This document summarizes a webinar on streamlining data management for clinical trials. The webinar covered the need for streamlined approaches given rising drug development costs. It discussed areas for improving efficiencies, including using standards, a parallel approach, identifying key reviewers, and tailoring processes based on trial type (e.g. a "Premier Express" approach for small phase 1 trials). An example case study showed how streamlining tasks and performing work in parallel reduced timelines for developing case report forms, annotated case report forms, databases, and edit checks for a small phase 1 trial from 9 weeks to 5 weeks.
Clinical Data Management Training @ Gratisol LabsGratisol Labs
Clinical data management involves processing clinical trial data using computer applications and database systems. It supports the collection, cleaning, and management of subject data. Key aspects of clinical data management include CRF design, database setup, data entry, discrepancy management, medical coding, quality control, and database lock. The goal is to ensure the integrity and quality of clinical trial data.
Appalla Venkataprabhakar and I presented this at the Oracle\'s Annual Clinical Development and Safety Conference 2010 at Hyderabad, India on 6th October 2010.
1. Clinical data management systems are needed for multi-center clinical trials to manage large volumes of data from multiple sites in real-time.
2. India has potential to grow as a clinical data management hub due to its large, skilled workforce and lower costs compared to other countries.
3. Stakeholders in clinical data management include sponsors, CROs, sites, and regulators who require standardized, clean data to be efficiently captured and reported.
This document outlines the process of clinical data management. It discusses the key steps and technologies involved in digitization, electronic data capture, data analytics, document management, data standardization, and infrastructure/security. The main stages described are feasibility analysis, system selection, design and implementation, data collection, quality control, and regulatory submission preparation. Technologies mentioned include EDC tools like Oracle Clinical, data standards like CDISC SDTM, and document management solutions from vendors such as Documentum.
Clinical Data Management (CDM) is a critical phase in clinical research that leads to generating high-quality, reliable data from clinical trials. CDM involves collecting, integrating, and ensuring the availability of appropriate quality and cost data. It encompasses entering, verifying, validating, and quality controlling the data gathered during clinical trials. The goal of CDM is to ensure the data supports conclusions drawn from the research.
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.
The document provides information on several clinical data management systems and software, including Oracle Clinical, SAS Clinical Software, TCS Clin-E2E Software, Cognos 8 Business Intelligence Software, Symetric Software, Akaza's OpenClinica Software, SigmaSoft's DMSys Software, and Progeny Clinical Software. It discusses their key features for managing clinical trials data such as electronic data capture, reporting, security, compliance with industry standards, and integration with other systems.
Clinical Data Management Plan_Katalyst HLSKatalyst HLS
A data management plan (DMP) ensures consistent and effective clinical data management practices throughout a clinical trial. The DMP describes all data management activities, roles, and responsibilities to promote standardized data handling. It provides an agreement between parties on data management deliverables. The DMP covers components like data flow, capture, setup, entry, transfer, processing, coding, safety handling, external data, and database locking. It serves to plan, communicate, and reference data management tasks. Developing a thorough DMP helps ensure quality and regulatory compliance in data collection and analysis.
Clinical Data Management Training @ Gratisol LabsGratisol Labs
Clinical data management involves processing clinical trial data using computer applications and database systems. It supports the collection, cleaning, and management of subject data. Key aspects of clinical data management include CRF design, database setup, data entry, discrepancy management, medical coding, quality control, and database lock. The goal is to ensure the integrity and quality of clinical trial data.
Appalla Venkataprabhakar and I presented this at the Oracle\'s Annual Clinical Development and Safety Conference 2010 at Hyderabad, India on 6th October 2010.
1. Clinical data management systems are needed for multi-center clinical trials to manage large volumes of data from multiple sites in real-time.
2. India has potential to grow as a clinical data management hub due to its large, skilled workforce and lower costs compared to other countries.
3. Stakeholders in clinical data management include sponsors, CROs, sites, and regulators who require standardized, clean data to be efficiently captured and reported.
This document outlines the process of clinical data management. It discusses the key steps and technologies involved in digitization, electronic data capture, data analytics, document management, data standardization, and infrastructure/security. The main stages described are feasibility analysis, system selection, design and implementation, data collection, quality control, and regulatory submission preparation. Technologies mentioned include EDC tools like Oracle Clinical, data standards like CDISC SDTM, and document management solutions from vendors such as Documentum.
Clinical Data Management (CDM) is a critical phase in clinical research that leads to generating high-quality, reliable data from clinical trials. CDM involves collecting, integrating, and ensuring the availability of appropriate quality and cost data. It encompasses entering, verifying, validating, and quality controlling the data gathered during clinical trials. The goal of CDM is to ensure the data supports conclusions drawn from the research.
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.
The document provides information on several clinical data management systems and software, including Oracle Clinical, SAS Clinical Software, TCS Clin-E2E Software, Cognos 8 Business Intelligence Software, Symetric Software, Akaza's OpenClinica Software, SigmaSoft's DMSys Software, and Progeny Clinical Software. It discusses their key features for managing clinical trials data such as electronic data capture, reporting, security, compliance with industry standards, and integration with other systems.
Clinical Data Management Plan_Katalyst HLSKatalyst HLS
A data management plan (DMP) ensures consistent and effective clinical data management practices throughout a clinical trial. The DMP describes all data management activities, roles, and responsibilities to promote standardized data handling. It provides an agreement between parties on data management deliverables. The DMP covers components like data flow, capture, setup, entry, transfer, processing, coding, safety handling, external data, and database locking. It serves to plan, communicate, and reference data management tasks. Developing a thorough DMP helps ensure quality and regulatory compliance in data collection and analysis.
This document discusses clinical data management (CDM) systems and processes. It defines key terms like source data, source documents, and raw data. It then describes the essential steps in CDM including initial planning, data collection, review and verification, coding, query resolution, data entry and validation, output and archiving. Finally, it outlines requirements for a good CDM system including system validation, security, change control, and archiving. The goal of CDM is to generate an accurate, high-quality clinical trial database while ensuring compliance with regulations.
This document provides guidance on clinical data management practices for analyzing research data. It discusses key aspects of clinical data management including planning, data collection, review, entry, coding, querying, output, and archiving. Ensuring accurate data capture and high quality databases is the objective. Adherence to good clinical data management practices and regulatory guidelines is emphasized. Effective planning, standardized processes, trained personnel, quality control measures, and system validation are seen as important for generating reliable data for analysis and reporting.
The document outlines the process for setting up clinical data management and pharmacovigilance processes. It discusses developing the protocol and case report forms, designing the database, installing software like Oracle Inform and Argus, and preparing documents like the data management plan. It also describes the data entry, validation, query resolution, medical coding, biostatistics, and database locking and freezing aspects of the clinical data management and pharmacovigilance setup process.
Clinical research and clinical data management - Ikya Globalikya global
Data management functions in clinical trials—extensive data cleaning, full query management, protocol deviation management, batch processing, as examples—have traditionally been served by stand-alone clinical data management systems (CDMS), whose input is from paper forms or from separate electronic data capture systems. Distinct electronic data capture and data management systems require data integration, with resulting timing and reconciliation issues.
1. A clinical data management system (CDMS) is used to manage data from clinical trials by storing data entered in case report forms (CRFs) by investigators.
2. Data management involves planning, collection, entry, validation, manipulation, backup and documentation of data to create a high quality database. Commonly used CDMS tools include Oracle Clinical, ClinTrial, Macro and eClinical Suite.
3. Open source CDMS tools include OpenClinica, openCDMS, TrialDB and PhOSCo which are free. All CDMS tools ensure an audit trail and management of discrepancies according to roles and user access levels.
CRO
This document provides an overview of a CRO's full-service clinical data management capabilities. It has over 25 years of experience and a team of 70 staff across Europe and India. The CRO offers a full range of CDM services including project management, database design, data entry, validation, and IT infrastructure validated to industry standards. It has experience across therapeutic areas and geographies, using mature CDISC-compliant platforms. The CRO maintains data security, backup/recovery policies, and has qualified experienced staff to deliver high-quality CDM services.
