Welcome! |
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Interested in joining one of the Data Transparency Working Group Projects? The projects below are currently calling for volunteers. |
Developing Predictive Models to Facilitate Interpretation of Toxicology Study Results – Started Q2 2024 | |
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Project Scope: A computational pipeline to build models to predict target organs of toxicity from SEND datasets has been developed and published on GitHub under PHUSE. Project team members will evaluate the feasibility and performance of this pipeline when run on data from within their organisations. The pipeline will be updated to improve compatibility with different database systems, and efforts will be made to improve its performance across disparate data sources. Additional study interpretations – e.g. adversity of findings, NOAEL determination, clinical translatability, structure activity relationship – will be explored for development of predictive models. Successful modeling approaches will be published in peer-reviewed scientific journal articles. | Current Status:
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Nonclinical Study Data Reviewer's Guide – Started Q1 2019 | |
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Project Scope: This project is to evolve the Nonclinical Study Data Reviewer's Guide (nSDRG), based on comments from a public PHUSE review, plus to adapt it to updates of the FDA Technical Conformance Guide. The project continues to check and align with the SDRG template and guide developed by the Optimizing the Use of Data Standards Working Group for clinical studies. Preparation of a Study Data Reviewer’s Guide (SDRG) is recommended as an integral part of a CDISC standards-compliant study data submission. The challenge is to operationalise this new documentation requirement efficiently and effectively. Challenges we seek to answer with this project:
Things we expect to learn along the way:
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Investigating the Use of FHIR in Clinical Research – Started Q | |
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Project Scope: Increasing interest in eSource keeps the issue of data integration between Research Systems (EDC, CTMS, CDMS, etc) and healthcare systems (EHR, etc) as a consistent want for Sponsors of Clinical Investigators and Regulators. Previous efforts to make this a repeatable, scalable solution have not met with wide-scale adoption, for a variety of reasons. Some common historical points of view have included:
Many of these issues are on the path to being resolved; government programs have pushed the adoption and accessibility of electronic health records. In addition, there are a number of stakeholders in the Research Industry that are making the use of healthcare resources a priority for the future; examples include Transcelerate eSource initiative and HL7 Vulcan Accelerator. | Current Status:
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