The document discusses decentralized clinical trials (DCT) and the need for collaboration to accelerate their adoption. It defines DCT and outlines their 17-year history prior to the COVID-19 pandemic accelerating their use. In 2020, surveys found most sponsors and CROs increasing DCT and most participants experiencing changes due to the pandemic. The document advocates for pairing the right decentralized methods and tools to each study and identifies barriers to adoption like regulatory issues. It proposes a Decentralized Trials & Research Alliance to enable collaboration and proposes meta-collaboration across initiatives to streamline efforts and avoid redundancy.
Decentralized Clinical Trials, presentaiton by Craig Lipset for mHealth IsraelLevi Shapiro
Decentralized Clinical Trials, presentaiton by Craig Lipset for mHealth Israel, April 20, 2021. Origin Story: Centralization Enables Decentralization. Analogous potential for centralization
leading to decentralization in clinical trials. Decentralization: Purpose and potential benefits, including resilience and
business continuity. Pre-Pandemic DCT Timeline: 17-year History Prior to COVID-19. Seasons of Decentralization in 2020. Spring of Continuity, Summer of Restarts, Fall of Commitment, Winter of Pathways to Scale. 79% of sponsors / CROs increasing DCT. 90% of participants experiencing change. 75% focus on going hybrid. 73% of Sites Will continue to use telemedicine beyond the pandemic. 76% have accelerated their DCT Strategies.Leading Implementation Strategy: Pairing DCT Toolkit to Study Needs. Identify the decentralized research methods and tools needed by the medicine portfolio. Ensure aligned SOPs & training, identify new partners, modify protocols/templates. Pair the “right” method/tool to each study
based upon diverse criteria. Barriers to Scaled Adoption of Decentralized Trials: Regulatory ambiguity, Global variability, Technology interop & data flow, Investigator & patient readiness, Endpoint limitations, Organization culture. Forecasts and Futures. Choice & Flexibility for Participants on a Visit-by-Visit Basis. Research Sites Empowered to Use Their Existing Technology. New Opportunities to Engage Treating Physicians Enables Research as a Care Option. Observational
“All-Comer” Studies and Platform Trials with DCT Bring Research to People.
Decentralized Trials in the Digital Era: “Rethinking Hybrid”Craig Lipset
Presentation at Society for Clinical Data Management - India meeting on 27 June 2020.
Addresses the past and the future of decentralized clinical trials.
Data Integrity in Decentralized Clinical Trials (DCTs)InsideScientific
Experts expand on the need for a comprehensive understanding of all sources of data in DCTs, and the need to evaluate those data centrally in real time to mitigate the risks associated with their capture (including data capture at the edge of the network (wearables)).
Every disruptive innovation must be complemented by adapted procedures, and this also applies to decentralized clinical trials (DCTs). Traditionally, sites entered clinical trial data in an Electronic Data Capture (EDC) system and these source data were verified at the site to confirm accuracy. Risk based monitoring focused on site level metrics such as screen failure rates, query rates, Serious Adverse Events (SAEs) reported, missed/late visits, etc. With DCTs, as source data are collected directly from participants this is no longer an option and a different approach is required to ensure the quality and integrity of the data. As a rule, a comprehensive understanding of all sources for data capture in a clinical trial and the process for centralization is essential. Also, it is important to evaluate the data collected in real time to allow early interventions that will ensure data integrity for regulatory submission.
In this webinar, Chitra Lele describes how centralized monitoring strategies can help aggregate and analyze data in real time and provide insights to a variety of functional teams across the trial continuum. Daniel Gutierrez describes how the Clinerion platform can boost data integrity in DCTs. The technology transforms global data sources to one query-able data model for structured medical data, while ensuring that the data keep its full resolution and integrity during aggregated queries.
Pierre Etienne talks about the expanding role of mobile Health Care Professionals (HCPs) and their crucial role in protecting data integrity. Clifton Chow finishes with a comparison of several artificial intelligence (AI) based binary classifiers for detecting the integrity of data obtained from Internet of Things (IoT) enabled wearable sensors.
