A Standard Computable Clinical Trial Protocol: The Role of the BRIDG Model

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "A Standard Computable Clinical Trial Protocol: The Role of the BRIDG Model"

Transcription

1 CLINICAL RESEARCH STANDARDS 383 Cara Willoughby, MS Eli Lilly and Company, Indianapolis, Indiana Doug Fridsma, MD, PhD University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania Lisa Chatterjee, MS Digital Infuzion, Inc., Gaithersburg, Maryland John Speakman National Cancer Institute, Rockville, Maryland Julie Evans Clinical Data Interchange Standards Consortium, Austin, Texas Rebecca Kush, PhD Clinical Data Interchange Standards Consortium, Austin, Texas A Standard Computable Clinical Trial Protocol: The Role of the BRIDG Model Today s clinical trial processes are inefficiently mired in excessive documentation and unnecessary human intervention. The protocol lies at the heart of these operations, making it a prime candidate for the benefits afforded by computer processing. With a vision to develop a standard machine-readable protocol, the Protocol Representation (PR) group, a team within the Clinical Data Interchange Standards Consortium (CDISC), identified a set of elements common to regulated clinical research protocols. These elements are being incorporated into the Biomedical Research Integrated Domain Group (BRIDG) model, an information model of biomedical research initiated by CDISC and collaboratively developed and maintained by CDISC, Health Level Seven (HL7), the National Cancer Institute (NCI), the Food and Drug Administration (FDA), and other stakeholders. The PR group plans to use BRIDG as a pathway to develop a standard structured protocol representation so that protocol information can be repurposed across multiple clinical research documents, databases, and systems from study start-up through reporting and regulatory submissions. The BRIDG model provides a means of knowledge acquisition, a tool for communication, a focus for collaboration, a starting point for application development, a means to standards development and harmonization, and an informatics research platform to support clinical research. Key Words Protocol; Clinical research; BRIDG; Standard; Model Corresponding Address Rebecca Kush, PhD, CDISC, Two Rivers Cove, Austin, TX 78717( INTRODUCTION Scientific communication in the biopharmaceutical industry occurs largely through documents, as evidenced by the elaborate document management processes and the volumes of paper that are features of traditional drug development and marketing. Although sophisticated techniques and tools are available for managing these documents, the number of documents that must be managed within any one organization continues to escalate. This increase in complexity limits our abilities to identify, to find, and to retrieve key items of information within and across these documents, as well as our ability to reuse the information effectively and efficiently. Mired in documentation, current clinical research processes are heavily dependent on human intervention, complex data integration steps, and interpretation. The translation and transcription of salient clinical information from these documents into other documents and databases, so that it can be used to drive related internal and external processes, including report generation and knowledge management, is essentially still a manual process. Perhaps the best illustration of this is the complex document that lies at the core of all trials the protocol. As defined by the International Conference on Harmonisation (ICH) of Technical Requirements for Registration of Pharmaceuticals for Human Use, a protocol is a document that describes the objective(s), design, methodology, statistical considerations and organization of a trial. The protocol usually also gives the background and rationale for the trial, but these could be provided in other protocol referenced documents (1). The protocol document is used in clinical research in much the same manner as a blueprint is used in the construction of a building. It is the definitive source for most of the key information about the study throughout its life span, including Institutional Review Board (IRB) evaluation, site setup, recruitment, inventory management, data management, database lock, analysis, reporting, and often beyond to regulatory submissions and postapproval marketing. Currently, this information is buried within a monolithic text document. This creates two problems. First, it limits the ability to assess the Drug Information Journal, Vol. 41, pp , /2007 Printed in the USA. All rights reserved. Copyright 2007 Drug Information Association, Inc.

2 384 CLINICAL RESEARCH STANDARDS Willoughby et al. quality of the protocol. Today s densely written documents are often ambiguous and lack clarity in describing procedures. For example, ensuring that inclusion and exclusion criteria are specified correctly and consistently throughout the protocol is time consuming and resource intensive. Inconsistencies can be found after the protocol has received IRB approval or even after the trial has started, which cause significant delays while the protocol is rewritten, reapproved, and redistributed. A more profound limitation is in the ability to locate and reuse that information, internally and externally, in downstream processes, documents, databases, and reports. For example, we may want to know whether a particular study is a blinded study. At present, one simple approach might be to use a search tool on the text document to search for key words such as study design or blind, but a full-text search usually requires the user to consciously tab through several findings of the word blind until the appropriate usage is identified (eg, This is a double-blind study. ). Furthermore, if synonyms are used (eg, masking for blinding ), such an approach will fail. The surest way is for a qualified individual to read the entire document carefully from the beginning. Since the mid-1990s, ICH guidelines have provided content and format standards for some of the most common clinical research documents submitted to regulatory agencies. Most drug development organizations and major academic medical centers have designed internal templates based on these guidelines and related regulatory requirements. Familiarity with these guidelines, or templates, certainly aids manual navigation, but the information is not sufficiently structured to be usefully interpreted by computer applications in a consistent manner. Furthermore, we often need to find detailed information (eg, degree of blinding) not for just one study but for many and across many documents. For example, a regulatory agency may request that a sponsor provide data from all clinical trials conducted on a drug that included geriatric patients with previous history of heart disease. If the sponsor is not already tracking this, and especially if this drug has been on the market for several years or has multiple approved indications, this information cannot be provided without a substantial amount of manual effort. In addition, recent interest in ensuring transparency of clinical research activities, and providing patients with a means to identify ongoing clinical studies in which they could participate, has encouraged the global development of registries with readily searchable key protocol information. The clinical research and drug development industries would clearly benefit from a computable way to find and repurpose clinical research information. PROTOCOL REPRESENTATION STANDARD INITIAL PROGRESS In 2002, awareness of the aforementioned limitations of protocols prompted leaders from Health Level 7 (HL7), Food and Drug Administration (FDA), and Clinical Data Interchange Standards Consortium (CDISC) to initiate a Protocol Representation (PR) project within the HL7 Regulated Clinical Research Information Management (RCRIM) Technical Committee. This PR group also became a team within CDISC. Membership includes clinical project managers, medical communication specialists, academic scientists, representatives of technology vendors, and statisticians with specific expertise in protocol development for regulated clinical trials. The original scope statement of the group was to identify standard elements of a clinical trial protocol that can be further elucidated and codified to facilitate study design, regulatory compliance, project management, trial conduct and data interchange among consumers and systems. In this statement, standard elements refers to the common component parts or the customary informational units found in most clinical research protocols. Because much of the content for a regulated clinical research protocol has been prescribed by the ICH, the overall hierarchy and the initial set of elements are based on ICH E6 and ICH E3 guidelines (1,2). These are primarily applicable to efficacy and safety trials but can be applied to other types of clinical

3 A Standard Computable Clinical Trial Protocol CLINICAL RESEARCH STANDARDS 385 research as well. Another reference for protocol elements included European Medicines Agency s (EMEA) EudraCT (3) and the CDISC Study Data Tabulation Model (SDTM) Study Summary (4). Later, elements from the CDISC SDTM Trial Design Model (TDM) were also included as well as elements related to statistical analysis based on ICH E9 Guidelines (5). Several other decisions and assumptions helped to lay the foundation for the PR standardization effort; these are outlined in a recently published article by Kush in Next Generation Pharmaceuticals (6). As of 2006, 264 protocol elements had been identified and described. These are posted as a spreadsheet in the Standards area of the CDISC Web site (7). During the development of this spreadsheet, every effort was made to accommodate different types of protocols for clinical research on a global basis. The spreadsheet contains detailed information about each element, including the element name, definition, explanation, and sources for each element and definition. Much of this information was concurrently used to enhance the CDISC glossary (8). Elements are categorized within the spreadsheet by the section heading topics outlined in ICH E6 (Figure 1). An example of the spreadsheet hierarchy, which includes headers, subheaders, and elements, is shown in Figure 2. A STANDARD STRUCTURED PROTOCOL REPRESENTATION The spreadsheet resulting from the initial work to identify and describe standard elements of a protocol is undeniably useful for many purposes, including building consensus around protocol content and meaning and ensuring that all necessary elements would be included in a newly authored protocol. However, the spreadsheet structure is basically flat, lacking information on how each element relates to another, the overall study process, and whether it is a single element or representative of a collection of elements. Following an initial attempt at creating an HL7 model from a subset of the protocol elements, it became clear that the approach and priorities for the PR work needed to be reviewed Protocol Representation Hierarchy Document Type General Information Background Information Trial Objectives and Purpose Trial Design Subject Selection and Withdrawal Subject Participation/Study Design Treatment of Subjects Efficacy Assessments Assessment of Safety Statistics Direct Access to Source Documents Quality Control and Quality Assurance Ethics Data Handling and Record Keeping Financing and Insurance Publication Policy Supplements Protocol Representation Hierarchy Sample: Sections, Subsections, Elements Document Type Clinical Trial Protocol General Information Protocol Identification Protocol Title Protocol Short Title Protocol Identification Number Protocol Contact Information Sponsor Sponsor Status =Section =Subsection =Element FIGURE 1 Protocol representation top-level sections. FIGURE 2 Hierarchy of protocol representation spreadsheet based on ICH E6, E3, and E9. Drug Information Journal

