#010 Centralized Monitoring: Risk-based Approach to Clinical Trial Processes

#010 Centralized Monitoring: Risk-based Approach to Clinical Trial Processes

#datascience #centralizedmonitoring #clinicaltrials #technologyinpharma #pharmatransformation In this episode, Jennifer Krohn, Associate Director of Risk-Based Quality Management at Gilead Sciences, shares how centralized monitoring is transforming clinical trial oversight, improving data quality, participant safety, and trial efficiency. From statistical tools and open-source innovation to CRA training and AI advancements, Jenn shares what it takes to detect critical data signals earlier, ensure trial integrity, and foster cross-functional collaboration in pharma through the open-source community. Materials shared in the episode: PHUSE RBQM Working Group [https://advance.hub.phuse.global/wiki/spaces/WEL/pages/26804599/Risk+Based+Quality+Management]RBQM Education Project [https://advance.hub.phuse.global/wiki/spaces/WEL/pages/36864002/End+to+End+RBQM+Education] PHUSE CM White Papers: * Centralized Monitoring: Exploring the Considerations and Challenges of Implementation [https://phuse.s3.eu-central-1.amazonaws.com/Deliverables/Risk+Based+Quality+Management/WP-073.pdf] * Can the Value of Centralized Monitoring be Quantified [https://phuse.s3.eu-central-1.amazonaws.com/Deliverables/Risk+Based+Quality+Management/WP-075.pdf] Jennifer Krohn https://www.linkedin.com/in/jenn-krohn/ [https://www.linkedin.com/in/jenn-krohn/]  Nat Chrzanowskahttps://www.linkedin.com/in/nat-chrzanowska/ [https://www.linkedin.com/in/nat-chrzanowska/]  __________________________________________ More about Appsilon: ► https://www.appsilon.com/ [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa0I2S3JBTjJ5M3A5M044cDlHTndkVkFIcmNpQXxBQ3Jtc0ttZWxSN2ZRcEQ4bVFTWnhaSE0zYVJfSW1EazR3QWJ2RkVySktaM1Nfazd5cDJGd1llU0szdkdRazVWb2FGYWRCV0d5bHJEQmtDQVdQSkpROV90dzNqelN5MlNRNWh2R1p5N0RlVDVqaVVvOEh2dzZFWQ&q=https%3A%2F%2Fwisegroup.pl%2F&v=Kr1aNPJVYT0] Appsilon empowers pharmaceutical and life sciences companies to leverage open-source technology for faster, data-driven decision-making in regulated environments. Schedule a free consultation with our expert ► https://www.appsilon.com/contact-us [https://www.appsilon.com/contact-us] _________________________________________ For more insights about how technology helps scientists push the boundaries of data analysis and reporting check out our blog: ► http://appsilon.com/blog [http://appsilon.com/blog]  LinkedIn: https://www.linkedin.com/company/appsilon/ [https://www.linkedin.com/company/appsilon/]

#009 GenAI in Clinical Reporting: Beyond the Buzz, Real Use Cases, and Future Directions

