
security and necessary firewalls to ensure that interim data is only accessible to those it is
intended for, that the rules and processes outlined in the protocol and DMC charter are
enforced, and that communication between the DMC and sponsor is effectively facilitated while
protecting the integrity of the trial and preventing the introduction of operational bias.
The system must also provide an audit trail that tracks “who saw what and when” providing
evidence to regulatory authorities that the protocol was strictly followed with a minimal
possibility of bias. This white paper describes the computer system, ACES, which Cytel has built,
that makes all of this possible. ACES (Access Control Execution System) has been purpose-built
to address the operational complexities inherent in adaptive design and pivotal clinical trials.
6 Software Testing Strategies for HIPAA ComplianceQASource
When entering the healthcare domain, it is integral that your team understands the specific regulations set forth by HIPAA so that they are included in your testing plan and strategy. As you test healthcare applications, remember the strategies outlined in this deck to ensure full compliance.
Seattle code camp 2016 - Role of Data Science in HealthcareGaurav Garg
Everyone loves to shake a stick at the healthcare industry for being backward. Fact is there is no lack of technology or data in healthcare.
Biggest challenge for healthcare providers is to identify what questions to ask the data. My team has implemented over 75 enterprise data warehouse projects in US healthcare industry. At the annual Seattle Code Camp, we discussed some of the examples of how data is used in the healthcare industry for compliance reporting (BI) and predictive analytics.
These slides are from Seattle Code Camp 2016, shares technologies, concepts and ideas for data science in the US healthcare industry.
LogiLab Electronic Lab Notebook (ELN) software acts as a middleware between the instrument and the LIMS through Method execution system and Laboratory execution system.
ehCOS: Global Pionner in the development of "Next-Generation Electronic Healt...everis/ ehCOS
Gartner, in "Market Trends: Vertical-Specific Software Will Be the Heart of New Global Healthcare Bodies" highlights two key aspects of the future EHR: Modular, Flexible, open, and ready to incorporate technological trends That will shape the coming decades. In this White papers, we explain why ehCOS CLINIC, has emerged as an new generation EHR today.
Leverage near real-time data with risk-based, adaptive site monitoring to identify issues and trigger targeted actions that proactively mitigate threats to a clinical trial's success.
Radiology turnaround time should be reduced, as the referring physician depends on the radiology report to provide the right treatment at the right time.
Radiology Workflow: Recognizing Clinical & Financial Benefits of Implementing...TriMed Media Group
Rutland Regional Medical Center in Vermont, is a 188-bed rural hospital that effectively weds high-tech imaging with patient-centric care. This high-tech hospital with a hometown touch utilizes an intuitive RIS-PACS-reporting solution in its radiology department that is delivering benefits across the health system. The ability to provide local, state-of-the-art imaging is convenient for patients and referring physicians. It keeps patients close to home, which, in turn, improves the medical center’s bottom line.
In the past decade, there has been a significant increase in the use of Data Monitoring
Committees (DMC) and Adaptive Designs (AD) in clinical trials. While the monitoring of safety
data by a formal committee is not required for all clinical trials, it has become the norm to have
a formal DMC conduct periodic safety reviews for any controlled trial that evaluates treatments
intended to prolong life or reduce risk of major adverse health outcomes, or for trials that
compare rates of mortality or major morbidity. Confirmatory, pivotal, and adaptive design trials
have more complex operational issues requiring an external and independent DMC. The DMC
may have access to unblinded interim data, be required to make expert recommendations
about how the trial should continue, and then ensure that planned adaptations are
implemented as outlined in the protocol without involving the sponsor or exposing it to
unblinded data or results.
This added complexity creates a challenge and a question: how can the DMC, statisticians, and
sponsor effectively communicate, share blinded and unblinded data, perform analyses, and
implement adaptations without introducing operational bias or compromising the integrity of
the trial? One solution is to utilize a sophisticated computer system that can provide the
security and necessary firewalls to ensure that interim data is only accessible to those it is
intended for, that the rules and processes outlined in the protocol and DMC charter are
enforced, and that communication between the DMC and sponsor is effectively facilitated while
protecting the integrity of the trial and preventing the introduction of operational bias.
The system must also provide an audit trail that tracks “who saw what and when” providing
evidence to regulatory authorities that the protocol was strictly followed with a minimal
possibility of bias. This white paper describes the computer system, ACES, which Cytel has built,
that makes all of this possible. ACES (Access Control Execution System) has been purpose-built
to address the operational complexities inherent in adaptive design and pivotal clinical trials.
