Journal of the Society for Clinical Data Management最新文献

{"title":"CDISC Implementation in an Academic Research Organization","authors":"Katie Jentoft, E. Tustison, H. Yu","doi":"10.47912/jscdm.164","DOIUrl":"https://doi.org/10.47912/jscdm.164","url":null,"abstract":"The FDA requirement for standardized data submissions has led us to use CDISC standards in clinical trials since January 2018. In our initial experience as an Academic Research Organization, we applied SDTM conversion to datasets after database lock. This presented challenges when trying to meet data standardization requirements not considered in our initial case report form design. In subsequent studies, we used predefined CDASH case report forms and developed original CDASH-compliant forms for disease- and study-specific data collection, easing the production of the final SDTM dataset. Continuing with this approach towards SDTM conversion has allowed us to leverage the Pinnacle 21 data checks to identify and resolve issues on an ongoing basis. This evolution of CDISC implementation enabled us to refine our standardization process to meet FDA requirements, streamlining data collection and overall efficiency of clinical trials. Looking towards the future, we hope to support collaborations to develop additional CDISC open-source educational resources and examples to improve the standardization process for all.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128808561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electronic Submission and Utilization of CDISC Standardized Clinical Study Data in Japan","authors":"Y. Ando","doi":"10.47912/jscdm.212","DOIUrl":"https://doi.org/10.47912/jscdm.212","url":null,"abstract":"In Japan, the submission of subject-level electronicclinical study data for new drug applications began on October 1, 2016, with a transitionalperiod. The transitional period expired on March 31, 2020, and currently, mostnew drug applications (NDAs) require the submission of electronic clinicalstudy data, which are considered important to provide information about a drugat the review and are required by the Pharmaceuticals and Medical DevicesAgency (PMDA). Standardization of submitted electronic clinical study datais essential to review using data analyses for applications of various drugssubmitted by multiple companies with limited review time and human resources.For most clinical trials and analyses, the PMDA requires clinical trial data tobe submitted in accordance with CDISC standards.This paper provides an overview of the advanced review with electronicdata projectand the current state of electronic data submission in Japan, as well asin terms of future expectations for the data standards, as based upon theexperiences of receiving and utilizing CDISC-compliant clinical study data inthe PMDA.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"10 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129436716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The United States Food Drug Administration’s Innovative Alternative Tools to Evaluate Good Clinical Practice During the COVID-19 Public Health Emergency","authors":"Kassa Ayalew, Jenn W. Sellers, Phillip D. Kronstein, Laurie Muldowney, Emily Gebbia, Jean Mulinde, David Burrow","doi":"10.47912/jscdm.216","DOIUrl":"https://doi.org/10.47912/jscdm.216","url":null,"abstract":"BackgroundThe COVID-19 public health emergency limited the U.S. Food and Drug Administration’s ability to conduct on-site good clinical practice (GCP) inspections. Alternative tools therefore have been used by FDA during the pandemic to evaluate the reliability and integrity of clinical trial data for marketing applications. However, no systematic assessment of the pandemic impact on in-person GCP inspections has been conducted. In addition, the alternative tools and their contribution to GCP oversight have not been reported.   MethodsThis retrospective study reviewed databases internal to FDA and identified and characterized alternative tools used in lieu of on-site GCP inspections in fiscal year (FY)*2020 and FY2021. The impact of the pandemic on on-site GCP inspections and the contribution of alternative tools to overall GCP activities** were described. ResultsBetween April 13, 2020, and September 30, 2021, FDA conducted 77 GCP evaluations using alternative tools. Alternative tools were used most commonly for GCP evaluations of non-U.S. clinical investigators in support of mission critical, original New Drug Applications (NDAs). FDA conduced 370 on-site GCP inspections in FY2020 and 451 in FY2021, which represented a 23% and 6% decrease, respectively, compared to the yearly average of 481 on-site GCP inspections in the 5 years preceding the pandemic. The use of alternative tools contributed 10% and 8% to total GCP activities in FY2020 and FY2021, respectively.ConclusionGCP evaluations using alternative tools have played a significant role in GCP activities supporting the review of marketing applications during the COVID-19 public health emergency. KeywordsCOVID-19 pandemic, public health emergency, remote regulatory assessment (RRA), good clinical practice, remote inspection, FDA. *Fiscal year is defined as from October 1 to September 30.