4 386 CLINICAL RESEARCH STANDARDS Willoughby et al. and revised. New directions for this effort included (a) leveraging standards that had matured since the initiation of the PR project, along with the PR elements spreadsheet, particularly the CDISC SDTM TDM and Trial Summary domain [which is identified as a specification in the FDA Final Guidance for esubmissions (9)]; (b) leveraging the domain analysis model that had been initiated to harmonize the CDISC standards and represents protocol as the research plan; and (c) agreeing on an initial set of priority use cases out of the many in which the protocol is involved in clinical research. On the basis of the new direction, the use cases that were agreed to be highest priority were the following: 1. To support the CDISC SDTM (eg, trial design, inclusion/exclusion criteria, planned assessments, interventions, and analyses). 2. To support study tracking databases (eg, EudraCT, clinicaltrials.gov, the protocol/trial tracking aspect of trial registry, or results databases or databases that support project management tools). 3. To support the development of the clinical trial protocol document. The new scope and mission for the PR group thus became To develop a standard structured protocol representation that supports the entire life-cycle of clinical research protocols to achieve semantic interoperability (the exchange of content and meaning) among systems and stakeholders. In this context, the term structured means that the data elements, and the relationships between them, are defined consistently and unambiguously, and are thus computable (ie, amenable to automated processing) and will enable semantic interoperability (exchange of content and meaning). For information from any standard to be acted on by a machine, it must be not only consistent but also compartmentalized, or broken into components or subcomponents that are identified and clearly defined, with the relationships between them likewise clearly defined. This process of assigning identification to information requires people to be unambiguous and precise about meanings and terminology (ie, semantics) and to reach a consensus on meaning where none may have existed before. Any experienced clinical site monitor, investigator, or regulator will quickly confirm that the typical clinical trial protocol document contains many implied meanings and unclear instructions that often lead to misinterpretations, errors, and inconsistencies in trial conduct. This becomes especially complicated when different companies/protocol sponsors have different meanings for the same word. The analysis that must be conducted to create a structured protocol can add value through improved clarity and communication, even if there is no immediate use case for computability of that protocol. In other words, this analysis confers benefits that can be realized even in a paper-based world. In addition to precise, unambiguous definitions for the elements in the PR spreadsheet, there must be a means to capture the information necessary to describe the richness and complexity of the relationships among the protocol elements, that is, a method for representing how these protocol elements relate to, and interact with, other items of information in the clinical trial life cycle. The aforementioned domain analysis model, now named the Biomedical Research Integrated Domain Group (BRIDG) model, fulfills this purpose. THE BRIDG MODEL The BRIDG model is now being approached as a collaborative project led by CDISC, National Cancer Institute (NCI), FDA, and HL7 and includes representatives from these organizations and other stakeholders. The goal is to construct a comprehensive domain analysis model that represents biomedical and clinical research in the context of health care. For the BRIDG model, clinical research is the domain of analysis. The development of the BRIDG model was initiated by CDISC in 2004 as an effort to harmonize existing CDISC models among one another and to harmonize clinical research standards with health care standards. Representatives of the CDISC board developed the initial model, which had the protocol as a major component at

5 A Standard Computable Clinical Trial Protocol CLINICAL RESEARCH STANDARDS 387 its center. The HL7 RCRIM Technical Committee (which was initiated by CDISC, HL7, and FDA) soon adopted this model as its domain analysis model. Using the HL7 Development Framework (HDF) methodology, an HL7 expert led clinical research domain experts through a series of focused modeling and vetting sessions to develop an overarching model intended to represent the entire clinical research domain. The HDF provides a means of eliciting knowledge from subject-matter experts and representing it in a Unified Modeling Language (UML) diagram, using naming conventions and terminology that are familiar to these subject-matter experts. This is the first action in a set of modeling steps necessary for achieving successful harmonization with the HL7 Reference Information Model (RIM), which because of its abstract and complex nature, typically requires HL7 expertise (a highly technical skill set not prevalent within the clinical research community) to navigate and interpret effectively. Concurrent with this CDISC initiative, the NCI instituted a research project called the Cancer Biomedical Informatics Grid (cabig ) a large-scale initiative aimed at creating an interconnected grid of shared data and software tools to support the cancer research community in the delivery of molecular medicine, in the form of innovative therapies, to cancer patients (10). Rather than construct yet another standard for the interchange of protocol information, researchers from the cabig program collaborated with CDISC and HL7 to develop the BRIDG model; CDISC and BRIDG models were considered to be best of breed for the clinical research domain. In November 2004, a team of modelers and clinical protocol experts representing CDISC, HL7, and cabig assembled to begin collaborative work specifically focused on the clinical trial protocol and incorporation of these elements into the existing BRIDG model. Using the initial model developed by CDISC and the 264 protocol elements identified by the PR group as a starting point, the team held a series of meetings over the next six months to construct the preliminary scaffolding of a UML model for protocol-driven clinical research. The process for modeling the protocol meant representing the entire plan for the clinical trial and concentrating on the protocol as a plan for a trial, as opposed to an actually instantiated trial. Placing the 264 protocol elements within the rich representation of the BRIDG model provided a way for subject-matter experts to describe both the what and the how of clinical trials and established a forum for subject-matter experts to clarify the semantics of those protocol elements. The modeling process required domain experts to be rigorous in defining each clinical research information element, in defining the relationships between each element, and in placing the elements and the relationships into the context of specific work processes. This required domain experts to define roles, responsibilities, and the interaction of elements as part of clinical research. For example, knowing that a particular data element is used both for tracking a clinical trial and for registering a clinical trial with external registries would be useful in defining the semantics and the requirements necessary for that element. In addition to the value that the BRIDG modeling effort has had in clarifying the semantics of clinical research and producing a comprehensive and clear representation of clinical research data elements, the process of developing the BRIDG model has served to unify communities within biomedical research, including pharmaceutical development organizations, government bodies, academic medical centers, standards organizations, and related service and technology providers. The HL7 RCRIM Technical Committee has now agreed that the BRIDG model should serve as its domain analysis model for developing all of their standards. CDISC is using the BRIDG model to help harmonize the existing CDISC standards to support the entire life cycle of clinical research. Within the cabig program, the BRIDG model is the starting point in the process of developing interoperable applications that share a common semantic foundation, and harmonization is under way to ensure that these diverse applications and groups Drug Information Journal

