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Navigating Evolving DEI Measures in Clinical Patient Recruitment: A Deep DiveIt is crucial throughout the clinical trials space to understand the challenges and triumphs of DEI.
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AI and Digital Technology in Regulatory SubmissionsA tool-based approach can significantly aid in the harmonization of regulatory requirements, mitigate inadvertent risks, and encourage collaboration by making data sharing more efficient and secure.
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AI/ML Approaches to Assisted Medical Writing—Part 2Following a discussion around summarization in Part 1, Part 2 discusses the method of pure abstraction in light of recent advances in deep learning and AI.
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Clinical Trials and TrustUnderstanding the role of social determinants on clinical trial participation and trust.
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Rethinking ECOG Scores to Improve Patient Access and Clinical Trials EligibilityRecent study results highlight need for new metrics in ECOG scoring to mitigate variability.
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Improving Diversity in Clinical Trial Volunteer Participation by Addressing Racial and Ethnic Representation Among the Clinical Research Workforce2020 Tufts CSDD study examines relationship between investigative site personnel diversity and study participant diversity.
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Adapting Site Selection for Clinical Trial Decentralization and the Future LandscapeSites not expected to fade away even as DCTs continue to grow past COVID-19.
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Sharing Anonymized and Functionally Effective (SAFE) Data Standard for Safely Sharing Rich Clinical Trial DataPresenting how data transformation is measured as part of the SAFE Data Standard, which data variables influence the rating and, how the appropriate level of data transformation is calculated.
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COVID-19 Pandemic Exemplifies the Benefits of CROsThe adaptability and innovative capacity of CROs highlighted in EUCROF survey.
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Breaking Historic Barriers to Ensure Psychedelic Therapy’s FutureEducation and equitable access are key to unlocking its full potential in the present and future.
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Diversity in Clinical Trial Data Transparency: A New Horizon for Data Sharing with Truthful StatisticsThe pursuit of balance between data utility, privacy protection, and equitable representation.
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Real-World Use of an Artificial Intelligence-Supported Solution for Coding of Adverse Events in Clinical TrialsStudy evaluates the use of AI-supported medical coding module.
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COVID-19 Will Have a Heterogeneous Impact on Clinical Trials, BiopharmasA discussion of how the coronavirus pandemic will have a multitude of impacts on the conduct of trials, as well as on the industry itself.
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Establishing the Right Foundation for Patient Safety in 2025How biopharmas are advancing their pharmacovigilance operations.
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Elevating Clinical Research Site Relationships With New Budget and Payment ParadigmsHow a deeper review of site budget and payment processes and technology is driving meaningful change in the industry.
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Diversity in Clinical Trials: Path to Achieving Health EquityBeyond technology, awareness, and access—cultural competence is key.
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Sample Size Re-Estimation as an Adaptive DesignUsing the promising-zone approach can salvage an underpowered trial.
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Clinical Trial Optionality: Its Reality is Within ReachHow advanced ePRO tools and approaches offer a path forward.
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Enhancing eCOA Through AI: A Look Ahead to 2025The three areas poised for a transformation in the advent of electronic clinical outcome assessment technologies.
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How Digital Twins are Driving Sustainability in Clinical Supply PlanningEmerging technologies like digital twins offer supply chain efficiency solutions, allowing the industry to integrate sustainable practices while ensuring patient safety.
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3 Common eCOA Implementation Challenges and How to Solve ThemOvercoming hurdles with licensing complexities, post-production changes, and IRB submissions can help in reducing timelines and increasing collaboration.
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Smart New Normal in Medication Management—Personalized, Integrated, and FlexibleWhat the next generation medication management in clinical trials should entail and insights on smart technologies and synergistic partnerships—backed by real-life implementation use cases.
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Optimizing Patient Recruitment and Engagement StrategiesFive strategies to reduce risk and achieve deadlines.
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Establishing Metrics and Standardization for Non-CRF Data in EDCWhile Case Report Forms are a main contributor to collected data, non-CRF data such as core laboratory data and central imaging can be critical to any clinical study.
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A New Era in Clinical TrialsIndustry challenges present an opportunity for innovation and the adoption of new solutions, particularly in addressing barriers related to patient recruitment, engagement, and retention.
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Artificial Intelligence Drives Industry Response to Project OptimusThe FDA has taken a clear position with Project Optimus in shifting toward more progressive tailored approaches while rejecting antiquated study designs to evolve clinical trial strategies to better align with newer drug classes.
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Case Study: Successful System Integration for Decentralized Clinical Trials endpoint Clinical and THREAD’s Solution Ensures the Successful Flow of eConsent DataToday’s clinical studies are increasingly complex and require patient-centric trial designs, like decentralized trials, more than ever before. As trials incorporate more decentralized components there is an ever-present need for multiple system integrations to support the various trial functions, with the goal being that all trial data flows seamlessly between systems and is stored in one repository for efficient oversight and analysis. These numerous integrated systems require closely managed integration, synchronization, and supportive partnerships to minimize error and maximize efficiency. In this case study, partners endpoint and THREAD dig-in to explore how IRT can be integrated with decentralized clinical trial (DCT) technology, working through tightly integrated workflows, to provide a streamlined process, a better user experience for Sites and Participants, higher quality data and real-time access to information.
Latest:
AI/ML Approaches to Assisted Medical Writing—Part 2Following a discussion around summarization in Part 1, Part 2 discusses the method of pure abstraction in light of recent advances in deep learning and AI.