YEARS
Track Record
Clinical data management (CDM) ensures the collection, integration, and availability of high-quality data from clinical trials. It supports clinical research and analysis across different study types. CDM tools like CDMS help manage large amounts of multicenter trial data. Regulations like 21 CFR Part 11 require electronic records and validated systems to ensure accurate, reliable data. Guidelines from SCDM and CDISC provide standards for good CDM practices and data collection. CDM processes clinical research data from source documents through database entry, quality checking, analysis, and archiving to support regulatory approval and conclusions about clinical results.
Clinical data management is the process of collecting, validating, and cleaning data from clinical trials. It aims to ensure data quality and integrity. Key aspects of clinical data management include electronic data capture, establishing data standards, using clinical data management systems, and performing activities like data collection, validation, and discrepancy management. It follows guidelines from organizations like SCDM and regulations like 21 CFR Part 11.
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.
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
Have full fleged clinical trial data management systems which bring them a good amount of business and revenue.
CDM is a fundamental process which controls data accuracy of each trial besides helping the timelessness to be achieved.
It helps in linking clinical research co-ordinator = who monitor all the sites & collects the data.
it Links with biostatisticians = who analyze, interpret and report data in clinically meaningful way.
Electronic Data Capture & Remote Data CaptureCRB Tech
CRB Tech is one of the best leading Software Development Company in Pune. We are offering Software Development Services as well as IT Training including Java, Dot Net, SEO and Clinical Research training in pune.
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.
Clinical data management (CDM) involves collecting, validating, and cleaning patient data from clinical trials to ensure it is complete, consistent, and compliant. A CDM team typically includes clinical data managers, programmers, and data entry associates. They are involved in all stages from study setup to completion. Key CDM activities include designing case report forms, programming data validation checks, overseeing data entry into clinical data management systems, manually and electronically cleaning the data, reconciling safety data with external sources, and locking the database once the trial is complete and the data is ready for analysis. The goal is to generate high-quality clinical trial data that can be analyzed to advance drug development timelines.
Introduction to Oracle Clinical Overview in Clinical Data Management in Clinical Trials of Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
Clinical data management involves processing clinical trial data through activities like data entry, validation, query resolution and medical coding. It aims to ensure the integrity and quality of clinical trial data, which regulatory agencies rely on for drug approval. The document provides an overview of the clinical data management process and roles involved at each stage, from study set-up to closeout.
Study setup_Clinical Data Management_Katalyst HLSKatalyst HLS
Introduction to Study Setup in Clinical Data Management in Clinical Trials of Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
The 3 main types of reports are:
1) Summary reports that summarize the data
2) Listings reports that list the entire data as is
3) Figures and graphs that provide graphical representations of the data
A programming plan outlines the algorithms, data presentations, and programming standards to generate derived datasets. Test plans are created for quality control to validate the derived datasets and reports meet specifications. SDTM is the clinical trial data standard used for regulatory submissions. Annual reports summarizing trial progress are submitted annually to the US FDA.
Clinical data capture involves collecting clinically significant data from subjects in clinical trials. This can be done via paper-based methods like case report forms or via electronic data capture (EDC) methods. EDC involves collecting data electronically and has advantages over paper methods like real-time reporting and faster data processing. Common EDC tools include using the internet, interactive voice response, personal digital assistants, and electronic case report forms (eCRFs). eCRFs allow direct entry of data into an electronic form without paper sources, eliminating errors from transcription.
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.
During this presentation, Ron Kershner, Ph.D. discussed the responsibilities of DMCs from the perspective of protecting patient safety and providing critical, independent oversight to key study objectives. Drawing on past clinical trials to illustrate key points, Ron addressed DMC operational considerations, such as meeting frequency and content, control of information, data cleaning issues and scope/format of data tabulations.
Lifesciences IT - 2011 YearbookSummaryGBI Research's research, 'Lifesciences IT - 2011 Yearbook" provides key data, information and analysis on Lifesciences \IT that is being implemented by pharmaceutical companies. GBI Research expects that information technology (IT) in the lifesciences industry will become a trendsetter, helping pharmaceutical companies mitigate current and evolving industry challenges. IT solutions utilized in the value chain of pharmaceutical companies help them to operate effectively and efficiently. GBI expects an increase in the adoption of IT by pharmaceutical companies looking to remain competitive in the market place. The Lifesciences industry is pressurized by various challenges such as declining Return on Investment (ROI) on R&D investments, entry of generics and layoffs. These factors are responsible for the lifesciences companies to invest in information technology solutions. Pharmaceutical companies have found that experimental techniques are costly, time-consuming, and involve the use of large numbers of animals for testing and are adapting to computerized combinatorial chemistry applications. Pharmaceutical Companies are increasingly adopting e-clinical trial solutions in the drug development phase. Cutting down clinical trial cost is the driving motivation for the adoption of e-clinical trial solutions. Services offered by IT companies in clinical data management are costly but have been proved to save cost for the companies in the long run. CTMS and EDC will attract the highest investments in the future followed by data mining, electronic submission tools and RFID. Outsourcing helps a pharmaceutical company to reduce costs by 30-35% and this is one of the main reasons why pharmaceutical companies outsource non-core R&D operational work to IT companies. When selecting a country to outsource clinical data management work, building the required competencies to tackle client requirements has gained a higher importance than the cost advantage it provides. The predictive analytics helps a company view beyond the sales volume in to real time prescribing patterns, as a behavior of continuum. This also helps the company to follow the evolving niche buster model. Many pharmaceutical companies have increased satisfaction levels from their customers in 2008. In 2004, 50% of the physicians were satisfied on the current number of calls. However, satisfaction levels have increased in 2008 with more than 57% of the physicians in the US satisfied with the current number of calls. The increase in satisfaction levels was directly proportional to the decrease of sales force in the US. It is built using data and information sourced from proprietary databases, primary and secondary research and in house analysis by GBI Research's team of industry experts.ScopeThe scope of this report includes - - Analysis of the leading segments in the Lifesciences IT market - Key drivers and barriers that have a significant impact on the Lifesciences IT market. - Competitive benchmarking of leading companies in the market. - Key M&A activities and strategic partnership deals that have taken place in 2009.- Inputs for customized IT solution based on business situation.Reasons to buyThe report will enhance your decision making capability. It will provide you with - - Align your product portfolio to the markets with high growth potential.- Develop market-entry and market expansion strategies by identifying the leading segments poised for strong growth.- Device better strategies through the understanding of key drivers and barriers in the market.- Develop key strategic initiatives by understanding the key focus of leading companies.- Accelerate and strengthen your market position by identifying key companies for mergers, acquisitions and strategic partnerships.
This document discusses clinical data management (CDM) systems and processes. It defines key terms like source data, source documents, and raw data. It then describes the essential steps in CDM including initial planning, data collection, review and verification, coding, query resolution, data entry and validation, output and archiving. Finally, it outlines requirements for a good CDM system including system validation, security, change control, and archiving. The goal of CDM is to generate an accurate, high-quality clinical trial database while ensuring compliance with regulations.
This document provides guidance on clinical data management practices for analyzing research data. It discusses key aspects of clinical data management including planning, data collection, review, entry, coding, querying, output, and archiving. Ensuring accurate data capture and high quality databases is the objective. Adherence to good clinical data management practices and regulatory guidelines is emphasized. Effective planning, standardized processes, trained personnel, quality control measures, and system validation are seen as important for generating reliable data for analysis and reporting.
The document outlines the process for setting up clinical data management and pharmacovigilance processes. It discusses developing the protocol and case report forms, designing the database, installing software like Oracle Inform and Argus, and preparing documents like the data management plan. It also describes the data entry, validation, query resolution, medical coding, biostatistics, and database locking and freezing aspects of the clinical data management and pharmacovigilance setup process.
Clinical research and clinical data management - Ikya Globalikya global
Data management functions in clinical trials—extensive data cleaning, full query management, protocol deviation management, batch processing, as examples—have traditionally been served by stand-alone clinical data management systems (CDMS), whose input is from paper forms or from separate electronic data capture systems. Distinct electronic data capture and data management systems require data integration, with resulting timing and reconciliation issues.
1. A clinical data management system (CDMS) is used to manage data from clinical trials by storing data entered in case report forms (CRFs) by investigators.
2. Data management involves planning, collection, entry, validation, manipulation, backup and documentation of data to create a high quality database. Commonly used CDMS tools include Oracle Clinical, ClinTrial, Macro and eClinical Suite.