SAS Clinical training program in Hyderabadyeswitha3zen
Excel in healthcare analytics with our top SAS Clinical training in Hyderabad. Gain hands-on expertise from clinical data analysis to SAS certification prep. Tailored for all, from fresh grads to pros. Enroll now!
Excel in healthcare analytics with our top SAS Clinical training in Hyderabad. Gain hands-on expertise from clinical data analysis to SAS certification prep. Tailored for all, from fresh grads to pros. Enroll now!
Study start up activities in clinical data managementsoumyapottola
Study start-up (SSU) is so much more than a one-time document management exercise. It’s a global, strategic operation that can get new drugs approved faster – and it’s ripe for innovation – from Site Selection to Site Activation and Site Training.
Many SSU tech solutions deployed by sponsors don’t deliver the results promised because they add burden without benefits to clinical research sites. The result? Site staff simply avoid using them.
When that happens, document exchange and tracking falls back to paper, email and Excel formats – with CRAs holding the processes together. The tools that were supposed to solve a problem become part of the problem – and consume preThe implementation and conduct of a study can be a complex process that involves a
team from various disciplines and multiple steps that are dependent on one another. This
document offers guidance for navigating the study start-up processcious clinical trial budget.
A successful clinical study start-up is a crucial first step and an important factor for the overall success of the trial. For this reason, SCRO has experienced study start-up teams, offering customized services depending on your needs, whether it be fuWhile the definition varies across companies, study startup typically includes the process of identifying and qualifying sites, collecting essential documents at the study and site level, and submitting these documents for ethics approval. Successful study startup requires coordination between sites, sponsors, and contract research organizations (CROs) to achieve critical milestones in a compliant manner.ll-service or single activities.
How to achieve better time management in EDC start up
Clinical data management requires strict time management processes, especially in study start up within an electronic data capture (EDC) system. Three steps that clinical data management teams can take to outline the planning and executing of each task that needs to be considered are as follows:
Make a List: Create a daily or weekly task list and schedule when each task will be completed. This strategy will assist you in maintaining focus and staying organized.
Set realist goals: Be realistic about what you can finish in the amount of time you have. When setting unrealistic goals, failure is almost certain to follow.
Explore time-saving techniques: Examples of techniques that could help save time include grouping similar tasks together or using a timer to stay focused.
To help get started, here is a list of EDC considerations for Study Start-Up deadlines:
Protocol finalization and study enrollment
Split go-live considerations
eCRF Specification meetings (this will ensure proper collaboration and minimize any back-and-forth communication)
EDC add-on modules (which will be required and need validation?)
ePRO/eCOA used with licensed questionnaires.
IRB requirements for add-on modules (eConsent/ePRO)
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.
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
Overview of Risk Based Monitoring in Clinical Trial ProcessesEditorIJTSRD1
Risk based monitoring RBM has emerged as a transformative approach in clinical trial processes. This paper provides an overview of RBM and its impact on the field of clinical research. By moving away from traditional on site monitoring and adopting a targeted and efficient approach, RBM has demonstrated numerous benefits in terms of cost effectiveness, data quality, and patient safety. This abstract summarizes the key findings discussed in the conclusion. The proactive identification and management of risks throughout the trial lifecycle have led to improved decision making, increased study participant compliance, and enhanced overall trial success rates. With advancing technology, RBM approaches are expected to evolve further, allowing for greater optimization and streamlining of clinical trial processes. The abstract concludes by emphasizing the potential of risk based monitoring to shape the future of clinical research and contribute to the development of safe and effective therapies for patients worldwide. Kelam Himasri | Sankara Narayanan. K "Overview of Risk-Based Monitoring in Clinical Trial Processes" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd58586.pdf Paper URL: https://www.ijtsrd.com.com/pharmacy/pharmacy-practice/58586/overview-of-riskbased-monitoring-in-clinical-trial-processes/kelam-himasri
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).
Risk-based Monitoring Strategies for Improved Clinical Trial PerformanceCognizant
To address draft regulatory guidance for risk-based clinical trial monitoring, sponsors should consider strategies that utilize social, mobile, analytics and cloud technologies to create responsive methodologies that satisfy both the spirit and the letter of these new guidelines.
Using Investigative Analytics to Speed New Drugs to MarketCognizant
Investigative analytics - covering exploratory data analysis (EDA) and inferential statistics - is a powerful, data-driven methodology for uncovering discrepancies in reports from clinical trials, and thus can help streamline and improve the trial process and accelerate the transition from molecule to medicine.