**GCP activities in this paper refers to on-site inspections and GCP evaluations using alternative tools conducted by the Office of Regulatory Affairs or the GCP Assessment Branch in the Division of Clinical Compliance Evaluation in the Office of Scientific Investigations in support of marketing applications submitted to the Center for Drug Evaluation and Research at FDA. ","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125261972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maximizing CDISC standards for specification of submission deliverable documents","authors":"J. Iversen","doi":"10.47912/jscdm.126","DOIUrl":"https://doi.org/10.47912/jscdm.126","url":null,"abstract":"CDSIC standards were originally developed for documentation purposes in the form of metadata standards describing submission deliverables. Many tools, vendors, and sponsor efforts have gone into verifying that submission documents adhere to those standards. By turning the beast on its head, the very same metadata can be used to create those submission deliverables from the specifications using validated computer code, thus eliminating the bulk of controls and verification for a study.The core principle is that the task of ensuring that two documents are identical (or similar) by comparing and checking, can be eliminated by creating one from the other in a systematic and automatic way by computer code.ODM-XML is the primary specification document for eCRF derivates from CDISC, a pure XML metadata specification documenting the collection of clinical data, not the actual collected clinical data itself. The corresponding submission deliverables are the blank CRF (bcrf.pdf) and the SDTM annotated CRF (acrf.pdf). A CDISC compliant EDC systems ought to be able to use the ODM-XML itself more or less directly to set the eCRF by a simple upload of the ODM-XML into the systems.Bridging the gap from ODM-XML to submission deliverables is quite simply done by  applying a style sheet (a special translating style sheet) to the ODM-XML file to display it as either an eCRF specification, one of the submission documents, or as another XML file for uploading into a specific EDC system. Whenever the desired document is of the same file format, the same stylesheet can be applied varying only in a specified parameter, guaranteeing the similarity of those documents as they originate from the same source.Define-xml is a well-established standard for documenting submission data. The standard way of displaying define-xml is through a similar style sheet provided by CDISC, containing links into targets in the SDTM annotated CRF (acrf.pdf) document.This article demonstrates how the submission documents can be created through careful definition of the ODM-XML, and applying a style sheet creating targets in the SDTM annotated CRF (acrf.pdf) for enhanced linking between this document and the define-xml document. Furthermore, this technique will demonstrate creation of an SDTM annotated specification for setting up an eCRF, as well as creation of the blank CRF (bcrf.pdf) document, all from a single source of metadata.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"174 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114109594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CDISC ADaM Phases, Periods, and Subperiods: A Case Study","authors":"J. Fulton","doi":"10.47912/jscdm.121","DOIUrl":"https://doi.org/10.47912/jscdm.121","url":null,"abstract":"INTRODUCTION Many clinical studies are comprised simply of Screening, Treatment, and Follow-up time periods. Occasionally the Treatment portion of the study needs to be divided further into analysis periods, and even sub-levels within one or more of the analysis periods, which introduces another layer of complexity when creating CDISC Analysis Data Model (ADaM) data sets. If it is important, for example, to know additional study details when a particular adverse event started, then the ADaM permissible Phase, Period, and Subperiod variables should be utilized.OBJECTIVES This paper will present a case study on an actual clinical trial that had interesting challenges regarding the correct implementation of the ADaM guidelines for these variables. In this study the route of administration was being investigated.  Rather than comparing study drugs, the route changed for each subject from one set of visits to the next.METHODS Topics will include: key ADaM variables that come into play, ADSL variables and how they relate to other ADaM Basic Data Structure (BDS) domain variables, and sample SAS macro code to derive some of the key treatment and timing variables. RESULTS Example data from the case study is displayed to illustrate the proper way to utilize the full set of Phase, Period, and Subperiod variables.  ADSL data is shared, as well as ADVS (vital signs) as an example of a BDS data set.  Additional tips are offered with regard to the Screening Phase, screen failures, tying treatment variables to the Period variables, and challenges when date or time information was not collected.CONCLUSIONS A complicated study design means multiple challenges in adhering to CDISC requirements, especially ADaM data sets.  But with a well thought out plan, and use of the ADaM Implementation Guide to tackle the obstacles piece by piece, the puzzle can come together in the end.