#datascience #genAI #clinicaltrials #clinicalreporting #AIinpharma #GenerativeAI #Roche #AIautomation #pharmaceuticalindustry #AIchallenges #AIbot #chatbots #copilot #codingassistant In this episode, we speak with Vincent Shen, Senior Principal Data Scientist at Roche, about the actual impact of generative AI in clinical data analysis. Vincent shares insights from his work implementing AI-powered tools, such as knowledge chatbots and coding assistants, that support clinical reporting at Roche. We discuss the evolving role of AI, the challenges of integrating it into clinical trial workflows, and the importance of rethinking the processes to  ensure effective AI use.In this episode: * AI will augment rather than replace data scientists in clinical trial workflows. * Roche has successfully deployed a GenAI-powered knowledge bot, saving an estimated 25 hours per 100 questions. * Coding assistants help data science teams accelerate time-to-insight. * Providing detailed specifications is essential for AI to deliver accurate and meaningful results. * Training AI models requires extra effort to ensure they correctly interpret context and domain-specific requirements. * The next big step is to rethink how processes are designed, not just automate existing ones. Vincent Shen https://www.linkedin.com/in/vincent-shen-vs/ [https://www.linkedin.com/in/vincent-shen-vs/]  Nat Chrzanowska https://www.linkedin.com/in/nat-chrzanowska/ [https://www.linkedin.com/in/nat-chrzanowska/]  __________________________________________ More about Appsilon: ► https://www.appsilon.com/ [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa0I2S3JBTjJ5M3A5M044cDlHTndkVkFIcmNpQXxBQ3Jtc0ttZWxSN2ZRcEQ4bVFTWnhaSE0zYVJfSW1EazR3QWJ2RkVySktaM1Nfazd5cDJGd1llU0szdkdRazVWb2FGYWRCV0d5bHJEQmtDQVdQSkpROV90dzNqelN5MlNRNWh2R1p5N0RlVDVqaVVvOEh2dzZFWQ&q=https%3A%2F%2Fwisegroup.pl%2F&v=Kr1aNPJVYT0] Appsilon empowers pharmaceutical and life sciences companies to leverage open-source technology for faster, data-driven decision-making in regulated environments. Schedule a free consultation with our expert ► https://www.appsilon.com/contact-us [https://www.appsilon.com/contact-us]  We design scalable and user-friendly Shiny dashboards to help you make data-driven decisions. ► https://www.appsilon.com/services/data-dashboards [https://www.appsilon.com/services/data-dashboards]  We design and implement Statistical Computing Environment for R and Python for efficient data analysis. ► https://www.appsilon.com/services/sce [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbGFsWVZvTy1YNkRKVVBkMUtjZlF0V3E5NXBJZ3xBQ3Jtc0tuQjZqZVNqM056d2Q0LWdmRE1jNGo3aVVRZnZqbzh4eGpOcHNXRG1KT01zbzNUN1p1MGJqNERTczRzYXhGNDhuQUxwS3M2SVRmSGh4NmxET3U5SGQxWnF2WjBhWFRIQ2g1aFVvTUpMZDVGdHpSTmk3Zw&q=https%3A%2F%2Fadwise.pl%2Fkonsultacja%2F&v=Kr1aNPJVYT0] We design, implement, and optimise data analysis environments so you can focus focus on insights and innovation. ► https://www.appsilon.com/services/platform [https://www.appsilon.com/services/platform] Where Technology Meets Science podcast is available on all podcasting platforms: ► Spotify: https://hubs.li/Q037KddD0 [https://hubs.li/Q037KddD0]  ► Apple Podcasts: https://hubs.li/Q037KlLl0 [https://hubs.li/Q037KlLl0]  ► YouTube: https://hubs.li/Q037Kpth0 [https://hubs.li/Q037Kpth0] __________________________________________ For more insights about how technology helps scientists push the boundaries of data analysis and reporting check out our blog ► http://appsilon.com/blog LinkedIn: https://www.linkedin.com/company/appsilon/ [https://www.linkedin.com/company/appsilon/]

#4 Pharma Brief: Generative AI Advances at FDA, Pharma’s Autonomous Agents, and Open-Source Tools Spotlight