Decentralized clinical trials (DCT) are defined as studies “executed through telemedicine and mobile/local healthcare providers, using processes and technologies differing from the traditional clinical trial model.”
Remote decentralized clinical trials (RDCT) are defined as “an operational strategy for technology-enhanced clinical trials that are more accessible to [participants] by moving clinical trial activities to more local settings.”
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.
This Risk Based Monitoring - Impact on Sites overview presentation, on targeted topics, was delivered to the ACRP Raleigh - Durham Chapter's Annual Conference in 2013.
Decentralized Clinical Trials, presentaiton by Craig Lipset for mHealth IsraelLevi Shapiro
Decentralized Clinical Trials, presentaiton by Craig Lipset for mHealth Israel, April 20, 2021. Origin Story: Centralization Enables Decentralization. Analogous potential for centralization
leading to decentralization in clinical trials. Decentralization: Purpose and potential benefits, including resilience and
business continuity. Pre-Pandemic DCT Timeline: 17-year History Prior to COVID-19. Seasons of Decentralization in 2020. Spring of Continuity, Summer of Restarts, Fall of Commitment, Winter of Pathways to Scale. 79% of sponsors / CROs increasing DCT. 90% of participants experiencing change. 75% focus on going hybrid. 73% of Sites Will continue to use telemedicine beyond the pandemic. 76% have accelerated their DCT Strategies.Leading Implementation Strategy: Pairing DCT Toolkit to Study Needs. Identify the decentralized research methods and tools needed by the medicine portfolio. Ensure aligned SOPs & training, identify new partners, modify protocols/templates. Pair the “right” method/tool to each study
based upon diverse criteria. Barriers to Scaled Adoption of Decentralized Trials: Regulatory ambiguity, Global variability, Technology interop & data flow, Investigator & patient readiness, Endpoint limitations, Organization culture. Forecasts and Futures. Choice & Flexibility for Participants on a Visit-by-Visit Basis. Research Sites Empowered to Use Their Existing Technology. New Opportunities to Engage Treating Physicians Enables Research as a Care Option. Observational
“All-Comer” Studies and Platform Trials with DCT Bring Research to People.
Decentralized Trials in the Digital Era: “Rethinking Hybrid”Craig Lipset
Presentation at Society for Clinical Data Management - India meeting on 27 June 2020.
Addresses the past and the future of decentralized clinical trials.
Data Integrity in Decentralized Clinical Trials (DCTs)InsideScientific
Experts expand on the need for a comprehensive understanding of all sources of data in DCTs, and the need to evaluate those data centrally in real time to mitigate the risks associated with their capture (including data capture at the edge of the network (wearables)).
Every disruptive innovation must be complemented by adapted procedures, and this also applies to decentralized clinical trials (DCTs). Traditionally, sites entered clinical trial data in an Electronic Data Capture (EDC) system and these source data were verified at the site to confirm accuracy. Risk based monitoring focused on site level metrics such as screen failure rates, query rates, Serious Adverse Events (SAEs) reported, missed/late visits, etc. With DCTs, as source data are collected directly from participants this is no longer an option and a different approach is required to ensure the quality and integrity of the data. As a rule, a comprehensive understanding of all sources for data capture in a clinical trial and the process for centralization is essential. Also, it is important to evaluate the data collected in real time to allow early interventions that will ensure data integrity for regulatory submission.
In this webinar, Chitra Lele describes how centralized monitoring strategies can help aggregate and analyze data in real time and provide insights to a variety of functional teams across the trial continuum. Daniel Gutierrez describes how the Clinerion platform can boost data integrity in DCTs. The technology transforms global data sources to one query-able data model for structured medical data, while ensuring that the data keep its full resolution and integrity during aggregated queries.