3. Open source CDMS tools include OpenClinica, openCDMS, TrialDB and PhOSCo which are free. All CDMS tools ensure an audit trail and management of discrepancies according to roles and user access levels.
CRO
This document provides an overview of a CRO's full-service clinical data management capabilities. It has over 25 years of experience and a team of 70 staff across Europe and India. The CRO offers a full range of CDM services including project management, database design, data entry, validation, and IT infrastructure validated to industry standards. It has experience across therapeutic areas and geographies, using mature CDISC-compliant platforms. The CRO maintains data security, backup/recovery policies, and has qualified experienced staff to deliver high-quality CDM services.
YEARS
Track Record
Clinical data management (CDM) ensures the collection, integration, and availability of high-quality data from clinical trials. It supports clinical research and analysis across different study types. CDM tools like CDMS help manage large amounts of multicenter trial data. Regulations like 21 CFR Part 11 require electronic records and validated systems to ensure accurate, reliable data. Guidelines from SCDM and CDISC provide standards for good CDM practices and data collection. CDM processes clinical research data from source documents through database entry, quality checking, analysis, and archiving to support regulatory approval and conclusions about clinical results.
Clinical data management is the process of collecting, validating, and cleaning data from clinical trials. It aims to ensure data quality and integrity. Key aspects of clinical data management include electronic data capture, establishing data standards, using clinical data management systems, and performing activities like data collection, validation, and discrepancy management. It follows guidelines from organizations like SCDM and regulations like 21 CFR Part 11.
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.
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
Have full fleged clinical trial data management systems which bring them a good amount of business and revenue.
CDM is a fundamental process which controls data accuracy of each trial besides helping the timelessness to be achieved.
It helps in linking clinical research co-ordinator = who monitor all the sites & collects the data.
it Links with biostatisticians = who analyze, interpret and report data in clinically meaningful way.
Electronic Data Capture & Remote Data CaptureCRB Tech
CRB Tech is one of the best leading Software Development Company in Pune. We are offering Software Development Services as well as IT Training including Java, Dot Net, SEO and Clinical Research training in pune.
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.
Clinical data management (CDM) involves collecting, validating, and cleaning patient data from clinical trials to ensure it is complete, consistent, and compliant. A CDM team typically includes clinical data managers, programmers, and data entry associates. They are involved in all stages from study setup to completion. Key CDM activities include designing case report forms, programming data validation checks, overseeing data entry into clinical data management systems, manually and electronically cleaning the data, reconciling safety data with external sources, and locking the database once the trial is complete and the data is ready for analysis. The goal is to generate high-quality clinical trial data that can be analyzed to advance drug development timelines.
Introduction to Oracle Clinical Overview in Clinical Data Management in Clinical Trials of Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
Clinical data management involves processing clinical trial data through activities like data entry, validation, query resolution and medical coding. It aims to ensure the integrity and quality of clinical trial data, which regulatory agencies rely on for drug approval. The document provides an overview of the clinical data management process and roles involved at each stage, from study set-up to closeout.
Study setup_Clinical Data Management_Katalyst HLSKatalyst HLS
Introduction to Study Setup in Clinical Data Management in Clinical Trials of Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
The 3 main types of reports are:
1) Summary reports that summarize the data
2) Listings reports that list the entire data as is
3) Figures and graphs that provide graphical representations of the data
A programming plan outlines the algorithms, data presentations, and programming standards to generate derived datasets. Test plans are created for quality control to validate the derived datasets and reports meet specifications. SDTM is the clinical trial data standard used for regulatory submissions. Annual reports summarizing trial progress are submitted annually to the US FDA.
Clinical data capture involves collecting clinically significant data from subjects in clinical trials. This can be done via paper-based methods like case report forms or via electronic data capture (EDC) methods. EDC involves collecting data electronically and has advantages over paper methods like real-time reporting and faster data processing. Common EDC tools include using the internet, interactive voice response, personal digital assistants, and electronic case report forms (eCRFs). eCRFs allow direct entry of data into an electronic form without paper sources, eliminating errors from transcription.
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.
During this presentation, Ron Kershner, Ph.D. discussed the responsibilities of DMCs from the perspective of protecting patient safety and providing critical, independent oversight to key study objectives. Drawing on past clinical trials to illustrate key points, Ron addressed DMC operational considerations, such as meeting frequency and content, control of information, data cleaning issues and scope/format of data tabulations.
Lifesciences IT - 2011 YearbookSummaryGBI Research's research, 'Lifesciences IT - 2011 Yearbook" provides key data, information and analysis on Lifesciences \IT that is being implemented by pharmaceutical companies. GBI Research expects that information technology (IT) in the lifesciences industry will become a trendsetter, helping pharmaceutical companies mitigate current and evolving industry challenges. IT solutions utilized in the value chain of pharmaceutical companies help them to operate effectively and efficiently. GBI expects an increase in the adoption of IT by pharmaceutical companies looking to remain competitive in the market place. The Lifesciences industry is pressurized by various challenges such as declining Return on Investment (ROI) on R&D investments, entry of generics and layoffs. These factors are responsible for the lifesciences companies to invest in information technology solutions. Pharmaceutical companies have found that experimental techniques are costly, time-consuming, and involve the use of large numbers of animals for testing and are adapting to computerized combinatorial chemistry applications. Pharmaceutical Companies are increasingly adopting e-clinical trial solutions in the drug development phase. Cutting down clinical trial cost is the driving motivation for the adoption of e-clinical trial solutions. Services offered by IT companies in clinical data management are costly but have been proved to save cost for the companies in the long run. CTMS and EDC will attract the highest investments in the future followed by data mining, electronic submission tools and RFID. Outsourcing helps a pharmaceutical company to reduce costs by 30-35% and this is one of the main reasons why pharmaceutical companies outsource non-core R&D operational work to IT companies. When selecting a country to outsource clinical data management work, building the required competencies to tackle client requirements has gained a higher importance than the cost advantage it provides. The predictive analytics helps a company view beyond the sales volume in to real time prescribing patterns, as a behavior of continuum. This also helps the company to follow the evolving niche buster model. Many pharmaceutical companies have increased satisfaction levels from their customers in 2008. In 2004, 50% of the physicians were satisfied on the current number of calls. However, satisfaction levels have increased in 2008 with more than 57% of the physicians in the US satisfied with the current number of calls. The increase in satisfaction levels was directly proportional to the decrease of sales force in the US. It is built using data and information sourced from proprietary databases, primary and secondary research and in house analysis by GBI Research's team of industry experts.ScopeThe scope of this report includes - - Analysis of the leading segments in the Lifesciences IT market - Key drivers and barriers that have a significant impact on the Lifesciences IT market. - Competitive benchmarking of leading companies in the market. - Key M&A activities and strategic partnership deals that have taken place in 2009.- Inputs for customized IT solution based on business situation.Reasons to buyThe report will enhance your decision making capability. It will provide you with - - Align your product portfolio to the markets with high growth potential.- Develop market-entry and market expansion strategies by identifying the leading segments poised for strong growth.- Device better strategies through the understanding of key drivers and barriers in the market.- Develop key strategic initiatives by understanding the key focus of leading companies.- Accelerate and strengthen your market position by identifying key companies for mergers, acquisitions and strategic partnerships.
Healthcare institutions are aggressively moving towards meeting compliance with MU1 and MU2 with the implementation of full-featured Electronic Health Records. Concomitantly, there will be a massive increase in the amount of clinical data captured electronically. Business intelligence (BI) which traditionally has focused on financial data can be leveraged to use clinical data to support providers in delivering high quality, efficient care. In addition, BI coupled with population health analytics can help meet many Accountable Care Organization needs. This presentation will discuss the Denver Health journey in using BI in a variety of was to facilitate the attainment of high quality care.
Selecting Core Clinical It Solutions For Life Sciences Organizations – Key S...Vinoth Kumar T
This document summarizes a presentation on selecting core clinical IT solutions for life sciences organizations. It discusses the challenges life sciences companies face with drug development timelines and costs. Effective clinical data management can help address these challenges by streamlining processes, improving data quality and security, and enabling faster data review and regulatory submissions. When selecting clinical IT solutions, companies should evaluate vendors, ensure regulatory compliance, and consider costs, integration, usability, and ongoing support. A successful implementation requires understanding existing workflows, conducting pilots, addressing security risks, and having open communication channels to resolve problems.
