Patrick Nadolny

An Integrated Data Review Plan streamlines the clinical trial process by eliminating redundant data reviews, establishing clear quality objectives, and minimizing the overall burden of data review. #clinical #clinicaltrials #clinicalresearch #biometrics #statistician #data #healthcare #rbqm #rbm #innovation #sasprogrammers

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How can you use innovative #RWE study designs to enrich your evidence generation and answer your #research questions? France offers a rich health #data ecosystem where you can link different datasets to create robust external comparators, pragmatic trials, #AI, and more. Find out how #IQVIA can help you unlock the potential of #RWD in our new Insights Brief: https://bit.ly/3Ux4CQG

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In today’s fast-paced and constantly changing healthcare landscape, leveraging modern data infrastructure and technologies to stay ahead of the curve is crucial for trusted health solutions. Watch as Sanofi's Head of Customer Master Data Management demonstrates how the global company enabled a Customer 360 Solution in over 50 locations with Master Data Management and data engineering. #mdm #data #dataplatform #datamanagement #masterdata #customerdata https://hubs.ly/Q02WRnQ40

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Key Differences b/w Randomized Clinical Trial (RCT) vs RWE (Real-World Evidence): Learn more about Real World Data: https://lnkd.in/gRGZdJJM Reference: https://lnkd.in/gN2vf6Hp #clinicaltrials #clinicareserach #data #healthcare #innovation #patient #regulatory #india #rct #rwe

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🚀 Generative AI can boost productivity by 7-9% but requires proper integration with #automation for real value. Kris Van den Bergh from Capgemini Belgium explores how AI-driven automation can transform contact centers. #GenAI #CapgeminiBE Read more: https://lnkd.in/ecyFATb7

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What is Clinical Data Science (CDS)? How does it differ from Clinical Data Management (CDM)? Where can I find CDS references? 🤔 If you're asking these questions, the "Clinical Data Science 101" free on-demand webinar is here to demystify what Clinical Data Science is and what it is NOT. Patrick Nadolny, SCDM Chair, leads you through everything you need to know to stay ahead of the evolution from #CDM to #CDS. Tune in today to discover everything about Clinical Data Science and its main drivers. ➡️ https://lnkd.in/ehVqWXWW

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Just came across this insightful article on the state of the CRO industry on Contract Pharma. It's clear that the industry is rapidly evolving with key trends such as decentralized clinical trials, digital transformation, and real-world evidence coming to the fore. It also highlights the importance of strategic partnerships and collaborations for industry growth. It's an exciting time to be part of this dynamic industry. #CRO #PharmaIndustry #ClinicalTrials #DigitalTransformation

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According to Harvard Business Review, only 3% of companies’ data meets basic quality standards, and fragmented data sources are partly to blame. Discover how harmonizing your datasets can decrease operational costs and create more connected customer experiences: https://bit.ly/3yqfpU8 #biopharma #datamanagement #masterdata

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👋 Say goodbye to SDTM double programming headaches and hello to seamless setup phases. Be sure to register for our webinar to learn how SGS has cracked the code with our shortcut to ditching SDTM double programming. Get ready for an exclusive look at SGS's game-changing approach. Register now 👉 https://lnkd.in/gGC56c_W #clinicalresearch #SDTM #clinicaldata

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Streamline Your Clinical Study Reporting with SAS https://lnkd.in/dspdTqta Clinical trials are a cornerstone of medical advancements, but generating comprehensive reports can be a challenge. This blog post dives into how Clinical SAS can streamline your clinical study reporting process. Let us explore:  💁‍♂️ What clinical study reports are and their significance 💁‍♂️ Key ICH E3 requirements for clinical study reporting 💁‍♂️ Best practices for clinical SAS programming Generating high-quality clinical study reporting is essential for regulatory submissions and scientific communication. SAS can help you achieve this efficiently and effectively. #ClinicalResearch #SAS #ClinicalTrialReporting #ClinicalDataManagement

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Excited to share how Copilot AI is revolutionizing query management in Clinical Data Management (CDM)! Enter Copilot AI—a game-changer in this domain. Here’s a closer look at how it’s transforming our processes: Example Use Case: Query Resolution in EDC Systems Traditionally, resolving data queries in Electronic Data Capture (EDC) systems is a time-consuming process, often requiring manual reviews and back-and-forth communication with site staff. Let’s consider a practical scenario: Scenario: Missing Laboratory Values During a clinical trial, a patient’s lab results for a critical biomarker are missing from the EDC system. Normally, this would trigger a manual review process: 1. Identification: A data manager notices the missing values during routine data checks. 2. Communication: The data manager sends a query to the site staff, requesting the missing information. 3. Resolution: The site staff retrieves the data and responds to the query. 4. Verification: The data manager verifies the accuracy and completeness of the received data. With Copilot AI, this process is streamlined significantly: How it Works: 1. Automated Query Identification: Copilot AI continuously monitors incoming data and automatically identifies the missing laboratory values. 2. Prioritization and Suggestion: It prioritizes this query based on the critical nature of the biomarker and suggests possible reasons for the missing data, such as common data entry errors or miscommunications. 3. Real-Time Assistance: Copilot AI provides real-time guidance to the data manager, generating a precise, compliant query to be sent to the site staff. For instance, it might suggest, “Please provide the lab results for biomarker XYZ for patient ID 123, as the values are currently missing from the system.” 4. Automated Follow-Up: If no response is received within a specified timeframe, Copilot AI can automatically send follow-up reminders. Benefits: • Increased Efficiency: Reduces query resolution time by up to 50%, allowing data managers to focus on more complex tasks. In this example, the data manager’s time is saved by automating both the identification and follow-up processes. • Enhanced Accuracy: Minimizes human error with AI-driven suggestions, ensuring that queries are precise and relevant. This leads to more accurate data collection and reduces the risk of missing critical information. • Cost Savings: Accelerates the data cleaning process, reducing overall study timelines and costs. Faster query resolution means quicker data lock and faster study completion. Integrating Copilot AI into our CDM workflows not only improves productivity but also enhances the quality and reliability of our clinical trial data. As we continue to innovate, we’re excited to see how AI will further shape the future of clinical research. #ClinicalDataManagement #AIinHealthcare #CopilotAI #ClinicalTrials #DataIntegrity #Innovation