6 388 CLINICAL RESEARCH STANDARDS Willoughby et al. can realize the promise of BRIDG and interoperate in a predictable way. The BRIDG model will continue to evolve, even as it is being implemented for specific developed applications. It is an open model, undergoing collaborative development by several key stakeholders. Anyone can contribute to this model by volunteering in one of the stakeholder organizations or by visiting the open-source Web site for the BRIDG project (11). From this Web site, the model can be viewed and downloaded in various formats. Process guidelines for harmonizing existing clinical research information models into BRIDG are in preparation, and an advisory board of representatives from the key stakeholders has been established to ensure that the model remains open, collaborative, and applicable to the stakeholder communities. The model will remain valuable only to the extent that the subject-matter experts within the community contribute to it, interact with it, build on it, and use it. LOOKING FORWARD Although structuring information requires careful analysis of how information should be divided or parsed into smaller units, the goals and intended use for the structured information must drive this analysis to ensure that the resulting representation is useful. The protocol document is used in many activities and serves multiple purposes throughout the life cycle of the clinical trial. The ultimate goal of the structured protocol is to make clinical protocol information backward-referenceable and forwardreusable within and across multiple clinical trial documents, databases, and systems. Three PR priority use cases will enable the development of a standard machine-readable protocol in stages, based on current needs, implementations, and additional use cases. These will both complement and support some of the other BRIDG initiatives that are under way by various stakeholders. The three priorities for furthering the protocol representation work will be described in greater detail; the analogous components of the protocol, which these priorities support, are depicted in Figure 3. PRIORITY 1: SUPPORT THE CDISC STUDY DATA TABULATION MODEL (SDTM) In July 2004, the FDA announced its desire to receive data for New Drug Applications (NDAs) in the SDTM standard format (12). Since then, several NDA submissions have employed the SDTM and more are in preparation. The SDTM is a standard for submission of study data tabulations and also study design information; such a standard for submission of data provides many benefits to regulatory reviewers. Through the use of tools built to read standard SDTM information, reviewers can work with the data more efficiently, with less preparation time. In addition, the FDA and NCI are currently implementing a cross-trial data warehouse (Janus) that will include both information on the study plan/design (ie, protocol information) and the results of those studies. Structured protocol provides the baseline plan so it can be effectively compared against actual data by reviewers. Some of the most important FDA priorities for structured protocol representation include: Trial design Inclusion/exclusion criteria Planned assessments (time and events table) and planned interventions Explicit statistical analysis plan components The PR group is developing structured representations of each of these key portions of the clinical trial plan. The TDM describes a general model for representing treatment arms (represented as horizontal bars in Figure 4), elements within an arm and visits (represented as the cells at the intersections between the horizontal and vertical bars), and is published as part of the SDTM. Inclusion/exclusion criteria will eventually need to be described in a computer-executable manner, which is being pursued. The planned assessments and interventions supports the time and events table, sometimes referred to as the schedule of events, or study calendar, which is found in all clinical trial protocols. Elements of the statistical analysis plan that are typically found in protocols are also included

7 A Standard Computable Clinical Trial Protocol CLINICAL RESEARCH STANDARDS 389 Clinical Trial Registry (CTR); Trial Tracking Trial Design Part 1 Protocol Components for Element Identification, BRIDG Modeling, XML Schema Development Time and Events Table Elements; Trial Design Part 2 Eligibility Criteria Statistical Analysis Plan Elements Machine-Readable Protocol Development and Testing Remaining Protocol Study Report Sections FIGURE 3 Components for developing a machine-readable protocol. Jan 2006 in the PR spreadsheet and are being incorporated into the PR model. When these content models are available, they will be modeled and harmonized into the BRIDG. XML implementations, both extensions of the CDISC Operational Data Model (ODM) and HL7 messages, can then be developed. Work is also under way both to develop interfaces to existing software packages and to develop new applications to support these elements. So another goal of the PR group is to use the PR model as an interface with these tools to facilitate, not only the protocol authoring but also the setup of the trial databases and the data collection (case report) forms based on that protocol. Although the SDTM was designed for submission of data to regulators, it is also used to facilitate data interchange between trial sponsors, partners, and technology or service, providers. If a drug development organization is going to use the SDTM for any reason, it seems logical to increase return on investment by using a protocol standard that is compatible in structure and can be applied throughout the clinical trial life cycle. The recently completed CDISC business case (13), in fact, indicates that the most value from standards applied to clinical research comes when they are implemented in the startup stage of a study, especially in the earliest stages of clinical development. Screen 1st Treatment 1st 2nd Treatment 2nd 3rd Treatment Follow up FIGURE 4 P P P Screen Placebo Screen 5 mg Screen 5 mg Randomization 5 mg Placebo 10 mg 10 mg 10 mg Placebo Follow up Follow up Follow up Example of the arms and epochs in a protocol using the TDM (supporting both the SDTM and protocol representation); courtesy of Diane Wold, TDM Team Leader. Drug Information Journal

8 390 CLINICAL RESEARCH STANDARDS Willoughby et al. PRIORITY 2: SUPPORT CLINICAL TRIAL REGISTRY (STUDY SUMMARY) AND TRACKING DATABASES The next highest priority for developing the structured protocol is the creation of a model to support protocol/trial tracking and the various clinical trial registries, such as the European clinical trials tracking database (EudraCT), clinicaltrials.gov, and the NCI s Physicians Data Query (PDQ ). Such a model would logically encompass a sufficiently representative subset of the eventual structured PR. Building on previous work, the PR spreadsheet of elements, which had already undergone a significant level of critical review, was used to identify a subset of appropriate elements for trial registration or trial tracking. This subset was further developed into a clinical trial registry (CTR) element spreadsheet that has been cross-referenced extensively with code lists for clinicaltrials.gov (14), the World Health Organization (WHO) Registration Data Set v2.2 (15), SDTM Trial Summary Codes (SDTM V3.1.1), PDQ DTD/Schema, and EudraCT. As discussed earlier, because the spreadsheet format lacks the structure required to define the domain fully, these elements were modeled for harmonization into the BRIDG model (Figure 5). Elements that map directly to the WHO Registration Data Set have already been added as an extension to the CDISC Operational Data Model (an XML backbone that carries CRF data and also can carry the SDTM data and metadata), thus enabling electronic WHO registration transmissions today. An HL7 standard is also being considered as an alternate implementation for use in transmissions to multiple trial registries. Inclusion and exclusion criteria are an essential component of trial registries, thus the development of machine-readable eligibility criteria (see priority 1) may actually be viewed as an extension to the CTR work. This is an area of the protocol that is of great interest to many different stakeholders. The stakeholders include registries, those offering ways to match patients to protocols, protocol-authoring software vendors, trial conduct management software vendors, and clinical trials staff eager to reduce the subjectivity of interpreting the eligibility criteria text. A machine-readable standard might also facilitate the conduct of international trials by framing the criteria using international standards and code lists to represent textual eligibility criteria. FIGURE 5 An example of a subset (14 of a total of 65 elements) of the Clinical Trial Registry Model in Preparation of UML modeling for the BRIDG; courtesy of Lakshmi Grama, CTR Team Leader. Protocol Title Protocol Short Title Protocol Identifier Clinical Trials Phase Study Synopsis Participation Type Trial Status Target Study Population Description Target Disease Condition Date of First Enrollment Duration of Subject Participation Targeted Accrual Study Purpose Study Investigation Type Clinical Trials Activities: Study.long Title Clinical Trials Activities: Study.shortTitle Clinical Trials Activities: Study.id Clinical Trials Activities: Study.phaseCode Clinical Trials Activities: Study.description Clinical Trials Activities: Study.multilnstitutionInd Clinical Trials Activities: Study.status Clinical Trials Activities: Study.populationDescription Clinical Trials Activities: Study.targetConditionCode Clinical Trials Activities: Planned Study.TBD Clinical Trials Activities: Planned Study.plannedSubjectParticipationDuration Clinical Trials Activities: Planned Study.plannedSubjectInterventionDuration Clinical Trials Activities: Planned Study.targetAccrualNumber Clinical Trials Activities: Study.intentCode Clinical Trials Activities: Study.TBD