Insights into the Canadian eHealth Landscape - MaRS Future of MedicineMaRS Discovery District
In recognition of the need to develop a national digital health strategy and to co-ordinate activity across the country, the Conference of Deputy Ministers established Canada Health Infoway in 2001.
This lecture describes Infoway’s role and the progress that it and its jurisdictional partners have made over the last decade. It outlines the challenges to achieving our collective goal of using technology to improve the health of Canadians and describes key enablers that must be in place for us to be successful. It also contains the results of recent public opinion research conducted with Canadians and healthcare providers and outlines the priorities for moving forward and the opportunities for action.
The specialized industry of collecting electronic patient-reported outcomes is increasing linearly, in part because global government regulators want to hear directly from the patient, and because the acceleration and availability of electronic collection (vs. paper collection) improves data quality and efficiencies for data analysis and trial management. This document will review the ePRO market, and outline the five ePRO methods what successfully support the collection of patient-reported data
Himss singapore 2012 clinician it leadership 2012[1]HealthXn
The document discusses how business intelligence and big data analytics can help clinicians and hospitals. It describes how new tools like business intelligence have emerged to organize and interpret vast amounts of healthcare information to benefit public health, research, patient care, and hospital operations. Healthcare organizations are now dealing with tremendous amounts of digital data stored in large repositories. Analytics can be used to detect patterns in this large, complex data that are too subtle for humans to observe directly. This can help improve areas like decision making, research, and the development of new treatments and services.
In this presentation from the Institute of Validation Technology's Life Sciences Aseptic Processing, Kim Van Antwerpen discusses collecting environmental data, methods for trending, and interpreting and sharing environmental monitoring data.
Pistoia presentation bio it-worldexpo 21april2010Nick Lynch
The document summarizes the origins and operations of the Pistoia Alliance, a non-profit organization formed to facilitate pre-competitive collaboration in the life sciences industry. The Pistoia Alliance was formed in Pistoia, Italy by GSK, AZ, Pfizer and Novartis to address common challenges with data interchange. Its mission is to standardize data exchange to reduce costs. Current projects include developing standards for semantic enrichment of literature, sequence data services, and electronic lab notebook queries. The organization has over 30 members and operates working groups to develop open standards through a governance process.
Sandor Szalma (Janssen) gives an overview of this potential Pistoia Alliance working group during the "Dragons' Den" session of the Pistoia Alliance Conference in Boston, MA, on April 24, 2012.
Sharing a New Ideal: How Tomorrow’s Understaffed, Multi-Site Lab Organization...mhartman1309
This presentation was presented by Chris Christopher at the Lab Quality Confab Conference on Nov 2, 2010. It shows how medical laboratories are using automation, technology and lean sigma improvement methodologies to meet organizational needs.
Workflow Process Management and Enterprise Application Integration in HealthcareAmit Sheth
The document discusses requirements, applications, technology, and research related to enterprise application integration in healthcare. It provides examples of healthcare applications that have used the METEOR EAppS (Enterprise Application Suite of Services and Tools), including neonatal clinical pathways, genome sequencing, eligibility-referral, and immunization tracking. It also discusses requirements for mission-critical healthcare applications and the state of technology, products, and research in areas like workflow management and enterprise application integration.
This document discusses EDGAR Online's role in promoting transparency through structured data. It notes that EDGAR Online has the largest and fastest XBRL dataset with over 11 years of US public company filings. It also has the most comprehensive set of XBRL products and services, including tools for companies to create and file XBRL documents and for regulators and analysts to analyze XBRL data. The document argues that data standards like XBRL are important to improve the outdated financial information supply chain and enable better data analysis.
Presentation at NeHC: Overview of ONC's health information exchange standards-selection activities. Focuses on HITSC, the S&I Framework, and the S&I Query Health Initiative.
Novadaq Technologies develops real-time fluorescence imaging technologies used in surgical procedures. Their SPY Imaging system provides clinically relevant images during complex surgeries to help surgeons see blood flow and vessel networks in real-time, reducing complication and re-surgery rates. Studies show their technology can save hospitals $2,000-$4,000 per surgery by virtually eliminating complications. With relationships with industry leaders and steady financial progress, Novadaq's imaging platform represents an emerging standard of care in surgeries where blood flow visualization is important.
In a unified eClinical infrastructure, formerly disparate clinical study systems are merged.
Users no longer work in “CTMS” or “eTMF”, but in a harmonized clinical infrastructure where a single source of truth is a given, and changes and additions automatically impact the appropriate data, documents and processes.
This presentation will show you what clinical unification is, its benefits and how it can be achieved.
The document discusses strategies for developing biosimilars in a cost-effective manner. It notes that while the biopharmaceutical opportunity is large, biosimilar development faces significant challenges related to regulation, manufacturing complexity, and marketing limitations. Companies therefore pursue various strategies like building internal capabilities, outsourcing non-core functions, partnering, and acquisitions. The document uses Reliance Life Sciences as a case study, outlining its multi-pronged approach to developing an integrated biosimilars pipeline and capabilities through both internal investment and external partnerships and deals.
Webcast: CIO Insights: How to Optimize User Experience Across 60 Hospitals Compuware APM
** If you would like to download a copy of the slides- please email jessica.murphy@compuware.com and she will send the slideset to you via email.**
For health services provider Christus Health, poorly performing applications are never an option. Just as medical equipment cannot fail, the applications supporting Christus Health must operate flawlessly. In order to avoid lost revenue, decreased clinical productivity and increased risk to patients, Christus employs an end-user perspective to application performance management.
Join Christus Health CIO George Conklin in this Compuware webcast to learn:
• What impacts healthcare app performance has on customer experience and business goals
• How Christus IT and the business teams optimize customer experience
• Real-world best practices for improving user experience without slowing down your healthcare processes and procedures
What You Will Learn:
George Conklin, Senior VP and CIO of Christus will share real-world experiences and Christus Heath’s best practice approach for ensuring users in their healthcare system have the best application performance possible.
Similar to Streamlining Data Management Start-up (20)
Feasibility Solutions to Clinical Trial Nightmaresjbarag
Slow patient recruitment and poor retention cause recurrent nightmares and perpetual problems often resulting in missing recruitment milestones. The cost of these delays represents hundreds of thousands of dollars for drug and device developers. By recognizing this issue, early detailed feasibility can provide planning and contingency solutions that are focused on reducing the impact of delayed recruitment. Furthermore understanding what motivates investigators and patients to actively participate in clinical studies and how patient recruitment strategies and materials can support all stakeholders to complete studies on time are critical aspects of clinical study delivery planning.
During this presentation, an experienced Premier Research feasibility and patient recruitment specialist, reviewed feasibility approaches to address protocol evaluation as well as addressed influences on country selection, site distribution and patient recruitment strategies to provide for more effective clinical trial planning and conduct.
For more information, go to http://www.premier-research.com.
Successful Pediatric Studies: Key Study Design and Site Selection Considerationsjbarag
The industry recognizes the importance of ensuring the safety and well‐being of children involved in research studies. Medical and regulatory bodies have worked to provide a framework to support appropriately designed studies through regulations and guidance documents in this vulnerable population. However, it is crucial to understand the nuances associated with pediatric trials, for the site, patient and family, in order to manage them to successful completion.
During the 2012 ACRP Annual Meeting, Dr. Charlene Sanders and Angi Robinson from Premier Research reviewed topics including the evaluation of study design considerations such as duration of treatment, required assessments, use of placebo, and inclusion of specific age groups; selection of appropriate sites for pediatric trials and the unique needs of these sites; identification of pediatric recruitment/retention hurdles and site specific strategies to overcome these as well as a reflection on ethical concerns related to pediatric research.
For more information, go to http://www.premier-research.com/pediatrics.
Over the past decade, CDISC data standards have become the FDA preferred method for the data submission. In fact, the FDA is considering a proposed rule change that would mandate the submission of data in CDISC Study Data Tabulation Model (SDTM) and Analysis Data Model (ADaM) formats for all new marketing applications. However, the implementation of this standard has proved to be intimidating to many with only a very small percentage of drug companies actually developing and submitting data in this format.
During the webinar, Thomas Kalfas, an experienced data management professional and CDISC subject matter expert, shared his knowledge and strategies for implementing CDSIC. Topics included a brief review of CDISC, implementation challenges, and insight into the best timing for implementation.