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.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
1. What is ACES®
and Where it’s Being Used
For
both
tradi+onal
and
adap+ve
trials,
ACES
addresses
the
secure
communica+on
complexi+es
and
regulatory
concerns
with
interim
analysis.
Since
introduced
in
2010,
we’ve
deployed
the
web-‐based
system
in
Phase
2
and
Phase
3
adap+ve
and
tradi+onal
trials
across
a
variety
of
therapeu+c
areas
including
oncology,
CNS,
infec+ous
diseases,
immunology,
and
psychiatry/psychology.
Access
Control
Execu/on
System
Independent
expert
commiJees
–
Data
Monitoring
and
Endpoint
Adjudica+on
–
while
increasingly
important,
add
administra+ve
complexity
for
clinical
trial
sponsors.
Securely
managing
the
exchange
of
confiden+al
informa+on
for
these
commiJees
also
exposes
sponsors
to
the
great
risk
of
compromising
the
integrity
of
their
study.
2. Why Sponsors are Implementing ACES
Key Benefits
1.
Regulatory
Trust
and
Confidence
ACES®
is
foremost
designed
to
achieve
regulatory
trust.
It
conforms
with
the
FDA
Guidance
and
EMA
posi+on
on
DMCs
and
Adap+ve
Trial
Design
providing
evidence
that
a
trial
is
conducted
with
a
secure
process,
including
a
‘who
saw
what
and
when’
audit
trail.
2.
Streamlined
Workflow
ACES
is
purpose-‐built
to
comprehensively
manage
clinical
trials
and
interim
analyses,
including
the
documenta+on
and
firewalls
necessary
to
preserve
trial
integrity.
ACES
automates
many
tasks
–
like
DMC
no+fica+ons,
reports,
or
randomiza+on
and
treatment
updates
for
IWRS
and
drug
supply.
It’s
web-‐based
and
easily
deployed
in
any
seXng.
3.
Decision
Engine
Integra/on
It’s
what
sets
ACES
apart
from
ordinary
document
management
packages
like
Documentum
and
SharePoint-‐based
apps.
ACES
ability
to
integrate
these
engines
is
helping
sponsors
of
all
sizes
make
even
their
most
complex
trials
more
rou+ne.
Typical
Decision
Engines
can
involve
dose
selec+on,
randomiza+on
schemes,
drug
supply
triggers,
early
stopping
rules,
adap+ve
design
simula+ons,
and
condi+onal
power
calcula+ons.
The
results
are
reported
as
specified
in
the
protocol,
and
only
to
those
permiJed.
3. Case Study - ACES Deployed in a Seamless
Phase 2 / 3 Adaptive Trial
The
Trial
Design
and
ACES
Ini+ally,
randomize
subjects
equally
across
four
treatment
arms,
then
perform
interim
analysis
once
enrollment
reaches
about
100
subjects
in
each
arm.
The
trial’s
interim
analysis
decision
rules:
1. Early
termina+on
for
fu+lity
2. Dose
selec+on:
select
one
or
two
most
ac+ve
doses
(observed
paJerns
of
response
rates)
with
placebo
to
move
into
trial’s
2nd
stage
3. Sample
size
increase:
a
one-‐+me
increase
based
on
condi+onal
power
for
2nd
stage
The
dose
selec+on
rules
were
also
loaded
into
ACES,
together
with
the
randomiza+on
table
and
treatment
codes.
4. Secure Reports and Communications
Between Sponsor – DMC – ISC – Site
ACES
Supports
DMC
The
trial’s
DMC
reviewed
the
analysis
report,
suppor+ng
tables,
lis+ngs,
and
graphs,
provided
with
ACES
and
made
their
recommenda+on
to
the
sponsor.
ACES
securely
stored
the
recommenda+on
and
triggered
no+fica+on
to
the
sponsor
company
representa+ves
to
review
and
accept.
The
pivotal
VALOR
trial
valortrial.com
is
an
example
of
ACES
use
to
support
a
sample-‐size
re-‐es+ma+on
confirmatory
study
in
oncology.
5. ACES Use Documented at ASCO
Protecting the Integrity of Adaptive Designs
(Per
the)
Guidance
documents
by
FDA
and
EMA
for
DSMB
and
Adap>ve
Trial
Design,
sugges>ng
‘A
well-‐trusted
firewall
established
for
trial
conduct
...
can
help
provide
assurance
that
sta>s>cal
and
opera>onal
biases
have
not
been
introduced.’
Cytel’s
Cyrus
Mehta
and
Eric
Silva
with
Sunesis
Pharmaceu+cals
co-‐authors
From
their
accepted
ASCO
2012
poster
presenta+on