9 A Standard Computable Clinical Trial Protocol CLINICAL RESEARCH STANDARDS 391 PRIORITY 3: SUPPORT THE DEVELOPMENT OF THE CLINICAL TRIAL PROTOCOL DOCUMENT Because this priority has a broad scope, the initial activities toward this use case have focused on working with technology providers who are developing specialized applications based on BRIDG that will use the PR standard. Stakeholders in the BRIDG project understand that standards alone are not useful without the applications that use them. Some individuals have joined the PR group for the purpose of being on the bleeding edge of tool development using the BRIDG. Presentations have been shared at multiple Drug Information Association, HL7, CDISC, Bio IT World, and vendor user group meetings, and several white papers and articles have been published to increase awareness of these projects. A selection of these is included on the CDISC Web site (13) ( This outreach effort has resulted in expressions of interest from several vendors to develop applications using the BRIDG model. Although some are waiting for BRIDG to be refined and expanded to include the areas addressed, many vendors and other groups are actively developing applications using parts of BRIDG and are concurrently enhancing the BRIDG model with their experience. By instantiating the model in software applications, these efforts improve the robustness of the BRIDG model and make tools available to leverage the protocol representation standard in streamlining clinical research. SUMMARY Because all clinical data and conclusions are ultimately rooted in the protocol, the concept of a machine-readable clinical trial protocol has the potential for pervasive impact far beyond the traditional boundaries of that document. Building on ICH content guidelines, a set of elements has been identified as common across the majority of regulated clinical trial protocols and other clinical research protocols. Although this is a necessary step for making information amenable to automated processing, it is insufficient without the added detail provided through conscious and explicit representation of the relationships and interactions among these elements with the rest of the clinical research space. BRIDG has served as a focus within the biomedical research community for a range of activities that will support the goal of a semantically interoperable representation of clinical trials and provides: A method of knowledge acquisition, providing a means of clarifying the semantics of clinical research concepts, and the important relationships and interactions between them. A tool for communication, helping to convey the semantics of clinical trials to people charged with developing applications to support them. A focus for collaboration, bringing together different stakeholders engaged in clinical trials research in an effort to develop and record the shared semantics. A method for developing and harmonizing standards. A starting point for application development for information technology vendors within HL7 and within cabig. The domain analysis model for HL7 RCRIM, which will serve to harmonize all RCRIM standards. An informatics research platform, bringing the expertise of the informatics community to bear on the very concrete problem of understanding and streamlining the administration and workflow of the clinical research process. It is hoped that BRIDG will stimulate new research in informatics, as clinical research workflow becomes better understood. As a key aspect of the BRIDG modeling, the elements and semantics from the PR spreadsheet of common protocol elements have laid the foundation for representing detailed structure of specific use cases for protocol information within BRIDG. The structuring of key pieces of the protocol such as the trial design and the planned time and events table has the potential to support and significantly enhance important use cases elsewhere in the life cycle of a clinical trial from case report development and registration though submission. The BRIDG can serve as a basis for CDISC ODM, HL7 V3 messages, or other implementa- Drug Information Journal

10 392 CLINICAL RESEARCH STANDARDS Willoughby et al. tions. The semantics will be the same (ie, based on a common domain analysis model) so that the information can be readily exchanged and integrated across different tools, applications, and databases, regardless of the way the protocol representation content standard is implemented. Through a combination of structured clinical trial information and standards-based tools, the drug development industry and other areas of biomedical research will reap the benefits that the developers of the structured protocol and BRIDG have been striving to achieve. Acknowledgments We express appreciation to Diane Wold, Joel Hoffman, Greg Anglin, and Art Gertel for editorial assistance with the manuscript. REFERENCES 1. International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. ICH Harmonised Tripartite Guideline. Guideline for Good Clinical Practice E6; International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. ICH Harmonised Tripartite Guideline. Structure and Content of Clinical Reports E3; European Clinical Trials Database EudraCT. Available at: Accessed March 15, CDISC Study Data Tabulation Model. Available at: index.html. Accessed March 15, International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. ICH Harmonised Tripartite Guideline. Structure and Content of Clinical Reports E9; Kush, R. Can clinical trial protocols be standardized? Next Generation Pharm. 2005; Protocol standard protocol representation spreadsheet. Available at: standards/prelements_fulllist2 0-0.pdf. Accessed March 15, CDISC Glossary Group. Clinical research glossary, version 4.0. Appl Clin Trials. 2005;14(special resource issue): FDA Final Guidance (Specifications SDTM). Available at: ersr/studydata-v1.3.pdf. Accessed March 15, cabig. Available at: Accessed March 15, BRIDG. Available at: Accessed March 15, FDA announces standard format that drug sponsors can use to submit human drug clinical trial data. FDA News. July 21, 2004: CDISC Business Case. Available at: Accessed March 15, ClinicalTrials.gov. Available at: Accessed March 15, WHO registration dataset. Available at: Accessed March 15, Lisa Chatterjee has disclosed that she has received financial or material support from Digital Infuzion, Inc. Cara Willoughby has disclosed that she is an employee and stock shareholder of Eli Lilly and Company. Doug Fridsma has disclosed that he receives research support from the National Institutes of Health and the National Cancer Institute. John Speakman has no conflicts to disclose. Rebecca Kush has no conflicts to disclose.

BRIDGing CDASH to SAS: How Harmonizing Clinical Trial and Healthcare Standards May Impact SAS Users Clinton W. Brownley, Cupertino, CA

BRIDGing CDASH to SAS: How Harmonizing Clinical Trial and Healthcare Standards May Impact SAS Users Clinton W. Brownley, Cupertino, CA BRIDGing CDASH to SAS: How Harmonizing Clinical Trial and Healthcare Standards May Impact SAS Users Clinton W. Brownley, Cupertino, CA ABSTRACT The Clinical Data Interchange Standards Consortium (CDISC),

More information

Electronic Submission of Regulatory Information, and Creating an Electronic Platform for Enhanced Information Management

Electronic Submission of Regulatory Information, and Creating an Electronic Platform for Enhanced Information Management Written Notice of Participation by the Clinical Data Interchange Standards Consortium (CDISC) and Written Statement for Discussion Topics to be Addressed In the FDA Public Hearing: Electronic Submission

More information

CDISC Journal. The BRIDG Model and a Model Implementation: The Clinical Trial Registration and Results HL7 Message

CDISC Journal. The BRIDG Model and a Model Implementation: The Clinical Trial Registration and Results HL7 Message CDISC Journal Clinical Data Interchange Standards Consortium O ctober 2011 The BRIDG Model and a Model Implementation: The Clinical Trial Registration and Results HL7 Message By Julie Evans and Abdul-Malik

More information

Development of an open metadata schema for Prospective Clinical Research (openpcr)

Development of an open metadata schema for Prospective Clinical Research (openpcr) Supplementary Web Material Development of an open metadata schema for Prospective Clinical Research (openpcr) in China A. Methods We used Singapore Framework for Dublin Core Application Profiles (DCAP),

More information

Udo Siegmann member of e3c, CDISC Sen. Dir. Acc. Management PAREXEL

Udo Siegmann member of e3c, CDISC Sen. Dir. Acc. Management PAREXEL Innovative Medicines Technological Platform Udo Siegmann member of e3c, CDISC Sen. Dir. Acc. Management PAREXEL Facts about PAREXEL Full service CRO (Clinical Research Organisation) Involved in more than

More information

Understanding CDISC Basics

Understanding CDISC Basics Trends in Bio/Pharmaceutical Industry Understanding CDISC Basics Jane Ma Abstract Data standards can make data and its associated program more portable. The CDISC (Clinical Data Interchange Standards Consortium)

More information

CDISC and Clinical Research Standards in the LHS

CDISC and Clinical Research Standards in the LHS CDISC and Clinical Research Standards in the LHS Learning Health System in Europe 24 September 2015, Brussels Rebecca D. Kush, PhD, President and CEO, CDISC CDISC 2015 1 CDISC Healthcare Link Goal: Optimize

More information

CDISC Strategy Document Version 9 (Final BOD Approved Version) 4 December 2006

CDISC Strategy Document Version 9 (Final BOD Approved Version) 4 December 2006 CDISC Strategy Document Version 9 (Final BOD Approved Version) 4 December 2006 Introduction The Clinical Data Interchange Standards Consortium (CDISC) has established standards to support the acquisition,

More information

Statistical Operations: The Other Half of Good Statistical Practice

Statistical Operations: The Other Half of Good Statistical Practice Integrating science, technology and experienced implementation Statistical Operations: The Other Half of Good Statistical Practice Alan Hopkins, Ph.D. Theravance, Inc. Presented at FDA/Industry Statistics

More information

Pilot. Pathway into the Future for. Delivery. April 2010 Bron W. Kisler, CDISC Senior Director bkisler@cdisc.org

Pilot. Pathway into the Future for. Delivery. April 2010 Bron W. Kisler, CDISC Senior Director bkisler@cdisc.org SHARE S&V Document and the Pilot Pathway into the Future for Standards Development and Delivery April 2010 Bron W. Kisler, CDISC Senior Director bkisler@cdisc.org 1 CDISC Mission To develop and support

More information

Managing and Integrating Clinical Trial Data: A Challenge for Pharma and their CRO Partners

Managing and Integrating Clinical Trial Data: A Challenge for Pharma and their CRO Partners Managing and Integrating Clinical Trial Data: A Challenge for Pharma and their CRO Partners Within the Pharmaceutical Industry, nothing is more fundamental to business success than bringing drugs and medical