Creating Effective Pediatric Assent Forms: Overcoming Common Obstaclesjbarag
This document discusses creating effective pediatric assent forms by overcoming common obstacles. It identifies five main obstacles: 1) treating assent as an afterthought, 2) lack of direction from sponsors/IRBs, 3) failure to account for developmental ages and reading levels, 4) difficulty creating readable forms, and 5) not planning the assent process logistics. It provides tools to write forms at appropriate reading levels, ensure all elements of assent are addressed, and plan who will obtain assent and where. The goal is to engage children in a developmentally-appropriate way and respect their participation in research decisions.
This presentation, led by Ryan Michaud, explored how to best employ IV/IWRS platforms for collecting and managing Patient Reported Outcomes (PRO) data, clinical supply management including drug accountability, visit tracking and randomization.
During this presentation, Dr. Charlene Sanders and Angi Robinson reviewed topics including the evaluation of study design considerations such as duration of treatment, required assessments, use of placebo, and inclusion of specific age groups; selection of appropriate sites for pediatric trials and the unique needs of these sites; identification of pediatric recruitment/retention hurdles and site specific strategies to overcome these as well as a reflection on ethical concerns related to pediatric research.
Guidelines for Effective and Appropriate Pediatric Assent and Parental Permis...jbarag
During this presentation, Angi Robinson and Elizabeth Jay reviewed the regulatory requirements for parental permission and pediatric assent; provided practical tips for compliant and age-appropriate form development including which elements to incorporate, the number of required signatures, and how to check for reading comprehension level; and offered recommendations for documentation of the consenting/assenting process.
Planning your Paediatric Investigation Plan (PIP) Submission in Europejbarag
During this presentation, Dr. Susan Bhatti, an experienced regulatory affairs professional, shared best practices and experiences learned from submitting PIPs. This included a brief review of the pediatric regulation requirements, insight for interacting with PDCO, and an overview of the PIP submission including procedures, timelines, structure and compliance.
Developing a Feasible Pediatric Plan for PREA/PMDSIA Compliancejbarag
This presentation will address issues surrounding the development of a pediatric plan for PREA/PMDSIA compliance including: when to develop a pediatric plan, what age groups should be included, is a pediatric formulation necessary, timing of the pediatric studies, what information should be submitted to FDA, and when a waiver or deferral is appropriate.
• Planning your PIP submission
• Which in-house departments should be involved?
• Interaction with CRO/ writer
• Interaction with PDCO
• Key points for successful PIP outsourcing
Centralized Resourcing Model for Clinical Trialsjbarag
A centralized resourcing model within clinical research organizations can provide efficiencies in resource management. It involves having a central point of contact to manage the resource assignment, deployment, and utilization across programs. Key ingredients for success include regular communication, standardized processes for resource requests and tracking, and reliable tools for resource planning and metrics. This model allows resources to be strategically allocated, utilization to be maximized through short-term assignments, and proactive planning to improve cost and time efficiencies.
Medical Writing Essential: Reviewing Statisitical Analysis Plansjbarag
Regulatory medical writers are tasked with generating high-quality clinical study reports (CSRs) promptly. To this end, statistical analysis plan (SAP) reviews are essential as they allow medical writers to verify that the SAP contains the information required for the CSR per regulatory guidance. This session will explain how to conduct SAP reviews and how to assess whether data presentations in addition to those proposed are needed for the CSR.
Ind Applications: A Case Study of Document Development from the Medical Writi...jbarag
This session is a presentation of a case study on management of a complex document development program for Investigational New Drug (IND) submissions. The scope of writing 19 documents for 3 IND submissions in 6 months dictated expert project management by a medical writing (MW) team. Through meticulous organization, strategic planning and communication, MW effectively managed the process and delivered the required documents well before the IND submission deadlines.
Meeting Enrollment Goals in a Competitive Environmentjbarag
Challenges in patient recruitment continue to be the number one cause in clinical trial delays. Through involvement in this workshop, participants will become familiar with how to develop, implement, manage and track site enrollment plans. This will include understanding the core elements that constitute an enrollment plan as well as understanding how the development of strategic tools and tactics can aid sites in the successful implementation, monitoring and tracking of results. Both project management and site perspectives on enrollment and recruitment plans will be discussed.
This document discusses managing high performance project teams. It emphasizes that conducting clinical research requires contributions from all team members. It outlines some fundamentals and challenges of project management including forming a cohesive team, maintaining motivation, and communication. It provides basics for managing teams such as establishing roles and responsibilities, communication plans, and holding regular meetings. It also discusses important leadership skills like being a good listener, connecting with others, and insulating the team from issues. Proactive communication techniques are also covered like being mindful of tone, email management, and making requests.
Cell Therapy Expansion and Challenges in Autoimmune DiseaseHealth Advances
There is increasing confidence that cell therapies will soon play a role in the treatment of autoimmune disorders, but the extent of this impact remains to be seen. Early readouts on autologous CAR-Ts in lupus are encouraging, but manufacturing and cost limitations are likely to restrict access to highly refractory patients. Allogeneic CAR-Ts have the potential to broaden access to earlier lines of treatment due to their inherent cost benefits, however they will need to demonstrate comparable or improved efficacy to established modalities.
In addition to infrastructure and capacity constraints, CAR-Ts face a very different risk-benefit dynamic in autoimmune compared to oncology, highlighting the need for tolerable therapies with low adverse event risk. CAR-NK and Treg-based therapies are also being developed in certain autoimmune disorders and may demonstrate favorable safety profiles. Several novel non-cell therapies such as bispecific antibodies, nanobodies, and RNAi drugs, may also offer future alternative competitive solutions with variable value propositions.
Widespread adoption of cell therapies will not only require strong efficacy and safety data, but also adapted pricing and access strategies. At oncology-based price points, CAR-Ts are unlikely to achieve broad market access in autoimmune disorders, with eligible patient populations that are potentially orders of magnitude greater than the number of currently addressable cancer patients. Developers have made strides towards reducing cell therapy COGS while improving manufacturing efficiency, but payors will inevitably restrict access until more sustainable pricing is achieved.
Despite these headwinds, industry leaders and investors remain confident that cell therapies are poised to address significant unmet need in patients suffering from autoimmune disorders. However, the extent of this impact on the treatment landscape remains to be seen, as the industry rapidly approaches an inflection point.
low birth weight presentation. Low birth weight (LBW) infant is defined as the one whose birth weight is less than 2500g irrespective of their gestational age. Premature birth and low birth weight(LBW) is still a serious problem in newborn. Causing high morbidity and mortality rate worldwide. The nursing care provide to low birth weight babies is crucial in promoting their overall health and development. Through careful assessment, diagnosis,, planning, and evaluation plays a vital role in ensuring these vulnerable infants receive the specialize care they need. In India every third of the infant weight less than 2500g.
Birth period, socioeconomical status, nutritional and intrauterine environment are the factors influencing low birth weight
These lecture slides, by Dr Sidra Arshad, offer a simplified look into the mechanisms involved in the regulation of respiration:
Learning objectives:
1. Describe the organisation of respiratory center
2. Describe the nervous control of inspiration and respiratory rhythm
3. Describe the functions of the dorsal and respiratory groups of neurons
4. Describe the influences of the Pneumotaxic and Apneustic centers
5. Explain the role of Hering-Breur inflation reflex in regulation of inspiration
6. Explain the role of central chemoreceptors in regulation of respiration
7. Explain the role of peripheral chemoreceptors in regulation of respiration
8. Explain the regulation of respiration during exercise
9. Integrate the respiratory regulatory mechanisms
10. Describe the Cheyne-Stokes breathing
Study Resources:
1. Chapter 42, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 36, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 13, Human Physiology by Lauralee Sherwood, 9th edition
“Psychiatry and the Humanities”: An Innovative Course at the University of Mo...Université de Montréal
“Psychiatry and the Humanities”: An Innovative Course at the University of Montreal Expanding the medical model to embrace the humanities. Link: https://www.psychiatrictimes.com/view/-psychiatry-and-the-humanities-an-innovative-course-at-the-university-of-montreal
The skin is the largest organ and its health plays a vital role among the other sense organs. The skin concerns like acne breakout, psoriasis, or anything similar along the lines, finding a qualified and experienced dermatologist becomes paramount.