Pierre Etienne talks about the expanding role of mobile Health Care Professionals (HCPs) and their crucial role in protecting data integrity. Clifton Chow finishes with a comparison of several artificial intelligence (AI) based binary classifiers for detecting the integrity of data obtained from Internet of Things (IoT) enabled wearable sensors.
Decentralized clinical trials (DCT) are defined as studies “executed through telemedicine and mobile/local healthcare providers, using processes and technologies differing from the traditional clinical trial model.”
Remote decentralized clinical trials (RDCT) are defined as “an operational strategy for technology-enhanced clinical trials that are more accessible to [participants] by moving clinical trial activities to more local settings.”
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.
This Risk Based Monitoring - Impact on Sites overview presentation, on targeted topics, was delivered to the ACRP Raleigh - Durham Chapter's Annual Conference in 2013.
eCOA and ePRO and Their Use in Clinical Trials_pptxClinosolIndia
Virtual clinical trials are becoming even more popular because of technology advances. They offer enormous benefits to sponsors and patients. However, there are challenges. One of the key elements of a virtual clinical trial is ePRO and eCOA.
Patient-reported outcome (PRO) endpoints are often necessary to adequately evaluate the treatment benefit provided by new medical products (e.g., drugs) in clinical trials.
The movement from paper-based to electronic PRO (ePRO) data collection has enhanced the integrity and accuracy of PRO data in clinical trials.
The US Food and Drug Administration has made it clear that electronic capture of clinical trial source data is preferred over paper-based data collection.
Electronic Data Capture (EDC) Systems: Streamlining Data CollectionClinosolIndia
Electronic Data Capture (EDC) systems are software platforms designed to streamline and enhance the process of collecting, managing, and monitoring clinical trial data electronically. EDC systems replace traditional paper-based data collection methods, offering numerous advantages for clinical research. Here's how EDC systems streamline data collection in clinical trials
Differences Between Satellite Sites and Multi Site Research ClinicsTrialJoin
In the clinical research industry, there are two terms that we commonly encounter: satellite sites and multi sites. Although these two might sound the same, they’re not! The concept of a satellite site is much different than multi-site clinics. However, we can still see a large part the industry that is confusing these two terms.
Below, we’ll explain to you the difference between a satellite site and multi-site clinics.
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.
This webinar will tell you what you need to know about clinical trials, their history, and help you prepare for a trial. If you’re currently considering participating in a clinical trial, we hope that this webinar helps to answer many of your questions.
In the presentation you'll learn the difference between different types of clinical trial and the design and purpose of clinical trials, and you'll get an inside look at the approval process.
The webinar was hosted by Dawn Richards, Director of Patient and Public Engagement at Clinical Trials Ontario and featured a panel of patients, James Davidson, Eric Pitters and Kathie LaForge.
Roles and Responsibilities of sponsor in conducting clinical trials as per GC...Dr B Naga Raju
Presentation on Roles and Responsibilities of sponsor in conducting clinical trials as per GCP-ICH for pursuing a subject in the course of PharmD programme under RGUHS
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.
Decentralized Monitoring in Clinical TrialsClinosolIndia
Decentralized monitoring in clinical trials refers to a modern approach to monitoring the progress, safety, and data integrity of clinical trials using remote and technology-driven methods. Traditional clinical trial monitoring involves frequent on-site visits by monitors to ensure that the trial is conducted according to the protocol and regulatory requirements. However, this approach can be resource-intensive, time-consuming, and may not always provide real-time insights.
Decentralized monitoring leverages technology, data analytics, and remote communication tools to monitor various aspects of clinical trials. Here are some key components of decentralized monitoring:
eCOA and ePRO and Their Use in Clinical Trials_pptxClinosolIndia
Virtual clinical trials are becoming even more popular because of technology advances. They offer enormous benefits to sponsors and patients. However, there are challenges. One of the key elements of a virtual clinical trial is ePRO and eCOA.
Patient-reported outcome (PRO) endpoints are often necessary to adequately evaluate the treatment benefit provided by new medical products (e.g., drugs) in clinical trials.