More information

Use of Electronic Health Records in Clinical Research: Core Research Data Element Exchange Detailed Use Case April 23 rd, 2009

Use of Electronic Health Records in Clinical Research: Core Research Data Element Exchange Detailed Use Case April 23 rd, 2009 Use of Electronic Health Records in Clinical Research: Core Research Data Element Exchange Detailed Use Case April 23 rd, 2009 Table of Contents 1.0 Preface...4 2.0 Introduction and Scope...6 3.0 Use Case

More information

11. Extension Potential Financial Benefits

11. Extension Potential Financial Benefits 11. Extension Potential Financial Benefits Estimating the financial value of using electronic health records (EHR) for clinical research is fraught with difficulties for a number of reasons, some of which

More information

Streamlining the drug development lifecycle with Adobe LiveCycle enterprise solutions

Streamlining the drug development lifecycle with Adobe LiveCycle enterprise solutions White paper Streamlining the drug development lifecycle with Adobe LiveCycle enterprise solutions Using intelligent PDF documents to optimize collaboration, data integrity, authentication, and reuse Table

More information

Clinical Data Management BPaaS Approach HCL Technologies

Clinical Data Management BPaaS Approach HCL Technologies Leading pharmaceutical companies are estimating new business models including alternative Clinical data management platforms to reduce costs, shorten timelines, and maintain quality and compliance. HCL

More information

Introduction to the CDISC Standards

Introduction to the CDISC Standards Introduction to the CDISC Standards Sandra Minjoe, Accenture Life Sciences, Wayne, Pennsylvania ABSTRACT The Clinical Data Interchange Standards Consortium (CDISC) encompasses a suite of standards across

More information

USE CDISC SDTM AS A DATA MIDDLE-TIER TO STREAMLINE YOUR SAS INFRASTRUCTURE

USE CDISC SDTM AS A DATA MIDDLE-TIER TO STREAMLINE YOUR SAS INFRASTRUCTURE USE CDISC SDTM AS A DATA MIDDLE-TIER TO STREAMLINE YOUR SAS INFRASTRUCTURE Kalyani Chilukuri, Clinovo, Sunnyvale CA WUSS 2011 Annual Conference October 2011 TABLE OF CONTENTS 1. ABSTRACT... 3 2. INTRODUCTION...

More information

TransCelerate's Role in Transforming Pharmaceutical Trials Presentation to PCORNet

TransCelerate's Role in Transforming Pharmaceutical Trials Presentation to PCORNet TransCelerate's Role in Transforming Pharmaceutical Trials Presentation to PCORNet Dalvir Gill, PhD - Chief Executive Officer 17 October, 2014 Presentation Objectives + TransCelerate History + Participating

More information

Accelerating Clinical Trials Through Shared Access to Patient Records

Accelerating Clinical Trials Through Shared Access to Patient Records INTERSYSTEMS WHITE PAPER Accelerating Clinical Trials Through Shared Access to Patient Records Improved Access to Clinical Data Across Hospitals and Systems Helps Pharmaceutical Companies Reduce Delays

More information

Joint Position on the Disclosure of Clinical Trial Information via Clinical Trial Registries and Databases 1 Updated November 10, 2009

Joint Position on the Disclosure of Clinical Trial Information via Clinical Trial Registries and Databases 1 Updated November 10, 2009 Joint Position on the Disclosure of Clinical Trial Information via Clinical Trial Registries and Databases 1 Updated November 10, 2009 The innovative pharmaceutical industry 2 is committed to the transparency

More information

Extracting the value of Standards: The Role of CDISC in a Pharmaceutical Research Strategy. Frank W. Rockhold, PhD* and Simon Bishop**

Extracting the value of Standards: The Role of CDISC in a Pharmaceutical Research Strategy. Frank W. Rockhold, PhD* and Simon Bishop** Extracting the value of Standards: The Role of CDISC in a Pharmaceutical Research Strategy Frank W. Rockhold, PhD* and Simon Bishop** GlaxoSmithKline Research and Development. RTP NC and Stevenage, UK

More information

Janus Clinical Trials Repository (CTR) An Update

Janus Clinical Trials Repository (CTR) An Update Janus Clinical Trials Repository (CTR) An Update Armando Oliva, M.D. Associate Director for Informatics CDER Office of Computational Science U.S. Food and Drug Administration 2015-03-16 The views expressed

More information

Data Standards Panel Discussion November 30, 2011

Data Standards Panel Discussion November 30, 2011 Data Standards Panel Discussion November 30, 2011 1 Data Standards Panel Discussion Panel Members Chuck Cooper, MD, CDER, FDA Margaret Haber, National Cancer Institute, NIH Dana Pinchotti, American College

More information

Current Status and Future Perspectives for Systemization of Clinical Study related the issues of CDISC in USA and other

Current Status and Future Perspectives for Systemization of Clinical Study related the issues of CDISC in USA and other Current Status and Future Perspectives for Systemization of Clinical Study related the issues of CDISC in USA and other ABSTRACT The term "the CDISC standard" has been used incorrectly for a few years.

More information

Medical Decision Logic, Inc.

Medical Decision Logic, Inc. Medical Decision Logic, Inc. mdlogix Registries and Health Science: Applied Health Informatics Presentation Plan Mission, Goals, and Vision Theoretical Foundation (models) Pragmatic Foundation (cases)

More information

Telling the Data Story: Use of Informatics, Harmonized Semantics and Metadata in the National Children s Study

Telling the Data Story: Use of Informatics, Harmonized Semantics and Metadata in the National Children s Study Telling the Data Story: Use of Informatics, Harmonized Semantics and Metadata in the National Children s Study John Lumpkin, MS, MBA, PMP Steven Hirschfeld, MD, PhD NIH-NICHD-National Children s Study

More information

4. Executive Summary of Part 1 FDA Overview of Current Environment

4. Executive Summary of Part 1 FDA Overview of Current Environment Public Meeting Regulatory New Drug Review: Solutions for Study Data Exchange Standards 1. Background Meeting Summary Food and Drug Administration White Oak, MD November 5, 2012 10am 4pm On November 5,

More information

Clinical Trials: The Crux of Cancer Innovation

Clinical Trials: The Crux of Cancer Innovation Clinical Trials: The Crux of Cancer Innovation Even as medical science is transforming cancer care, major deficiencies in the way cancer clinical trials are designed, carried out, regulated and funded

More information

Accenture Accelerated R&D Services: CDISC Conversion Service Overview

Accenture Accelerated R&D Services: CDISC Conversion Service Overview Accenture Life Sciences Rethink Reshape Restructure for better patient outcomes Accenture Accelerated R&D Services: CDISC Conversion Service Overview Using standards to drive speed to market and meet regulatory

More information

Data Standards and the National Cardiovascular Research Infrastructure (NCRI)

Data Standards and the National Cardiovascular Research Infrastructure (NCRI) Data Standards and the National Cardiovascular Research Infrastructure (NCRI) A partnership with Duke Clinical Research Institute (DCRI) and the American College of Cardiology Foundation (ACCF) November

More information

LEVERAGING COUNTRYWIDE EHRs TO FACILITATE AN INTEGRATED RESEARCH FRAMEWORK Kuttin O 1, Gall W 1

LEVERAGING COUNTRYWIDE EHRs TO FACILITATE AN INTEGRATED RESEARCH FRAMEWORK Kuttin O 1, Gall W 1 LEVERAGING COUNTRYWIDE EHRs TO FACILITATE AN INTEGRATED RESEARCH FRAMEWORK Kuttin O 1, Gall W 1 Abstract Collaboration between clinical care and medical research is essential to meet demands for improvements

More information

PharmaSUG 2016 Paper IB10

PharmaSUG 2016 Paper IB10 ABSTRACT PharmaSUG 2016 Paper IB10 Moving from Data Collection to Data Visualization and Analytics: Leveraging CDISC SDTM Standards to Support Data Marts Steve Kirby, JD, MS, Chiltern, King of Prussia,

More information

How to Increase Site Productivity with a CTMS. Manage financials, meet timelines, increase compliance, and more...