Lecture 6 -- Memory 2015.pptlearning occurs when a stimulus (unconditioned st...AyushGadhvi1
learning occurs when a stimulus (unconditioned stimulus) eliciting a response (unconditioned response) • is paired with another stimulus (conditioned stimulus)
STUDIES IN SUPPORT OF SPECIAL POPULATIONS: GERIATRICS E7shruti jagirdar
Unit 4: MRA 103T Regulatory affairs
This guideline is directed principally toward new Molecular Entities that are
likely to have significant use in the elderly, either because the disease intended
to be treated is characteristically a disease of aging ( e.g., Alzheimer's disease) or
because the population to be treated is known to include substantial numbers of
geriatric patients (e.g., hypertension).
Histololgy of Female Reproductive System.pptxAyeshaZaid1
Dive into an in-depth exploration of the histological structure of female reproductive system with this comprehensive lecture. Presented by Dr. Ayesha Irfan, Assistant Professor of Anatomy, this presentation covers the Gross anatomy and functional histology of the female reproductive organs. Ideal for students, educators, and anyone interested in medical science, this lecture provides clear explanations, detailed diagrams, and valuable insights into female reproductive system. Enhance your knowledge and understanding of this essential aspect of human biology.
Test bank for karp s cell and molecular biology 9th edition by gerald karp.pdfrightmanforbloodline
Test bank for karp s cell and molecular biology 9th edition by gerald karp.pdf
Test bank for karp s cell and molecular biology 9th edition by gerald karp.pdf
Test bank for karp s cell and molecular biology 9th edition by gerald karp.pdf
5-hydroxytryptamine or 5-HT or Serotonin is a neurotransmitter that serves a range of roles in the human body. It is sometimes referred to as the happy chemical since it promotes overall well-being and happiness.
It is mostly found in the brain, intestines, and blood platelets.
5-HT is utilised to transport messages between nerve cells, is known to be involved in smooth muscle contraction, and adds to overall well-being and pleasure, among other benefits. 5-HT regulates the body's sleep-wake cycles and internal clock by acting as a precursor to melatonin.
It is hypothesised to regulate hunger, emotions, motor, cognitive, and autonomic processes.
Travel Clinic Cardiff: Health Advice for International TravelersNX Healthcare
Travel Clinic Cardiff offers comprehensive travel health services, including vaccinations, travel advice, and preventive care for international travelers. Our expert team ensures you are well-prepared and protected for your journey, providing personalized consultations tailored to your destination. Conveniently located in Cardiff, we help you travel with confidence and peace of mind. Visit us: www.nxhealthcare.co.uk
Osvaldo Bernardo Muchanga-GASTROINTESTINAL INFECTIONS AND GASTRITIS-2024.pdfOsvaldo Bernardo Muchanga
GASTROINTESTINAL INFECTIONS AND GASTRITIS
Osvaldo Bernardo Muchanga
Gastrointestinal Infections
GASTROINTESTINAL INFECTIONS result from the ingestion of pathogens that cause infections at the level of this tract, generally being transmitted by food, water and hands contaminated by microorganisms such as E. coli, Salmonella, Shigella, Vibrio cholerae, Campylobacter, Staphylococcus, Rotavirus among others that are generally contained in feces, thus configuring a FECAL-ORAL type of transmission.
Among the factors that lead to the occurrence of gastrointestinal infections are the hygienic and sanitary deficiencies that characterize our markets and other places where raw or cooked food is sold, poor environmental sanitation in communities, deficiencies in water treatment (or in the process of its plumbing), risky hygienic-sanitary habits (not washing hands after major and/or minor needs), among others.
These are generally consequences (signs and symptoms) resulting from gastrointestinal infections: diarrhea, vomiting, fever and malaise, among others.
The treatment consists of replacing lost liquids and electrolytes (drinking drinking water and other recommended liquids, including consumption of juicy fruits such as papayas, apples, pears, among others that contain water in their composition).
To prevent this, it is necessary to promote health education, improve the hygienic-sanitary conditions of markets and communities in general as a way of promoting, preserving and prolonging PUBLIC HEALTH.
Gastritis and Gastric Health
Gastric Health is one of the most relevant concerns in human health, with gastrointestinal infections being among the main illnesses that affect humans.
Among gastric problems, we have GASTRITIS AND GASTRIC ULCERS as the main public health problems. Gastritis and gastric ulcers normally result from inflammation and corrosion of the walls of the stomach (gastric mucosa) and are generally associated (caused) by the bacterium Helicobacter pylor, which, according to the literature, this bacterium settles on these walls (of the stomach) and starts to release urease that ends up altering the normal pH of the stomach (acid), which leads to inflammation and corrosion of the mucous membranes and consequent gastritis or ulcers, respectively.
In addition to bacterial infections, gastritis and gastric ulcers are associated with several factors, with emphasis on prolonged fasting, chemical substances including drugs, alcohol, foods with strong seasonings including chilli, which ends up causing inflammation of the stomach walls and/or corrosion. of the same, resulting in the appearance of wounds and consequent gastritis or ulcers, respectively.
Among patients with gastritis and/or ulcers, one of the dilemmas is associated with the foods to consume in order to minimize the sensation of pain and discomfort.
Osvaldo Bernardo Muchanga-GASTROINTESTINAL INFECTIONS AND GASTRITIS-2024.pdf
Streamlining Data Management Start-up
1. 2 0 1 1 FA L L B I O M E T R I C S W E B I N A R S E R I E S
Streamlining Data Management Start-up
Nov. 15, 2011 Presented by Cheryl Silva
2. Cheryl Silva
Associate Director, Technical Operations
Expertise in:
– CRF design
– Database development
– Application support
– Electronic data handling
– Report programming
Programming/software development background
Bachelor’s degree in Computer and Information
Science from the University of Massachusetts
2011 FALL BIOMETRICS WEBINAR SERIES
3. Today’s Topics
3
▪ Need for Streamlined Approach
▪ Areas for Efficiencies
– Standards
– Parallel approach
– Identifying key reviewers
– One size doesn’t fit all
▪ Summary
2011 FALL BIOMETRICS WEBINAR SERIES
4. Need for Streamlined Approach
In 2003, health economists in the US estimated the average cost
of bringing a drug to market at US$802 million. Today, those
Drug Approvals – From
costs are forecasted in the range of $1.3 to - $1.7 billion. Clinical
trials cost is one of the biggest expense categories for
Invention to Market…
biopharmaceutical companies.
The Industry Challenge:Year Trip
A 12-
• More than 80% of clinical trials experience delay
from one to six months costing pharmaceutical
companies upwards of $35,000 per day, per trial.
• Only 10% of trials are completed on time.
2011 FALL BIOMETRICS WEBINAR SERIES
5. Need for Streamlined Approach
In 2003, health economists in the US estimated the average cost
of bringing a drug to market at US$802 million. Today, those
costs are forecasted in the range of $1.3 to - $1.7 billion. Clinical
trials cost is one of the biggest expense categories for
biopharmaceutical companies.
The Industry Challenge:
• More than 80% of clinical trials experience delay
from one to six months costing pharmaceutical
companies upwards of $35,000 per day, per trial.
• Only 10% of trials are completed on time.