The movement from paper-based to electronic PRO (ePRO) data collection has enhanced the integrity and accuracy of PRO data in clinical trials.
The US Food and Drug Administration has made it clear that electronic capture of clinical trial source data is preferred over paper-based data collection.
Electronic Data Capture (EDC) Systems: Streamlining Data CollectionClinosolIndia
Electronic Data Capture (EDC) systems are software platforms designed to streamline and enhance the process of collecting, managing, and monitoring clinical trial data electronically. EDC systems replace traditional paper-based data collection methods, offering numerous advantages for clinical research. Here's how EDC systems streamline data collection in clinical trials
Differences Between Satellite Sites and Multi Site Research ClinicsTrialJoin
In the clinical research industry, there are two terms that we commonly encounter: satellite sites and multi sites. Although these two might sound the same, they’re not! The concept of a satellite site is much different than multi-site clinics. However, we can still see a large part the industry that is confusing these two terms.
Below, we’ll explain to you the difference between a satellite site and multi-site clinics.
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.
This webinar will tell you what you need to know about clinical trials, their history, and help you prepare for a trial. If you’re currently considering participating in a clinical trial, we hope that this webinar helps to answer many of your questions.
In the presentation you'll learn the difference between different types of clinical trial and the design and purpose of clinical trials, and you'll get an inside look at the approval process.
The webinar was hosted by Dawn Richards, Director of Patient and Public Engagement at Clinical Trials Ontario and featured a panel of patients, James Davidson, Eric Pitters and Kathie LaForge.
Roles and Responsibilities of sponsor in conducting clinical trials as per GC...Dr B Naga Raju
Presentation on Roles and Responsibilities of sponsor in conducting clinical trials as per GCP-ICH for pursuing a subject in the course of PharmD programme under RGUHS
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.
Decentralized Monitoring in Clinical TrialsClinosolIndia
Decentralized monitoring in clinical trials refers to a modern approach to monitoring the progress, safety, and data integrity of clinical trials using remote and technology-driven methods. Traditional clinical trial monitoring involves frequent on-site visits by monitors to ensure that the trial is conducted according to the protocol and regulatory requirements. However, this approach can be resource-intensive, time-consuming, and may not always provide real-time insights.
Decentralized monitoring leverages technology, data analytics, and remote communication tools to monitor various aspects of clinical trials. Here are some key components of decentralized monitoring:
4/22/2020 Originality Report
https://ucumberlands.blackboard.com/webapps/mdb-sa-BB5a31b16bb2c48/originalityReport/ultra?attemptId=c27f66fc-c5df-47dc-9f48-d005b34b35d9… 1/4
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SafeAssign Originality Report
Spring 2020 - Data Science & Big Data Analy (ITS-836-9) - Second Bi-T… • Final Exam (project)
%59Total Score: High riskNaveeda Reddy Anugu
Submission UUID: eb75ebf8-071b-3035-cadd-c5c1220ab248
Total Number of Reports
1
Highest Match
59 %
Final.pptx
Average Match
59 %
Submitted on
04/22/20
10:09 PM CDT
Average Word Count
1,130
Highest: Final.pptx
%59Attachment 1
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Word Count: 1,130
Final.pptx
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FINAL SPONSOR PRESENTATION
Naveeda Reddy Anugu
University of the Cumberlands
Professor: Dr Kelly Wibbenmeyer
DATE: 04/22/2020
SITUATION
The hospital intends to utilize patient data gathers to enhance the health of its members and offer services at relatively lower costs
This is in response to patients’ previous complaints about the high cost of treatment and associated low health results
The impacts points toward ineffective treatment plans and harmful prescription of medication to susceptible populations
Data collected include diseases treated and billed for, prescriptions were given, and the types of treatments given
The data may be used in big data analytics to enhance treatment options, customize patients’ risks and to support customized treatment intervention
Advanced and frontier big data analytics has the potential to improve health. Data can be used to distinguish between effective and ineffective medical practices
depending on an individual patient. Aetna, is a company that collects data for more than 20 million customers and from its pilot project studies, it is evident that
health institutions can promote health and reduce costs by utilizing Big Data Analytics. 2
PROJECT GOALS
The project entails unveiling an invention that will permit big data analytics to buttress decisions and intervention in healthcare settings
The aim of the intervention include: Creation of patient centered decision making support systems
1
2
3
4
2
https://ucumberlands.blackboard.com/webapps/mdb-sa-BB5a31b16bb2c48/originalityReport?attemptId=c27f66fc-c5df-47dc-9f48-d005b34b35d9&course_id=_114115_1&download=true&includeDeleted=true&print=true&force=true
4/22/2020 Originality Report
https://ucumberlands.blackboard.com/webapps/mdb-sa-BB5a31b16bb2c48/originalityReport/ultra?attemptId=c27f66fc-c5df-47dc-9f48-d005b34b35d9… 2/4
The aim of the intervention include: Creation of patient-centered decision making support systems
Utilization of patient's data contained in clinical trails, insurance companies records and in patient’s health reco.