#datascience #dataanalysis #technology #pharmabrief #clinicaltrials #technologyinpharma #pharma #pharmanews Pharma Brief’s fourth edition spotlights generative AI’s rapid expansion across pharma and regulatory landscapes. This issue covers the FDA’s planned rollout of generative AI tools across all centers, including the launch of Elsa to streamline reviews and inspections. We explore Anthropic’s Model Context Protocol as a new standard for context-aware AI, plus pharma’s growing use of autonomous agents in clinical operations and medical writing, with insights from BCG’s latest report.Benchling’s integration of Claude into biotech R&D workflows highlights significant time savings and smarter data management. Catch a recap of the AWS Life Sciences Symposium keynote and FDA’s public call for comments on the CDISC Dataset-JSON standard, which could reshape study data exchange.Open-source tools like {mergen}, {kuzco}, and {cheetahR} are featured to empower your R workflows with AI, computer vision, and blazing-fast data rendering. You can follow Pharma Brief on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/ [https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/] Now also available in audio on your favorite podcast platforms. Links from the episode: FDA’s Generative AI Rollout: https://www.fda.gov/news-events/press-announcements/fda-announces-completion-first-ai-assisted-scientific-review-pilot-and-aggressive-agency-wide-aiBCG [https://www.fda.gov/news-events/press-announcements/fda-announces-completion-first-ai-assisted-scientific-review-pilot-and-aggressive-agency-wide-aiBCG] Report on AI Agents in Pharma: https://www.linkedin.com/posts/bcg-platinion_ai-agents-and-the-model-context-protocol-activity-7330864988070309891-zhCZ [https://www.linkedin.com/posts/bcg-platinion_ai-agents-and-the-model-context-protocol-activity-7330864988070309891-zhCZ] Benchling + Claude Integration: https://www.anthropic.com/customers/benchling [https://www.anthropic.com/customers/benchling] AWS Life Sciences Symposium 2025 & Keynote: https://aws.amazon.com/blogs/industries/7th-annual-aws-life-sciences-symposium/ [https://aws.amazon.com/blogs/industries/7th-annual-aws-life-sciences-symposium/] https://www.youtube.com/watch?v=3hohXZF_3ys  [https://www.youtube.com/watch?v=3hohXZF_3ys] FDA Request for Comments on CDISC Dataset-JSON: https://www.federalregister.gov/documents/2025/04/09/2025-06051/electronic-study-data-submission-data-standards-clinical-data-interchange-standards-consortium [https://www.federalregister.gov/documents/2025/04/09/2025-06051/electronic-study-data-submission-data-standards-clinical-data-interchange-standards-consortium] Open Source Highlights: {muttest} https://github.com/jakubsob/muttest [https://github.com/jakubsob/muttest] {mergen} https://bioinformatics.mdc-berlin.de/mergen/ [https://bioinformatics.mdc-berlin.de/mergen/] gptstudio & gpttools https://github.com/MichelNivard/gptstudio [https://github.com/MichelNivard/gptstudio] {kuzco} https://github.com/frankiethull/kuzco [https://github.com/frankiethull/kuzco] {cheetahR} https://github.com/cynkra/cheetahR [https://github.com/cynkra/cheetahR] Upcoming Events: * AI and SaMD in Healthcare Webinar | 18 June 2025 | Virtual * PHUSE Single Day Event | 21 June 2025 | Hyderabad, India * COSA Spotlight Q2 2025 | 24 June 2025 | Virtual * Value-Driven Clinical Data Review Webinar | 26 June 2025 | Virtual * PSI/PHUSE Change Management Event | 3 July 2025 | Cambridge, UK * PSI Webinar on iRISE Consortium Results | 24 July 2025 | Virtual Open Call for Papers: R/Pharma 2025 https://sessionize.com/rpharma-2025 [https://sessionize.com/rpharma-2025] Subscribe on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/ [https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/]  Nat Chrzanowska https://www.linkedin.com/in/nat-chrzanowska/ [https://www.linkedin.com/in/nat-chrzanowska/]https://www.linkedin.com/in/nat-chrzanowska/__________________________________________ More about Appsilon: ► https://www.appsilon.com/ [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa0I2S3JBTjJ5M3A5M044cDlHTndkVkFIcmNpQXxBQ3Jtc0ttZWxSN2ZRcEQ4bVFTWnhaSE0zYVJfSW1EazR3QWJ2RkVySktaM1Nfazd5cDJGd1llU0szdkdRazVWb2FGYWRCV0d5bHJEQmtDQVdQSkpROV90dzNqelN5MlNRNWh2R1p5N0RlVDVqaVVvOEh2dzZFWQ&q=https%3A%2F%2Fwisegroup.pl%2F&v=Kr1aNPJVYT0] Appsilon empowers pharmaceutical and life sciences companies to leverage open-source technology for faster, data-driven decision-making in regulated environments. Schedule a free consultation with our expert ► https://www.appsilon.com/contact-us [https://www.appsilon.com/contact-us] __________________________________________ For more insights about how technology helps scientists push the boundaries of data analysis and reporting check out our blog: ► http://appsilon.com/blog  [http://appsilon.com/blog] LinkedIn: https://www.linkedin.com/company/appsilon/ [https://www.linkedin.com/company/appsilon/]