2011 FALL BIOMETRICS WEBINAR SERIES
7. 2005 Survey
Factors that Could Best Prevent Future Delays
7
% “Best Prevent Future Delays”
50% 45%
42%
40% 37% 35% 34%
30%
20%
10%
0%
EDC Fewer More Money Standardized Sites Involved
Technologies Intermediaries for Patient CRFs Earlier in the
Recruitment Protocol
Process
Source: CenterWatch Survey of Investigative Sites in the U.S., 2005 (n=612)
Multiple responses offered
2011 FALL BIOMETRICS WEBINAR SERIES
8. Electronic Data Capture
8
Medidata Rave…
Improving efficiency
of study build and
life cycle
management
Electronic Data
Capture (EDC)…
expedite
time-to-market
2011 FALL BIOMETRICS WEBINAR SERIES
9. 2009 Survey
Factors that Could Best Prevent Future Delays
9
% “Best Prevent Future Delays”
50%
40%
31% 30% 29%
30% 27% 26%
20%
10%
0%
Fewer Streamlined EDC More Money Standardized
Intermediaries Contracting Technologies for Patient CRFs
and Budgeting Recruitment
Source: CenterWatch Survey of Investigative Sites in the U.S., 2009 (n=950)
Multiple responses offered
2011 FALL BIOMETRICS WEBINAR SERIES
10. Streamlining Study Start-up
10
Without a streamlined study start-up process, the
following efficiencies gained through the use of EDC are
diminished:
Real time data entry/data availability
Real time data cleaning
2011 FALL BIOMETRICS WEBINAR SERIES
11. Efficiencies
Standards
Parallel Approach
Identifying Key Reviewers
One size does not fit all
– Premier Express
2011 FALL BIOMETRICS WEBINAR SERIES
12. Standards
12
▪ Standard CRFs
▪ Global Library objects
▪ Standard Data Validation Plan (DVP) pre-populated
with Standard edit checks
▪ Different companies maintain different Standards
– Premier Research follows
Clinical Data Acquisition
Standards Harmonization
(CDASH) industry standards
▪ Important: Agreeing to Standards up front saves time
2011 FALL BIOMETRICS WEBINAR SERIES
13. Parallel Approach
13
Identify tasks that can be performed in parallel
Edit Check Edit Check
Start DVP
Programming Testing
Identify CRFs
Live Database
from Standards
Start Database Database
Study Training
Build Testing
Data Manager
Data Programmer
2011 FALL BIOMETRICS WEBINAR SERIES
14. Key Pieces to Parallel Approach
14
Resource Managing
Standard
Allocation and Timeline
Timelines
Management Shifts
2011 FALL BIOMETRICS WEBINAR SERIES
15. Parallel Approach
15
Perform Parallel Reviews
2011 FALL BIOMETRICS WEBINAR SERIES
16. Parallel Approach
16
Perform Parallel Reviews
2011 FALL BIOMETRICS WEBINAR SERIES
17. Identifying Key Reviewers
17
Identify key reviewers based on:
1) Deliverable
– Edit check specification will not necessarily have the same reviewers as Data
Entry Guidelines
– Create a table of deliverables and identify reviewers & approvers
Deliverable Reviewers/Approvers
Data Management Plan Project Manager, Lead Data Manager
Edit Check Specifications Lead Data Manager, Database Developer
Batch Data Load Specifications Database Developer, Clinical Programmer
Dataset Listings Lead Data Manager, Clinical Programmer
2) Role
– Example: Chief Operating Officer does not need to review CRFs
– Example: CRA does not need to review dataset specifications
2011 FALL BIOMETRICS WEBINAR SERIES
18. One size does not fit all
18
Different types of trials have different study start-up needs
Phase 3 Phase 1
Global Multicenter Single Center
Oncology Trial Pain Trial
Number of Sites 258 1
Number of Subjects 1200 48
Duration 3.5 years 4 months
Number of CRF page 60 unique pages 24 unique pages
2011 FALL BIOMETRICS WEBINAR SERIES
19. Premier Express
19
Premise:
▪ Process designed to meet the needs of small phase 1
pharmaceutical and device studies
▪ Timelines for these studies are short
Key components:
▪ Standard data collection pages
▪ Don’t need to collect and subsequently analyze more data
than necessary
– Standard single module edit checks
– Limited sponsor reviews of key documents to expedite
execution of trial
2011 FALL BIOMETRICS WEBINAR SERIES
20. Case Study
20
DATA MANAGEMENT 45 days
Mock eCRF Development 13 days
STANDARD 9 WEEK TIMELINE Mock eCRF Development & Internal Review 6 days
Sponsor v1.0 Review and Comments Provided 3 days
13 days for CRF development Mock eCRF v1.0 Updated Based on Sponsor Comments 1 day
Sponsor v2.0 Review and Comments Provided 2 days
Mock eCRF v2.0 Updated Based on Sponsor Comments 1 day
Sponsor Approval 0 days
Annotated Case Report Form (aCRF) 11 days
aCRF Development & Internal Review 3 days
Sponsor v1.0 Review Comments Provided 3 days
11 days for aCRF development aCRF Updates Based on Sponsor Comments 1 day
Sponsor v2.0 Review Comments Provided 3 days
aCRF Updates Based on Sponsor Comments 1 day
Approval Annotated CRF 0 days
Database Development 8 days
Database Developed 2 days
8 days for database development Database QC & DM Testing 4 days
Data Entry Screens Tested by Sponsor (UAT) – optional 2 days
Database Activation 0 days
Edit Check Programming 13 days
Edit Checks Programmed 5 days
13 days for edit check development Data Management Testing 8 days
Edit Checks Activated 0 days
2011 FALL BIOMETRICS WEBINAR SERIES
21. Case Study
21
Phase 1 Single Center Pain Trial
Number of Sites 1
Number of Subjects 48
Duration 4 months
Number of CRF page 24 unique pages
Goal: database and edit checks activated within 5 weeks
Plan:
1) Use existing Premier Research CDASH Standard CRFs
2) Sponsor waived their review of CRFs and annotated CRFs
3) Limit internal CRFs and annotated CRFs reviews to relevant parties
and implement review meetings to streamline communication
4) Execute activities in parallel
2011 FALL BIOMETRICS WEBINAR SERIES
22. Case Study
22
DATA MANAGEMENT 45 days
Mock eCRF Development 13 days
ACCELERATED 5 WEEK TIMELINE Mock eCRF Development & Internal Review 6 days
Sponsor v1.0 Review and Comments Provided 3 days
4 days for CRF development Mock eCRF v1.0 Updated Based on Sponsor Comments 1 day
Sponsor v2.0 Review and Comments Provided 2 days
Mock eCRF v2.0 Updated Based on Sponsor Comments 1 day
Sponsor Approval 0 days
Annotated Case Report Form (aCRF) 11 days
aCRF Development & Internal Review 3 days
Sponsor v1.0 Review Comments Provided 3 days
3 days for aCRF development aCRF Updates Based on Sponsor Comments 1 day
Sponsor v2.0 Review Comments Provided 3 days
aCRF Updates Based on Sponsor Comments 1 day
Approval Annotated CRF 0 days
Database Development 8 days
Database Developed 2 days
7 days for database development Database QC & DM Testing 4 days
Data Entry Screens Tested by Sponsor (UAT) – optional 2 days
Database Activation 0 days
Edit Check Programming 13 days
Edit Checks Programmed 5 days
11 days for edit check development Data Management Testing 8 days
Edit Checks Activated 0 days
2011 FALL BIOMETRICS WEBINAR SERIES
23. Case Study
23
Mock eCRF Development 13 days
STANDARD Mock eCRF Development & Internal Review 6 days
Sponsor v1.0 Review and Comments Provided 3 days
13 days for CRF
development Mock eCRF v1.0 Updated Based on Sponsor Comments 1 day
Sponsor v2.0 Review and Comments Provided 2 days
Mock eCRF v2.0 Updated Based on Sponsor Comments 1 day
Sponsor Approval 0 days
Initial eCRF development and review reduced from 6 to 4 days by copying eCRFs Premier Research’s
standard pages. Sponsor leveraged Premier Research CDASH and study start-up expertise regarding the
look/feel of the data entry pages and the alignment of the data collection requirements with the protocol.