How to Increase Site Productivity with a CTMS. Manage financials, meet timelines, increase compliance, and more... How to Increase Site Productivity with a CTMS Manage financials, meet timelines, increase compliance, and more... By Introduction Clinical trials are essential to the development and safety of new drugs

More information

An Introduction to CDISC: Available CDISC Standards and Models and How SAS Supports These

An Introduction to CDISC: Available CDISC Standards and Models and How SAS Supports These An Introduction to CDISC: Available CDISC Standards and Models and How SAS Supports These Dave Handelsman Principal Strategist, Clinical R&D, SAS October 2005 Copyright 2005, SAS Institute Inc. All rights

More information

The Intelligent Content Framework

The Intelligent Content Framework The Intelligent Content Framework A practical approach to accelerating the Study Design and Regulatory Documentation Development Processes using a Rules-driven, Structured Content Authoring Solution Framework

More information

Clinical Data Management Overview

Clinical Data Management Overview The 2 nd Clinical Data Management Training Clinical Data Management Overview Andrew Taylor ( 安 泰 乐 ), M.S. Head of Clinical Data Management August 30, 2010 Learning Objectives Overview of Process Related

More information

End-to-End E-Clinical Coverage with Oracle Health Sciences InForm GTM

End-to-End E-Clinical Coverage with Oracle Health Sciences InForm GTM End-to-End E-Clinical Coverage with InForm GTM A Complete Solution for Global Clinical Trials The broad market acceptance of electronic data capture (EDC) technology, coupled with an industry moving toward

More information

Therapeutic Area Standards (TAS) Initiative Project Plan

Therapeutic Area Standards (TAS) Initiative Project Plan Therapeutic Area Standards (TAS) Initiative Project Plan Version: 2.0 Document Date: June, 2014 REVISION HISTORY Version Number Revision Date Description of Change 1.0 September, 2013 Initial Document

More information

The Development of the Clinical Trial Ontology to standardize dissemination of clinical trial data. Ravi Shankar

The Development of the Clinical Trial Ontology to standardize dissemination of clinical trial data. Ravi Shankar The Development of the Clinical Trial Ontology to standardize dissemination of clinical trial data Ravi Shankar Open access to clinical trials data advances open science Broad open access to entire clinical

More information

Overview of the CDISC Operational Data Model for Clinical Data Acquisition and Archive (based on CDISC DTD 1.1 Final)

Overview of the CDISC Operational Data Model for Clinical Data Acquisition and Archive (based on CDISC DTD 1.1 Final) Overview of the CDISC Operational Data Model for Clinical Data Acquisition and Archive (based on CDISC DTD 1.1 Final) Copyright 2002 CDISC April 26, 2002 History and Background Historically there has been

More information

The REUSE project: EHR as single datasource for biomedical research

The REUSE project: EHR as single datasource for biomedical research The REUSE project: EHR as single datasource for biomedical research Naji El Fadly 1,3, Noël Lucas 2, Pierre-Yves Lastic 4, François Macary 5, Philippe Verplancke 6, Christel Daniel 1,2 1 INSERM UMRS 872,

More information

The Importance of Good Clinical Data Management and Statistical Programming Practices to Reproducible Research

The Importance of Good Clinical Data Management and Statistical Programming Practices to Reproducible Research The Importance of Good Clinical Data Management and Statistical Programming Practices to Reproducible Research Eileen C King, PhD Research Associate Professor, Biostatistics Acting Director, Data Management

More information

COMMITTEE FOR MEDICINAL PRODUCTS FOR HUMAN USE (CHMP) GUIDELINE ON DATA MONITORING COMMITTEES

COMMITTEE FOR MEDICINAL PRODUCTS FOR HUMAN USE (CHMP) GUIDELINE ON DATA MONITORING COMMITTEES European Medicines Agency Pre-authorisation Evaluation of Medicines for Human Use London, 27 July 2005 Doc. Ref. EMEA/CHMP/EWP/5872/03 Corr COMMITTEE FOR MEDICINAL PRODUCTS FOR HUMAN USE (CHMP) GUIDELINE

More information

Prospect of ICT Utilization at Core Clinical Research Hospitals

Prospect of ICT Utilization at Core Clinical Research Hospitals Prospect of ICT Utilization at Core Clinical Research Hospitals Koki Akahori One of Fujitsu s endeavors in healthcare is to develop coordinated solutions for medicine and pharmaceuticals, and is focusing

More information

End-to-End Management of Clinical Trials Data

End-to-End Management of Clinical Trials Data End-to-End Management of Clinical Trials Data A Revolutionary Step Toward Supporting Clinical Trials Analysis Over the Next Decades of Clinical Research WHITE PAPER SAS White Paper Table of Contents Introduction....

More information

Advancing research: a physician s guide to clinical trials

Advancing research: a physician s guide to clinical trials Advancing research: a physician s guide to clinical trials Recruiting and retaining trial participants is one of the greatest obstacles to developing the next generation of Alzheimer s treatments Alzheimer

More information

Automate Data Integration Processes for Pharmaceutical Data Warehouse

Automate Data Integration Processes for Pharmaceutical Data Warehouse Paper AD01 Automate Data Integration Processes for Pharmaceutical Data Warehouse Sandy Lei, Johnson & Johnson Pharmaceutical Research and Development, L.L.C, Titusville, NJ Kwang-Shi Shu, Johnson & Johnson

More information

Needs, Providing Solutions

Needs, Providing Solutions Identifying Needs, Providing Solutions 1 I n d u s t r y The growth of medical research and the countless innovations coming from the pharmaceutical, biotechnology and medical device industry, has improved

More information

PharmaSUG 2013 - Paper IB05

PharmaSUG 2013 - Paper IB05 PharmaSUG 2013 - Paper IB05 The Value of an Advanced Degree in Statistics as a Clinical Statistical SAS Programmer Mark Matthews, inventiv Health Clinical, Indianapolis, IN Ying (Evelyn) Guo, PAREXEL International,

More information

Implementation and Operation of CDISC ODM-based EDC by UMIN

Implementation and Operation of CDISC ODM-based EDC by UMIN Implementation and Operation of CDISC ODM-based EDC by UMIN Takahiro Kiuchi, M.D., Ph.D. UMIN Center, The University of Tokyo Hospital, Tokyo, Japan 1 Content 1. CDISC standards and academic research 2.

More information

Paper DM10 SAS & Clinical Data Repository Karthikeyan Chidambaram

Paper DM10 SAS & Clinical Data Repository Karthikeyan Chidambaram Paper DM10 SAS & Clinical Data Repository Karthikeyan Chidambaram Cognizant Technology Solutions, Newbury Park, CA Clinical Data Repository (CDR) Drug development lifecycle consumes a lot of time, money

More information

Increasing Development Knowledge with EPFC

Increasing Development Knowledge with EPFC The Eclipse Process Framework Composer Increasing Development Knowledge with EPFC Are all your developers on the same page? Are they all using the best practices and the same best practices for agile,

More information

The CDISC Healthcare Link Initiative

The CDISC Healthcare Link Initiative Value Proposition The CDISC Healthcare Link Initiative Spontaneous Triggered Adverse Drug Event Reporting (ASTER) In 2008, a pilot project was launched between CDISC, CRIX, Pfizer, Brigham and Women s

More information

Kentucky Lung Cancer Research Program. 2010 Strategic Plan Update

Kentucky Lung Cancer Research Program. 2010 Strategic Plan Update Kentucky Lung Cancer Research Program 2010 Strategic Plan Update Approved by the KLCR Program Governance Board August 12, 2009 KLCR Program Strategic Plan Table of Contents Introduction... 3 GOAL 1: Investigator-Initiated

More information

Challenges and Opportunities in Clinical Trial Data Processing

Challenges and Opportunities in Clinical Trial Data Processing Challenges and Opportunities in Clinical Trial Data Processing Vadim Tantsyura, Olive Yuan, Ph.D. Sergiy Sirichenko (Regeneron Pharmaceuticals, Inc., Tarrytown, NY) PG 225 Introduction The review and approval

More information

The NIH Roadmap: Re-Engineering the Clinical Research Enterprise

The NIH Roadmap: Re-Engineering the Clinical Research Enterprise NIH BACKGROUNDER National Institutes of Health The NIH Roadmap: Re-Engineering the Clinical Research Enterprise Clinical research is the linchpin of the nation s biomedical research enterprise. Before

More information

Management and Administration of SNOMED CT as a part of an Interdisciplinary Terminology for Health and Social Care