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115180359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Making Clinical Data Acquisition Standards Harmonization (CDASH) Electronic Case Report Forms Available on the REDCap Shared Data Instrument Library","authors":"A. Cheng, Rhonda Facile, John Owen, Richard Marshall, K. Mellars, Nan Kennedy, Brenda L. Minor, Kyle Mcguffin, Paul A. Harris","doi":"10.47912/jscdm.172","DOIUrl":"https://doi.org/10.47912/jscdm.172","url":null,"abstract":"Introduction: A guiding principle behind the development and deployment of the REDCap data management platform has always included attention to workflow design that allows easy implementation of best practices for clinical and translational researchers. CDISC standards such as CDASH have helped the clinical research community improve the efficiency, actionability, and quality of their clinical trials data, but have had limited uptake among the academic institutions. Objective: To create a scalable methodology to convert CDISC CDASH eCRF instrument metadata into REDCap data dictionaries for the purpose of simplifying adoption and use of CDASH instruments by research teams across the REDCap Consortium.Results: We have used our replicable methods to translate metadata from 34 CDASH Foundational eCRFs and 20 CDASH Crohn’s Disease eCRFs into REDCap eCRF metadata and have made these instruments available in the REDCap Shared Data Instrument Library for widespread sharing and uptake across the REDCap Consortium. Users can import the standardized eCRFs directly into their REDCap projects for immediate use in clinical trial data collection.Conclusion: Disseminating CDISC standards through the REDCap community will increase the accessibility of these standards for academic medical centers. Having academic clinical researchers using CDISC standards may lead to more research datasets that interoperate with pharmaceutical sponsored trials, and more discoveries from secondary use of clinical research data.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132228335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Note of Special Appreciation to JSCDM’s Peer Reviewers","authors":"R. Ittenbach","doi":"10.47912/jscdm.148","DOIUrl":"https://doi.org/10.47912/jscdm.148","url":null,"abstract":"The Journal of the Society for Clinical Data Management: Informatics and Data Science in Clinical Research (JSCDM) would like to offer a heart-felt thank you to our 27 peer reviewers for 2021.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"86 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132879885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Test","authors":"Melissa A. Kirwin","doi":"10.47912/jscdm.154","DOIUrl":"https://doi.org/10.47912/jscdm.154","url":null,"abstract":"<jats:p>test</jats:p>","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"45 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121004598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Institutional Change in Clinical Trials in the era of the COVID-19 Pandemic","authors":"T. Miyaji, T. Kiuchi, Takuhiro Yamaguchi","doi":"10.47912/jscdm.103","DOIUrl":"https://doi.org/10.47912/jscdm.103","url":null,"abstract":"To understand the current phenomena of conducting clinical trials in the era of the coronavirus disease (COVID-19) and prepare for a change in conduct, it might be worth to understand the phenomena of clinical trials from the perspective of “institutional change”. This short perspective paper will describe the basic concepts of institutions and institutional change and explore expected institutional changes in clinical trials as a result of the coronavirus disease (COVID-19).","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130383687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The implementation of a data learning series focused on clinical development teams in a contract research organization","authors":"S. Medendorp, Allison Crumpler","doi":"10.47912/jscdm.39","DOIUrl":"https://doi.org/10.47912/jscdm.39","url":null,"abstract":"Effective management of a clinical trialrequires having real time access to information that provides useful insightsinto trial progress and that lends itself to collaborative decisionmaking.  Data visualizations using datafrom multiple source systems employed during the conduct of a clinical trialhave become an essential tool in the recent past as support for collaborativedecision making by project teams. Having the ability to access, analyze, read,work with, and present data to support an argument are  important skills that ensure datavisualizations fulfill their purpose in clinical trial management. There is anexpectation that members of the clinical trial team either possess or developthe data literacy skill sets necessary to collaborate on the successfulexecution of a clinical drug development trial. Here we describe thedevelopment of a Data Learning Series program targeted to increase the data literacyskills within a Contract Research Organization in support of the digitalevolution of the drug development industry.","PeriodicalId":440423,"journal":{"name":"Journal of the Society for Clinical Data Management","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131464766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}