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Curious about what you might be missing out on? See what makes Advanced Intake powered by LifeSphere NavaX a must-have for #pharmacovigilance. Swipe to discover the unmatched power of Advanced Intake by the numbers. ➡ Schedule a demo to find out how you can realize cost savings and efficiency gains today: https://lnkd.in/euFT-KpH #advancedautomation #pvcaseintake #pharmatech #lifesciences #genai #automation

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RBQM Silence: Every Speaks, less Follows- Why or Why not? Key Factors! #clinicaltrials #clinicalresearch #rbqm #rbm #data #innovation #healthcare #data #biometrics CuMinds Innovations

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🚀 Transforming Drug Discovery: The AI Revolution In the rapidly evolving landscape of pharmaceutical R&D, artificial intelligence (AI) is proving to be a game-changer. A recent published in Drug Discovery Today has highlighted some groundbreaking trends that underscore the potential of AI in revolutionizing drug discovery and development*. Exponential Growth in AI-Driven Discoveries Over the past decade, there has been a significant surge in the number of drugs and vaccines discovered through AI. This growth is not just in numbers but also in the speed with which these discoveries are moving from the lab to clinical trials. AI-native biotech companies, often in collaboration with big pharma, are leading this charge, showcasing an impressive annual growth rate in clinical entries*. Doubling Success Rates One of the most striking findings from the study is the success rate of AI-discovered molecules in Phase I clinical trials, which stands at 80-90%. This is nearly double the historical average*. Such high success rates in early trials are indicative of AI's capability to design molecules with optimal drug-like properties, potentially transforming the economics of drug development. Accelerating Drug Development AI is not only improving success rates but also significantly speeding up the drug discovery process. Traditional methods take approximately 4-6 years to discover new small molecules. With AI, this timeline is dramatically reduced. For instance, a recent example from the industry showed that a drug candidate was developed in just 8 months using AI, compared to the years it would typically take**. The Future is Now As we look to the future, the integration of AI in drug discovery promises not only faster development times and improved success rates but also a potential shift in how we approach complex diseases. With every pharmaceutical giant now investing in AI, the next decade could see a dramatic transformation in how new therapies are developed, tested, and brought to market. Call to Action For those of us in the life sciences sector, the message is clear: embracing AI is no longer optional but a necessity to stay competitive and lead in innovation. The opportunities to improve patient outcomes and reduce development costs are immense and within our grasp. Let's discuss how we can further integrate AI into our strategies to not only keep up with the pace of innovation but to set new benchmarks in drug discovery and development also with tools such as our #AIDDISON solution #Digital #AI #ArtificialIntelligence #DrugDiscovery #DrugDevelopment #Technology #Innovation #creativity #futurism https://lnkd.in/gdrdCNfC * https://lnkd.in/gbaiwB4X ** https://lnkd.in/gfF2kuAk

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Transforming Data for SDTM/ADaM and TFLs In #clinicaltrials, #biostatisticians and statistical programmers are pivotal in transforming raw data into standardized formats like #SDTM (Study Data Tabulation Model) and #ADaM (Analysis Data Model) to meet regulatory standards and ensure consistent analysis across studies. They also develop programs to create #TFLs (tables, listings, and figures), crucial for effectively communicating study results to stakeholders such as researchers and regulatory bodies. This meticulous process, executed during dry-run and production phases, is essential for precise data presentation and informed decision-making in healthcare and drug development. Clinixir, Thailand’s leading contract research organization, offers comprehensive clinical research solutions for medical innovations. ✉️ [email protected] 🌐 www.clinixir.com

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Developing Clinical Analytics Solution? Understanding Role-Specific Challenges to Drive Analytics and Technology Solutions! Identifying and addressing the pain points of individuals involved in clinical trials is paramount to the development of effective analytics solutions and technology platforms. By understanding the unique challenges faced by each role, we can create tools that streamline processes, improve efficiency, and enhance decision-making. CuMinds Innovations #clinicaltrials #clinicaldatamanagement #clinicalresearch #data #biometrics #innovation #technology #healthcare #patient

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IQVIA Intelligent Document Review achieved 99% accuracy in key sets of documents while reducing processing time by more than 50% compared to the manual eTMF approach. Learn how: https://bit.ly/3WSkH5a #eTMF #ClinicalTrials #DocumentReview

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Transform your clinical trials with this insightful guide on implementing an electronic Trial Master File (#eTMF) system. 🖥️ Discover the essential steps to successfully navigate the digital transformation journey and streamline document management in your trials. https://hubs.li/Q02tRCg20 Interested in learning about our eTMF solution? Read more here: https://hubs.li/Q02tRwPp0 #CTMS #eTMF #EDC #RTSM #Safety #PV #Pharmaceutical #Biotechnology #MedicalDevices #Diagnostics #Cloudbyz #ClinicalTrials #Salesforce Salesforce

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