Management and Administration of SNOMED CT as a part of an Interdisciplinary Terminology for Health and Social Care Management and Administration of SNOMED CT as a part of an Interdisciplinary Terminology for Health and Social Care 1 By all means, quote the National Board of Health and Welfare's reports, but remember

More information

Use of Metadata to Automate Data Flow and Reporting. Gregory Steffens Novartis PhUSE 13 June 2012

Use of Metadata to Automate Data Flow and Reporting. Gregory Steffens Novartis PhUSE 13 June 2012 Use of Metadata to Automate Data Flow and Reporting Gregory Steffens Novartis PhUSE 13 June 2012 Stages of Metadata Evolution I In the beginning... No corporate or industry level data or reporting standards

More information

CLINICAL DEVELOPMENT OPTIMIZATION

CLINICAL DEVELOPMENT OPTIMIZATION PAREXEL CLINICAL RESEARCH SERVICES CLINICAL DEVELOPMENT OPTIMIZATION Enhancing the clinical development process to achieve optimal results ADVANCED TECHNOLOGY COMBINED WITH INTELLIGENT THINKING CAN HELP

More information

CDISC Roadmap Outline: Further development and convergence of SDTM, ODM & Co

CDISC Roadmap Outline: Further development and convergence of SDTM, ODM & Co CDISC Roadmap Outline: Further development and convergence of SDTM, ODM & Co CDISC Ausblick: Weitere Entwicklung und Konvergenz der CDISC-Standards SDTM, ODM & Co. Jozef Aerts - XML4Pharma Disclaimer Views

More information

Basic Unified Process: A Process for Small and Agile Projects

Basic Unified Process: A Process for Small and Agile Projects Basic Unified Process: A Process for Small and Agile Projects Ricardo Balduino - Rational Unified Process Content Developer, IBM Introduction Small projects have different process needs than larger projects.

More information

Precision Medicine Challenge Centralized Pharmacogenomic Recruitment Database

Precision Medicine Challenge Centralized Pharmacogenomic Recruitment Database Precision Medicine Challenge Centralized Pharmacogenomic Recruitment Database March 13, 2016 Table of Contents Key Proposal Elements Strategic Considerations Page 2 Key Proposal Elements Current Trial

More information

Transforming CliniCal Trials: The ability to aggregate and Visualize Data Efficiently to make impactful Decisions

Transforming CliniCal Trials: The ability to aggregate and Visualize Data Efficiently to make impactful Decisions : The ability to aggregate and Visualize Data Efficiently to make impactful Decisions www.eclinicalsol.com White Paper Table of Contents Maximizing Your EDC Investment... 3 Emerging Trends in Data Collection...

More information

A Guide to Clinical Trials

A Guide to Clinical Trials A Guide to Clinical Trials For young people with cancer and their parents Children s Cancer and Leukaemia Group www.cclg.org.uk Original booklet produced in conjunction with the CCLG Patient Advocacy Committee.

More information

Providing Regulatory Submissions In Electronic Format Standardized Study Data

Providing Regulatory Submissions In Electronic Format Standardized Study Data Providing Regulatory Submissions In Electronic Format Standardized Study Data Guidance for Industry U.S. Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation

More information

Participating in Alzheimer s Disease Clinical Trials and Studies

Participating in Alzheimer s Disease Clinical Trials and Studies Participating in Alzheimer s Disease Clinical Trials and Studies FACT SHEET When Margaret was diagnosed with earlystage Alzheimer s disease at age 68, she wanted to do everything possible to combat the

More information

Training/Internship Brochure Advanced Clinical SAS Programming Full Time 6 months Program

Training/Internship Brochure Advanced Clinical SAS Programming Full Time 6 months Program Training/Internship Brochure Advanced Clinical SAS Programming Full Time 6 months Program Domain Clinical Data Sciences Private Limited 8-2-611/1/2, Road No 11, Banjara Hills, Hyderabad Andhra Pradesh

More information

Introduction. The Evolution of the Data Management Role: The Clinical Data Liaison

Introduction. The Evolution of the Data Management Role: The Clinical Data Liaison Introduction The CDL is a new role that will become a standard in the industry for companies that want to make more efficient use of limited resources: time and money. A CDL is key in that he or she conducts

More information

Trials and Tribulations of SDTM Trial Design

Trials and Tribulations of SDTM Trial Design PharmaSUG 2011 - Paper CD13 Trials and Tribulations of SDTM Trial Design Fred Wood, Octagon Research Solutions, Wayne, PA Mary Lenzen, Octagon Research Solutions, Wayne, PA ABSTRACT An increasing number

More information

UTILIZING CDISC STANDARDS TO DRIVE EFFICIENCIES WITH OPENCLINICA Mark Wheeldon CEO, Formedix Boston June 21, 2013

UTILIZING CDISC STANDARDS TO DRIVE EFFICIENCIES WITH OPENCLINICA Mark Wheeldon CEO, Formedix Boston June 21, 2013 UTILIZING CDISC STANDARDS TO DRIVE EFFICIENCIES WITH OPENCLINICA Mark Wheeldon CEO, Formedix Boston June 21, 2013 AGENDA Introduction Real World Uses : Saving Time & Money. Your Clinical Trials Automated.

More information

Roadmap for study startup

Roadmap for study startup How-To Guide Roadmap for study startup Deploying Adobe technology to automate clinical study startup procedures Section 1: Introduction and overview 2 1.1 Introduction 2 1.2 Overview of the clinical study

More information

An Ontology-based Architecture for Integration of Clinical Trials Management Applications

An Ontology-based Architecture for Integration of Clinical Trials Management Applications An Ontology-based Architecture for Integration of Clinical Trials Management Applications Ravi D. Shankar, MS 1, Susana B. Martins, MD, MSc 1, Martin O Connor, MSc 1, David B. Parrish, MS 2, Amar K. Das,

More information

Streamlining the Flow of Clinical Trial Data: EHR to EDC to Sponsor

Streamlining the Flow of Clinical Trial Data: EHR to EDC to Sponsor Streamlining the Flow of Clinical Trial : EHR to EDC to Sponsor Landen Bain Liaison to Healthcare CDISC Interchange Standards Consortium) Jane Griffin, RPh Director, Pharmaceutical Research Cerner Corporation

More information

April 3, 2015. Dear Dr. DeSalvo:

April 3, 2015. Dear Dr. DeSalvo: April 3, 2015 Karen DeSalvo, MD, MPH, MSc National Coordinator for Health Information Technology Office of the National Coordinator for Health Information Technology U.S. Department of Health and Human

More information

CDISC and IHE P R O U D LY P R E S E N T

CDISC and IHE P R O U D LY P R E S E N T New Directions Life Sciences Bridging to Healthcare The Clinical Data Interchange Standards Consortium (CDISC) is leading a fi rst-of-its-kind demonstration to prototype the bridging of healthcare data

More information

Global Policy on Interactions with Healthcare Professionals

Global Policy on Interactions with Healthcare Professionals Global Policy on Interactions with Healthcare Professionals Global Policy on Interactions with Healthcare Professionals Pfizer is committed to collaborating with physicians and other healthcare professionals,

More information

Care Management and Health Records Domain Technical Committee

Care Management and Health Records Domain Technical Committee July 8, 2009 Version 2.5 HITSP Summary Documents Using HL7 Continuity of Care Document (CCD) Component HITSP/C32 Submitted to: Healthcare Information Technology Standards Panel Submitted by: Care Management

More information

PharmaSUG2010 - Paper HS01. CDASH Standards for Medical Device Trials: CRF Analysis. Parag Shiralkar eclinical Solutions, a Division of Eliassen Group

PharmaSUG2010 - Paper HS01. CDASH Standards for Medical Device Trials: CRF Analysis. Parag Shiralkar eclinical Solutions, a Division of Eliassen Group PharmaSUG2010 - Paper HS01 CDASH Standards for Medical Device Trials: CRF Analysis Parag Shiralkar eclinical Solutions, a Division of Eliassen Group Jennie Tedrow Boston Scientific Kit Howard Kestrel Consultants

More information

Life Sciences and Analytics SAS 2.0

Life Sciences and Analytics SAS 2.0 Life Sciences and Analytics SAS 2.0 Dave Handelsman Business Solutions Manager, SAS Life Sciences and Analytics SAS 1.0 Capture data Raw data sets Develop, test and apply SAS programs Extracted data sets