A Health Catalyst Overview: Learn How a Data First Strategy Can Drive Increas...Health Catalyst
Without the pressure of a one-on-one demo, you can join a crowd of peers to ‘kick the tires’ if you will, as you listen to Jared Crapo—a sought after healthcare strategist—talk about what a data-first strategy is, and the strategic components to a data-first strategy employing a data operating system, a breakthrough engineering approach that combines the features of data warehousing, clinical data repositories, and health information exchanges in a single, common-sense technology platform that turns data into actionable assets used for all types of outcomes improvements.
Lest you worry about too much ‘pie in the sky’ strategy talk with few results to show, Sam Turman, Senior Solution Architect, will provide tangible solution demonstrations that are driving material results. Even if you aren’t in the market for Health Catalyst solutions and services, you will be able to:
Think with more clarity through your approach to overcoming the current market challenges.
Reconsider the strategy you are employing to build cross-organizational awareness and support to put a data-first plan at the center of your plan.
Define action you can take today to assess your gaps, understand your options, and accelerate your progress to drive outcomes improvements.
Join us and you won’t be disappointed. Jared is one of those types of thinkers that many pay big money to listen to and it is our fortune to have 60 minutes with him to think deeply about moving healthcare forward, one patient at a time. We hope you can join us.
Role of Clinical Data Management in Risk-Based MonitoringClinosolIndia
Clinical Data Management (CDM) plays a significant role in the implementation of Risk-Based Monitoring (RBM) within clinical trials. RBM is an approach that focuses monitoring efforts on areas of highest risk, thereby optimizing resource allocation, enhancing data quality, and ensuring patient safety. Here's how CDM contributes to RBM
The true clinical, economic and social value of remote patient monitoring is yet to be exploited. Trusts have been challenged to do more with less, but telehealth has suffered from expensive, proprietary systems, existing in isolation with too little thought given to security. The purpose of this study is to investigate whether cost-effective remote patient monitoring can promote pro-active self-management and can avoid expensive emergency admissions. Successful deployment is dependent on scrutiny of
the details of the challenge and the solution.
The MediPi project is a clinically lead, open-source platform aimed at providing a secure, extensible, low cost, remote patient monitoring solution. Patients with Heart Failure, COPD and Diabetes were given Raspberry Pi based touchscreen units and asked to submit daily measurements from their homes using blood pressure cuffs, pulse oximeters, scales, thermometers and subjective yes/no questionnaires about how they felt. The MediPi Concentrator server API allows any registered clinical system secure access to the data, for clinicians to view trends, set thresholds and respond directly to the patient. Clinician’s reports showed that patients were receptive to the technology and keen to actively manage their care, with anxiety reduced in 34% patients. The cost of the monitoring per patient was lower than other studies with potential for further savings. The MediPi system proved robust but Bluetooth communication issues with certain physiological devices prevented the study from reporting on downstream economic savings.