Mock eCRF Development 13 days
4
ACCELERATED Mock eCRF Development & Internal Review 6 days
4
Sponsor v1.0 Review and Comments Provided 0
3 days
4 days for CRF
development Mock eCRF v1.0 Updated Based on Sponsor Comments 0 days
1 day
Sponsor v2.0 Review and Comments Provided 0
2 days
Mock eCRF v2.0 Updated Based on Sponsor Comments 0 days
1 day
Sponsor Approval 0 days
2011 FALL BIOMETRICS WEBINAR SERIES
24. Case Study
24
DATA MANAGEMENT 36 days
Mock eCRF Development 4 days
ACCELERATED 5 WEEK TIMELINE Mock eCRF Development & Internal Review 4 days
Sponsor v1.0 Review and Comments Provided 0 days
4 days for CRF development Mock eCRF v1.0 Updated Based on Sponsor Comments 0 days
Sponsor v2.0 Review and Comments Provided 0 days
Mock eCRF v2.0 Updated Based on Sponsor Comments 0 days
Sponsor Approval 0 days
Annotated Case Report Form (aCRF) 11 days
aCRF Development & Internal Review 3 days
Sponsor v1.0 Review Comments Provided 3 days
3 days for aCRF development aCRF Updates Based on Sponsor Comments 1 day
Sponsor v2.0 Review Comments Provided 3 days
aCRF Updates Based on Sponsor Comments 1 day
Approval Annotated CRF 0 days
Database Development 8 days
Database Developed 2 days
7 days for database development Database QC & DM Testing 4 days
Data Entry Screens Tested by Sponsor (UAT) – optional 2 days
Database Activation 0 days
Edit Check Programming 13 days
Edit Checks Programmed 5 days
11 days for edit check development Data Management Testing 8 days
Edit Checks Activated 0 days
2011 FALL BIOMETRICS WEBINAR SERIES
25. Case Study
25
Annotated Case Report Form (aCRF) 11 days
STANDARD aCRF Development & Internal Review 3 days
Sponsor v1.0 Review Comments Provided 3 days
11 days for aCRF
development aCRF Updates Based on Sponsor Comments 1 day
Sponsor v2.0 Review Comments Provided 3 days
aCRF Updates Based on Sponsor Comments 1 day
Approval Annotated CRF 0 days
Initial aCRF development and review remains the same since aCRF generation is usually standard. Sponsor
leveraged Premier Research CDASH and start-up expertise regarding the names of the database objects.
Annotated Case Report Form (aCRF) 11 days
3
ACCELERATED aCRF Development & Internal Review 3 days
Sponsor v1.0 Review Comments Provided 0
3 days
3 days for aCRF
development aCRF Updates Based on Sponsor Comments 0 days
1 day
Sponsor v2.0 Review Comments Provided 0
3 days
aCRF Updates Based on Sponsor Comments 0 days
1 day
Approval Annotated CRF 0 days
2011 FALL BIOMETRICS WEBINAR SERIES
26. Case Study
26
DATA MANAGEMENT 28 days
Mock eCRF Development 4 days
ACCELERATED 5 WEEK TIMELINE Mock eCRF Development & Internal Review 4 days
Sponsor v1.0 Review and Comments Provided 0 days
4 days for CRF development Mock eCRF v1.0 Updated Based on Sponsor Comments 0 days
Sponsor v2.0 Review and Comments Provided 0 days
Mock eCRF v2.0 Updated Based on Sponsor Comments 0 days
Sponsor Approval 0 days
Annotated Case Report Form (aCRF) 3 days
aCRF Development & Internal Review 3 days
Sponsor v1.0 Review Comments Provided 0 days
3 days for aCRF development aCRF Updates Based on Sponsor Comments 0 days
Sponsor v2.0 Review Comments Provided 0 days
aCRF Updates Based on Sponsor Comments 0 days
Approval Annotated CRF 0 days
Database Development 8 days
Database Developed 2 days
7 days for database development Database QC & DM Testing 4 days
Data Entry Screens Tested by Sponsor (UAT) – optional 2 days
Database Activation 0 days
Edit Check Programming 13 days
Edit Checks Programmed 5 days
11 days for edit check development Data Management Testing 8 days
Edit Checks Activated 0 days
2011 FALL BIOMETRICS WEBINAR SERIES
27. Case Study
27
STANDARD Database Development 8 days
Database Developed 2 days
8 days for Database QC & DM Testing 4 days
database Data Entry Screens Tested by Sponsor (UAT) – optional 2 days
development
Database Activation 0 days
Because Standard CRF are used, database objects may be copied in from Standard Global Library. This
reduces initial development and QC time by 1 day. Sponsor UAT testing increases from 2 to 3 days because
this is the first time sponsor is seeing data entry screens.
ACCELERATED Database Development 8 days
7
Database Developed 21days
day
7 days for Database QC & DM Testing 4 days
3
database
Data Entry Screens Tested by Sponsor (UAT) – optional 2 days
3
development
Database Activation 0 days
2011 FALL BIOMETRICS WEBINAR SERIES
28. Case Study
28
DATA MANAGEMENT 27 days
Mock eCRF Development 4 days
ACCELERATED 5 WEEK TIMELINE Mock eCRF Development & Internal Review 4 days
Sponsor v1.0 Review and Comments Provided 0 days
4 days for CRF development Mock eCRF v1.0 Updated Based on Sponsor Comments 0 days
Sponsor v2.0 Review and Comments Provided 0 days
Mock eCRF v2.0 Updated Based on Sponsor Comments 0 days
Sponsor Approval 0 days
Annotated Case Report Form (aCRF) 3 days
aCRF Development & Internal Review 3 days
Sponsor v1.0 Review Comments Provided 0 days
3 days for aCRF development aCRF Updates Based on Sponsor Comments 0 days
Sponsor v2.0 Review Comments Provided 0 days
aCRF Updates Based on Sponsor Comments 0 days
Approval Annotated CRF 0 days
Database Development 7 days
Database Developed 1 day
7 days for database development Database QC & DM Testing 3 days
Data Entry Screens Tested by Sponsor (UAT) – optional 3 days
Database Activation 0 days
Edit Check Programming 13 days
Edit Checks Programmed 5 days
11 days for edit check development Data Management Testing 8 days
Edit Checks Activated 0 days
2011 FALL BIOMETRICS WEBINAR SERIES
29. Case Study
29
STANDARD Edit Check Programming 13 days
Edit Checks Programmed 5 days
13 days for Data Management Testing 8 days
database
Edit Checks Activated 0 days
development
Because Standard database objects are used, edit checks may be copied in from Standard Global Library.
This reduces initial development and QC time by 1 day.
Note: The example used in this case study required more edit checks than usual because of the complicated
enrollment criteria. Typically, the use of Premier Express would nearly eliminate all programming time.
ACCELERATED Edit Check Programming 13 days
11
Edit Checks Programmed 5 days
4
11 days for Data Management Testing 8 days
7
database
Edit Checks Activated 0 days
development
2011 FALL BIOMETRICS WEBINAR SERIES
30. Case Study
30
DATA MANAGEMENT 25 days
Mock eCRF Development 4 days
ACCELERATED 5 WEEK TIMELINE Mock eCRF Development & Internal Review 4 days
Sponsor v1.0 Review and Comments Provided 0 days
4 days for CRF development Mock eCRF v1.0 Updated Based on Sponsor Comments 0 days
Sponsor v2.0 Review and Comments Provided 0 days
Mock eCRF v2.0 Updated Based on Sponsor Comments 0 days
Sponsor Approval 0 days
Annotated Case Report Form (aCRF) 3 days
aCRF Development & Internal Review 3 days
Sponsor v1.0 Review Comments Provided 0 days
3 days for aCRF development aCRF Updates Based on Sponsor Comments 0 days
Sponsor v2.0 Review Comments Provided 0 days
aCRF Updates Based on Sponsor Comments 0 days
Approval Annotated CRF 0 days
Database Development 7 days
Database Developed 1 day
7 days for database development Database QC & DM Testing 3 days
Data Entry Screens Tested by Sponsor (UAT) – optional 3 days
Database Activation 0 days
Edit Check Programming 11 days
Edit Checks Programmed 4 days
11 days for edit check development Data Management Testing 7 days
Edit Checks Activated 0 days
2011 FALL BIOMETRICS WEBINAR SERIES
31. Summary
Time benefits gained from the use of EDC can
only be realized when an efficient DM
approach is used
Efficiencies in study start-up can be gained
through the use of standards, advanced
planning, and tailoring the process to meet the
project needs
2011 FALL BIOMETRICS WEBINAR SERIES
32. Upcoming Webinars
32
Register at www.premier-research.com/webinars
▪ Strategies for Implementing CDISC
13 December at11:00 am EST
Speaker: Thomas Kalfas
Listen to past webinars:
▪ The Role of Data Monitoring Committees
Speaker: Ron Kershner, Ph.D.
▪ IVR/IWR…More than just Randomization
Speaker: Ryan Michaud
2011 FALL BIOMETRICS WEBINAR SERIES
33. Questions?
Cheryl Silva
Associate Director, Technical Operations
234 Copeland Street
Quincy, MA 02169
Telephone: 617.237.1120
cheryl.silva@premier-research.com
2011 FALL BIOMETRICS WEBINAR SERIES