More information

V3 Technical Editorial Services. For HL7 Contract Work Announcement V3 Technical Editor

V3 Technical Editorial Services. For HL7 Contract Work Announcement V3 Technical Editor 1 1 1 1 1 1 1 1 0 1 0 1 V Technical Editorial Services For HL Contract Work Announcement V Technical Editor RIM Document Editorial Assessment June 00 Ockham Information Services LLC 0 Adams Street Decatur,

More information

Voluntary Genomic Data Submissions at the U.S. FDA

Voluntary Genomic Data Submissions at the U.S. FDA Voluntary Genomic Data Submissions at the U.S. FDA International Conference on Harmonization Chicago, IL November 9-10, 9 2005 Felix W. Frueh, PhD Associate Director for Genomics Office of Clinical Pharmacology

More information

Re: Docket No. FDA 2014 N 0339: Proposed Risk-Based Regulatory Framework and Strategy for Health Information Technology Report; Request for Comments

Re: Docket No. FDA 2014 N 0339: Proposed Risk-Based Regulatory Framework and Strategy for Health Information Technology Report; Request for Comments Leslie Kux Assistant Commissioner for Policy Food and Drug Administration Division of Docket Management (HFA 305) Food and Drug Administration 5630 Fishers Lane, Rm. 1061 Rockville, MD 20852 Re: Docket

More information

PONTE Presentation CETIC. EU Open Day, Cambridge, 31/01/2012. Philippe Massonet

PONTE Presentation CETIC. EU Open Day, Cambridge, 31/01/2012. Philippe Massonet PONTE Presentation CETIC Philippe Massonet EU Open Day, Cambridge, 31/01/2012 PONTE Description Efficient Patient Recruitment for Innovative Clinical Trials of Existing Drugs to other Indications Start

More information

EHR Standards Landscape

EHR Standards Landscape EHR Standards Landscape Dr Dipak Kalra Centre for Health Informatics and Multiprofessional Education (CHIME) University College London d.kalra@chime.ucl.ac.uk A trans-national ehealth Infostructure Wellness

More information

ADaM Implications from the CDER Data Standards Common Issues and SDTM Amendment 1 Documents Sandra Minjoe, Octagon Research Solutions, Wayne, PA

ADaM Implications from the CDER Data Standards Common Issues and SDTM Amendment 1 Documents Sandra Minjoe, Octagon Research Solutions, Wayne, PA ABSTRACT: ADaM Implications from the CDER Data Standards Common Issues and SDTM Amendment 1 Documents Sandra Minjoe, Octagon Research Solutions, Wayne, PA Over the past few years, the United States Food

More information

EMEA RM DRAFT GUIDANCE ISPE RESPONSE 1

EMEA RM DRAFT GUIDANCE ISPE RESPONSE 1 EMEA RM DRAFT GUIDANCE ISPE RESPONSE 1 October 4, 2005 Guideline on Risk Management Systems for Medicinal Products for Human Use DRAFT London, 6 September 2005. This guideline will be included as chapter

More information

ABSTRACT INTRODUCTION THE MAPPING FILE GENERAL INFORMATION

ABSTRACT INTRODUCTION THE MAPPING FILE GENERAL INFORMATION An Excel Framework to Convert Clinical Data to CDISC SDTM Leveraging SAS Technology Ale Gicqueau, Clinovo, Sunnyvale, CA Marc Desgrousilliers, Clinovo, Sunnyvale, CA ABSTRACT CDISC SDTM data is the standard

More information

JOURNAL OF OBJECT TECHNOLOGY

JOURNAL OF OBJECT TECHNOLOGY JOURNAL OF OBJECT TECHNOLOGY Online at www.jot.fm. Published by ETH Zurich, Chair of Software Engineering JOT, 2006 Vol. 5. No. 8, November-December 2006 Requirements Engineering Tasks Donald Firesmith,

More information

Effective Health Care Program

Effective Health Care Program Effective Health Care Program Research Reports Number 40 Registry of Patient Registries (RoPR): Project Overview Richard E. Gliklich, M.D. Daniel Levy, M.S. Jannette Karl, M.B.A., P.M.P. Michelle B. Leavy,

More information

The Future of Clinical Data in Clinical Research

The Future of Clinical Data in Clinical Research The Future of Clinical Data in Clinical Research Rebecca D. Kush, PhD President & CEO, CDISC SBMF International Course on Clinical Research, Brazil 1 November 2008 What if. mobile devices were used regularly

More information

Medical Informatic Basics for the Cancer Registry

Medical Informatic Basics for the Cancer Registry Medical Informatic Basics for the Cancer Registry DEVELOPED BY: THE NCRA EDUCATION FOUNDATION AND THE NCRA CANCER INFORMATICS COMMITTEE Medical Informatics is the intersection of science, computer science

More information

Business & Decision Life Sciences What s new in ADaM

Business & Decision Life Sciences What s new in ADaM Business & Decision Life Sciences What s new in ADaM Gavin Winpenny 23 rd June 2015 Agenda What s happening CDISC and Regulatory Submission Landscape ADaM Implementation Guide ADaM Data Structures for

More information

Priority Program Translational Oncology Applicants' Guidelines

Priority Program Translational Oncology Applicants' Guidelines Stiftung Deutsche Krebshilfe Dr. h.c. Fritz Pleitgen Präsident Spendenkonto Kreissparkasse Köln IBAN DE65 3705 0299 0000 9191 91 BIC COKSDE33XXX Priority Program Translational Oncology Applicants' Guidelines

More information

What We Are..! www.ardent-cro.com

What We Are..! www.ardent-cro.com Your Trusted CRO! Regus, Level-2, Connaught Place, Bund Garden Road, Pune-411001, MH, India. Phone: 020-65-31-31-71 Email: ardent@ardent-cro.com Web: What We Are..! Ardent Clinical Research Services is

More information

TIBCO Spotfire Helps Organon Bridge the Data Gap Between Basic Research and Clinical Trials

TIBCO Spotfire Helps Organon Bridge the Data Gap Between Basic Research and Clinical Trials TIBCO Spotfire Helps Organon Bridge the Data Gap Between Basic Research and Clinical Trials Pharmaceutical leader deploys TIBCO Spotfire enterprise analytics platform across its drug discovery organization

More information

Gregory S. Nelson ThotWave Technologies, Cary, North Carolina

Gregory S. Nelson ThotWave Technologies, Cary, North Carolina Using SAS 9 in Clinical Research Gregory S. Nelson ThotWave Technologies, Cary, North Carolina Abstract For 30 years SAS has been used in pharmaceutical research settings for data management, analytics

More information

Global regulatory affairs role in the biopharmaceutical industry

Global regulatory affairs role in the biopharmaceutical industry CHAPTER TWO Global affairs role in the biopharmaceutical industry 2.1 Overview 2.2 Global affairs organization 2.3 Role of global affairs 2.4 Key functions and activities 2.5 Global strategy 2.6 Global

More information

Integrated Clinical Data with Oracle Life Sciences Applications. An Oracle White Paper October 2006

Integrated Clinical Data with Oracle Life Sciences Applications. An Oracle White Paper October 2006 Integrated Clinical Data with Oracle Life Sciences Applications An Oracle White Paper October 2006 Integrated Clinical Data with Oracle Life Sciences Applications EXECUTIVE OVERVIEW Even the largest pharmaceutical

More information

The American Academy of Ophthalmology Adopts SNOMED CT as its Official Clinical Terminology

The American Academy of Ophthalmology Adopts SNOMED CT as its Official Clinical Terminology The American Academy of Ophthalmology Adopts SNOMED CT as its Official Clinical Terminology H. Dunbar Hoskins, Jr., M.D., P. Lloyd Hildebrand, M.D., Flora Lum, M.D. The road towards broad adoption of electronic

More information

EURORDIS-NORD-CORD Joint Declaration of. 10 Key Principles for. Rare Disease Patient Registries

EURORDIS-NORD-CORD Joint Declaration of. 10 Key Principles for. Rare Disease Patient Registries EURORDIS-NORD-CORD Joint Declaration of 10 Key Principles for Rare Disease Patient Registries 1. Patient Registries should be recognised as a global priority in the field of Rare Diseases. 2. Rare Disease

More information