A decentralized clinical trial (DCT) is an innovative approach to conducting clinical research that leverages digital technologies and remote processes to enable greater patient participation and data collection outside of traditional clinical trial settings. In a decentralized trial, participants have the flexibility to engage in the study from their own homes or local healthcare facilities, reducing the need for frequent visits to centralized trial sites.
The key features of decentralized clinical trials include:
Remote Participant Engagement: DCTs utilize various digital tools and platforms to facilitate participant engagement. This may involve virtual visits, telemedicine consultations, electronic informed consent, and remote monitoring of participants' health status and adherence to study protocols.
Mobile and Wearable Technologies: Mobile devices and wearable sensors play a significant role in decentralized trials. They enable real-time data collection, including vital signs, patient-reported outcomes, medication adherence, and other relevant health data. These technologies enhance convenience for participants while providing continuous, objective data for researchers.
Virtual Study Operations: DCTs employ virtual tools for study management and coordination. These include electronic data capture systems, online study training, remote monitoring of data quality, and electronic trial master files. Virtual platforms facilitate seamless communication between study teams, investigators, and participants.
Local Healthcare Providers: In decentralized trials, local healthcare providers or clinical research sites often play a more substantial role in participant recruitment, enrollment, and follow-up. These providers may be responsible for conducting study visits, collecting samples, and implementing study interventions, while ensuring compliance with the trial protocol.
Data Security and Privacy: Protecting participant data and maintaining privacy are critical in decentralized trials. Robust data security measures, such as encryption, secure data transmission, and compliance with privacy regulations like GDPR or HIPAA, are implemented to safeguard participants' sensitive information.
Disruptors in the Medical Imaging IndustryBill Kelly
An overview of the Disruptors in the Medical Imaging Market. This free webinar will also give you more insight on the various factors that influence the market. We touch on results from a survey of a survey of 147 radiologists highlight the importance of reimbursement changes –both “appropriateness” measures and value-based medicine – as the most significant factors that will impact the imaging market.
Learn more about the next stage in Meaningful Use and how that affects today's health care providers.Will there be changes in the measures required to receive Medicare or Medicaid Incentive funds? Will there be any changes to data capturing? Find out in this informative presentation.
Presentation by Jens Lundgren, Rigshospitalet, University of Copenhagen - European AIDS Clinical Society, Denmark, at AIDS 2018 conference during the joint ECDC and EACS satellite "Getting to 90: Addressing inequalities in the HIV continuum of care in Europe and Central Asia"
MPG Life Sciences Software Market Snapshot October 2020Madison Park Group
We are pleased to present our life sciences software market snapshot for October 2020.
Madison Park Group is a unique investment banking firm that takes a "strategy first" approach to advising software companies. Our partners have developed and advised numerous successful companies as operators, investors and investment bankers.
Rohan Khanna, Jonathan Adler and James Tomasullo spearhead the firm's efforts in the space.
Closed-Loop EHR Integration Targets Burnout, Improves WorkflowsHealth Catalyst
The widespread adoption of EHRs has significantly altered the workflows of physicians and other healthcare workers. However, while EHRs were developed to better organize patient data and improve care coordination, most require significant and sometimes duplicative documentation, often resulting in workforce burnout.
Health Catalyst’s new Closed-Loop Analytics™ service tackles the EHR workload challenge by helping healthcare providers optimize their use of analytics in existing workflows. Closed-Loop Analytics leverages the knowhow of Health Catalyst clinical workflow experts with work experience at EHR vendors such as Epic, Cerner, and Allscripts. The team works with health systems to deploy analytics solutions directly into the EHR and better leverage analytics to simplify workflows and improve outcomes.
In this webinar, you will learn how Closed-Loop Analytics can help you:
- Determine where end-users are wasting time on duplicative tasks and how to optimize the EHR build to develop efficiencies.
- Develop analytical tools and deploy them into the EHR for increased utilization and improved insights at the point of decision-making.