#008 Machine Learning Modeling in Neuroscience Clinical Trials Design

#datascience #dataanalysis #technology #machinelearning #clinicaltrials #placebo In this episode, Jing Dai, Director of Biostatistics at Jazz Pharmaceuticals, shares insights from the PHUSE US Connect conference and her work on applying machine learning to neuroscience clinical trials. She discusses challenges like high placebo response and attrition, the value of interdisciplinary collaboration, and how AI/ML can shape trial design, improve regulatory readiness, and move the field toward more objective, data-driven outcomes. In this episode, you will learn: * How machine learning can help address high placebo response and attrition in neuroscience clinical trials. * Why traditional statistical models struggle with high-dimensional clinical data. * Key regulatory frameworks (GxP, GMLP) for ensuring AI/ML models meet compliance standards in drug development. * Practical tips for fostering interdisciplinary collaboration between biostatisticians, clinicians, and data scientists. Nat Chrzanowska https://www.linkedin.com/in/nat-chrzanowska/ [https://www.linkedin.com/in/nat-chrzanowska/] Jing Dai https://www.linkedin.com/in/jingdai1009/ [https://www.linkedin.com/in/jingdai1009/]  __________________________________________ More about Appsilon: ► https://www.appsilon.com/ [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa0I2S3JBTjJ5M3A5M044cDlHTndkVkFIcmNpQXxBQ3Jtc0ttZWxSN2ZRcEQ4bVFTWnhaSE0zYVJfSW1EazR3QWJ2RkVySktaM1Nfazd5cDJGd1llU0szdkdRazVWb2FGYWRCV0d5bHJEQmtDQVdQSkpROV90dzNqelN5MlNRNWh2R1p5N0RlVDVqaVVvOEh2dzZFWQ&q=https%3A%2F%2Fwisegroup.pl%2F&v=Kr1aNPJVYT0] Appsilon empowers pharmaceutical and life sciences companies to leverage open-source technology for faster, data-driven decision-making in regulated environments. Schedule a free consultation with our expert ► https://www.appsilon.com/contact-us [https://www.appsilon.com/contact-us]  __________________________________________ For more insights about how technology helps scientists push the boundaries of data analysis and reporting check out our blog: ► http://appsilon.com/blog [http://appsilon.com/blog]  LinkedIn: https://www.linkedin.com/company/appsilon/ [https://www.linkedin.com/company/appsilon/]

#007 How Open Source and Community Efforts Drive R-Based FDA Submissions

#datascience #dataanalysis #technology #datascience #opensource #pharmaverse #pharma #dataanalysis #clinicaltrials In this episode, Ben Straub, Principal Programmer at GSK, explores the shift from proprietary software to open source tools in the pharmaceutical industry. He shares insights into regulatory challenges, the rise of R, and the impact of {admiral} and other open-source packages on clinical data analysis and submissions. From pilot programs to enterprise-wide adoption, learn why collaboration is key to reducing risk and shaping the future of regulatory workflows. In this episode, you will learn: * Lessons learned from GSK’s open source adoption journey, * How collaboration via pharmaverse, PHUSE, and R Consortium accelerates regulatory submissions * How {admiral} package for ADaM datasets was one of the triggers for widespread open source adoption in pharma * Why R is a dominant language in pharma * What are the next milestones to modernize outdated regulatory standards Webinar about GSK's R Journey: From Pilot Projects to Enterprise Adoption: https://www.youtube.com/watch?v=xDrt6txplek [https://www.youtube.com/watch?v=xDrt6txplek] Admiral package: https://pharmaverse.github.io/admiral/ [https://pharmaverse.github.io/admiral/] __________________________________________ More about Appsilon: ► https://www.appsilon.com/ [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa0I2S3JBTjJ5M3A5M044cDlHTndkVkFIcmNpQXxBQ3Jtc0ttZWxSN2ZRcEQ4bVFTWnhaSE0zYVJfSW1EazR3QWJ2RkVySktaM1Nfazd5cDJGd1llU0szdkdRazVWb2FGYWRCV0d5bHJEQmtDQVdQSkpROV90dzNqelN5MlNRNWh2R1p5N0RlVDVqaVVvOEh2dzZFWQ&q=https%3A%2F%2Fwisegroup.pl%2F&v=Kr1aNPJVYT0] Appsilon empowers pharmaceutical and life sciences companies to leverage open-source technology for faster, data-driven decision-making in regulated environments. Schedule a free consultation with our expert ► https://www.appsilon.com/contact-us [https://www.appsilon.com/contact-us]  __________________________________________ For more insights about how technology helps scientists push the boundaries of data analysis and reporting check out our blog: ► http://appsilon.com/blog [http://appsilon.com/blog]  LinkedIn: https://www.linkedin.com/company/appsilon/ [https://www.linkedin.com/company/appsilon/]