- See the value of expanded integration capabilities with an analytics tool embedded into the EHR, such as launching to a patient’s chart or initiating an update to a treatment team.
- Understand how interoperability and FHIR are revolutionizing workflow integration and how you can put them to work.
Evolution in the Role of Patient Participation in Clinical ResearchCraig Lipset
Presentation by Craig Lipset at Precision Medicine World Congress (Palo Alto CA, 24 January 2020).
This presentation shares a "top 10 list" of places where patient participation in research is facing radical change for the better.
Growth Opportunities for Entrepreneurs in Clinical Research ServicesCraig Lipset
Presentation by Craig Lipset for mHealth Israel on February 12 2020 hosted at Google Tel Aviv.
This talk reviews current challenges and trends in clinical trials today, followed by a forecast for trials will be impacted by decentralization, distribution, democratization, and disruption.
The presentation concludes with some considerations for entrepreneurs seeking to grow new solutions for clinical trials.
The 17-Year History of Remote and Virtual Clinical TrialsCraig Lipset
Many look at decentralized (or remote or virtual) clinical trials as something "new". In fact the model has been around for nearly two decades. So why is adoption so low among the research community?
Presentation by Craig Lipset at the NIH Collaboratory Grand Rounds on July 26 2019 in Bethesda MD.
Full replay will be available at: https://rethinkingclinicaltrials.org/grand-rounds-hub/
This presentation shares what industry best matches the perspective of a clinical research sponsor, and maps digital solutions that may enhance, disrupt, or ultimately displace roles in clinical research.
NIH NSF Digital Clinical Trials Workshop 02Apr2019 [Lipset]
NIH NSF Digital Clinical Trials Workshop 02Apr2019 [Lipset]Craig Lipset
Presentation by Craig Lipset at the NIH / NSF "Digital Clinical Trials Workshop" on April 2 2019 in Bethesda MD.
https://www.nhlbi.nih.gov/events/2019/digital-clinical-trials-workshop-creating-vision-future
This presentation details two key themes for digital in medicine development as well as a range of incremental areas where digital is impacting clinical trials today.
CBS HITLAB Digital Health in Medicine Development 14May2019 [Lipset]Craig Lipset
Presentation by Craig Lipset at the Columbia Business School / HITlab executive education course on Digital Health Strategy on May 11 2019 in NYC.
This presentation shares implications for digital in medicine development including those that will be incremental, those that are disruptive and those that will displace incumbents.
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdfJim Jacob Roy
Cardiac conduction defects can occur due to various causes.
Atrioventricular conduction blocks ( AV blocks ) are classified into 3 types.
This document describes the acute management of AV block.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
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
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
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.
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
2. @craiglipset 2
Craig Lipset: About Me
Advisor
Faculty
Board Member Formerly
Views and positions expressed represent those of the presenter and not necessarily of the affiliations above
3. @craiglipset 3
Decentralized Clinical Trials [DCT]: Defined
Clinical Trials Transformation Initiative. Decentralized Clinical Trials. Published September 2018. https://www.ctti-
clinicaltrials.org/projects/decentralized-clinical-trials.
IMI Trials@Home. Glossary of Terms and Definitions Used. Updated April 2021.
https://trialsathome.com/wp-content/uploads/2021/04/D2.1-Glossary-of-terms-and-definitions_-2021Update_Final.pdf
[Clinical Trials] executed through telemedicine and
mobile/local healthcare providers (HCPs), using
procedures that vary from the traditional clinical trial
model (e.g., the investigational medical product [IMP] is
shipped directly to the trial participant).
Clinical Trials that make use of digital innovations and
other related methods to make them more accessible to
participants. By moving clinical trial activities to the
participant’s home or to other local settings this minimises
or eliminates physical visits to a clinical trial centre.
4. @craiglipset 4
“What’s in a name?
That which we call a rose by any other name would smell as sweet.”
The Benefits And Challenges
Of Siteless Clinical Trials
Remote Clinical Trials Market
Clinical Research Analysis 2021-2026
Virtual Clinical Trials Market
Size Worth $11.5 Billion By 2028
5. @craiglipset 5
Origin Story: Centralization Enables Decentralization
Central
site
Analogous potential for centralization
leading to decentralization in clinical trials
2008/2009 Case for Pfizer REMOTE study
Entity being decentralized: Investigator site
6. @craiglipset 6
Decentralization: Purpose
Clinical Trials Transformation Initiative. Decentralized Clinical Trials. Published September 2018.
https://www.ctti-clinicaltrials.org/projects/decentralized-clinical-trials.
…and from 2020
Resilience and
business continuity
8. @craiglipset 8
Seasons of Decentralization in 2020
Spring
of Continuity
Summer
of Restarts
Fall
of Commitment
Winter
of Pathways
to Scale
9. @craiglipset 9
Seasons of Decentralization in 2020
Spring
of Continuity
Summer
of Restarts
Fall
of Commitment
Winter
of Pathways
to Scale
79% of
Sponsors/CROs
Increasing DCT
Clinical Trials Europe, May 2020, n=184
90% of
Participants
Experiencing
Change
CISCRP 2020, n=38
10. @craiglipset 10
Seasons of Decentralization in 2020
Spring
of Continuity
Summer
of Restarts
Fall
of Commitment
Winter
of Pathways
to Scale
75% Focus on
Going Hybrid
ERT Survey Report: Virtual Trials and the COVID-19 Pandemic, June 2020
11. @craiglipset 11
Seasons of Decentralization in 2020
Spring
of Continuity
Summer
of Restarts
Fall
of Commitment
Winter
of Pathways
to Scale
73% of Sites Will
Continue to Use
Telemedicine
Beyond the
Pandemic
12. @craiglipset 12
Seasons of Decentralization in 2020
Spring
of Continuity
Summer
of Restarts
Fall
of Commitment
Winter
of Pathways
to Scale
76% Have
Accelerated Their
DCT Strategies
Oracle Research Report: Accelerated Evolution,
November 2020
13. @craiglipset 13
Leading Implementation Strategy: Pairing DCT Toolkit to Study Needs
1
Identify the decentralized research methods
and tools needed by the medicine portfolio
Ensure aligned SOPs & training,
identify new partners,
modify protocols/templates
eConsent
Video visits
Home health
Local labs+imaging
Remote monitoring
Digital endpoints
Central site/PI
Home drug supply
2
Pair the “right” method/tool to each study
based upon diverse criteria
Patient insights
Drug delivery
Safety profile
Intelligence
Country requirements
Regulatory feedback
Environmental risk
Organizational culture
14. @craiglipset 14
Barriers to Scaled Adoption of Decentralized Trials
Regulatory
ambiguity
Global
variability
Technology
interop &
data flow
Investigator
& patient
readiness
Endpoint
limitations
Organization
culture
15. @craiglipset 15
Decentralized Trials & Research Alliance
The Mission
The DTRA will enable
collaboration of stakeholders to
accelerate the adoption of
patient-focused, decentralized
clinical trials and research
within life sciences and
healthcare through education
and research.
The Vision
Research participation made
accessible to everyone,
enabled by the consistent,
widespread adoption of
appropriate decentralized
research methods.
18. @craiglipset 18
Meta-Collaboration to Accelerate Adoption
o Collaboration across the collaborations
o Each collaboration’s charter & membership bring unique strengths/limitations
o Ensure transparency
o Avoid redundancy
o Maintain clear charters and boundaries
o Trigger hand-offs
19. @craiglipset 19
Forecasts and Futures
Choice & Flexibility
for Participants
on a Visit-by-Visit
Basis
Research Sites
Empowered to Use
Their Existing
Technology
New Opportunities
to Engage
Treating Physicians
Enables Research as
a Care Option
Observational
“All-Comer” Studies
and Platform Trials
with DCT Bring
Research to People