🤖🧬 Where Technology Meets Science

Appsilon
🤖🧬 Where Technology Meets Science

Where Science Meets Technology by Appsilon is a series of interviews and discussions focused on how technology can accelerate data science processes, particularly within life sciences and biopharmaceutical companies. Each episode will explore various aspects of innovation and its potential to address challenges where traditional methods may fall short. We will feature internal experts from our delivery teams, along with clients and partners as guest speakers, providing valuable insights into the intersection of science and technology. The podcast is brought to you by Appsilon. Appsilon empowers Fortune 500 companies to leverage open-source technology for faster, data-driven decision-making in regulated environments

  1. #009 GenAI in Clinical Reporting: Beyond the Buzz, Real Use Cases, and Future Directions

    JUN 5

    #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/  Nat Chrzanowska https://www.linkedin.com/in/nat-chrzanowska/  __________________________________________ More about Appsilon: ► https://www.appsilon.com/ 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  We design scalable and user-friendly Shiny dashboards to help you make data-driven decisions. ► 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 We design, implement, and optimise data analysis environments so you can focus focus on insights and innovation. ► https://www.appsilon.com/services/platform Where Technology Meets Science podcast is available on all podcasting platforms: ► Spotify: https://hubs.li/Q037KddD0  ► Apple Podcasts: https://hubs.li/Q037KlLl0  ► YouTube: 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/

    36 min
  2. #4 Pharma Brief: Generative AI Advances at FDA, Pharma’s Autonomous Agents, and Open-Source Tools Spotlight

    JUN 4

    #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/ 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 Report on AI Agents in Pharma: 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 AWS Life Sciences Symposium 2025 & Keynote: https://aws.amazon.com/blogs/industries/7th-annual-aws-life-sciences-symposium/ 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 Open Source Highlights: {muttest} https://github.com/jakubsob/muttest {mergen} 

https://bioinformatics.mdc-berlin.de/mergen/ gptstudio & gpttools https://github.com/MichelNivard/gptstudio {kuzco} 
https://github.com/frankiethull/kuzco {cheetahR} https://github.com/cynkra/cheetahR Upcoming Events: AI and SaMD in Healthcare Webinar | 18 June 2025 | VirtualPHUSE Single Day Event | 21 June 2025 | Hyderabad, IndiaCOSA Spotlight Q2 2025 | 24 June 2025 | VirtualValue-Driven Clinical Data Review Webinar | 26 June 2025 | VirtualPSI/PHUSE Change Management Event | 3 July 2025 | Cambridge, UKPSI Webinar on iRISE Consortium Results | 24 July 2025 | Virtual Open Call for Papers: R/Pharma 2025 https://sessionize.com/rpharma-2025 Subscribe on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/  Nat Chrzanowska https://www.linkedin.com/in/nat-chrzanowska/ __________________________________________ More about Appsilon: ► https://www.appsilon.com/ 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 __________________________________________ 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/

    6 min
  3. #008 Machine Learning Modeling in Neuroscience Clinical Trials Design

    MAY 22

    #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/ Jing Dai https://www.linkedin.com/in/jingdai1009/  __________________________________________ More about Appsilon: ► https://www.appsilon.com/ 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  __________________________________________ 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/

    34 min
  4. #007 How Open Source and Community Efforts Drive R-Based FDA Submissions

    MAY 8

    #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 submissionsHow {admiral} package for ADaM datasets was one of the triggers for widespread open source adoption in pharmaWhy R is a dominant language in pharmaWhat are the next milestones to modernize outdated regulatory standardsWebinar about GSK's R Journey: From Pilot Projects to Enterprise Adoption: https://www.youtube.com/watch?v=xDrt6txplek Admiral package: https://pharmaverse.github.io/admiral/ __________________________________________ More about Appsilon: ► https://www.appsilon.com/ 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  __________________________________________ 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/

    35 min
  5. #3 Pharma Brief: FDA's Animal Testing Phase-Out, AI in Clinical Development, and Open-Source News

    MAY 7

    #3 Pharma Brief: FDA's Animal Testing Phase-Out, AI in Clinical Development, and Open-Source News

    #datascience #dataanalysis #technology #pharmabrief #clinicaltrials #technologyinpharma #pharma #pharmanews Pharma Brief is back with its third edition, packed with essential industry insights and the latest developments in pharma and biotech. This issue covers the FDA’s plan to phase out animal testing for monoclonal antibodies in favor of AI models and NAMs, insights from Stanford’s AI Index 2025 and McKinsey’s analysis of AI in clinical development, plus new tools like CDISC Dataset Generator, scMultiSim, open-source releases from Novo Nordisk and Genentech and more! You can follow Pharma Brief on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/ And now it’s available in audio on all your favorite podcasting platforms.  Links from the episode: FDA’s New Plan for Phasing Out Animal Testing: https://www.fda.gov/news-events/press-announcements/fda-announces-plan-phase-out-animal-testing-requirement-monoclonal-antibodies-and-other-drugsStanford’s AI Index Report 2025: https://hai-production.s3.amazonaws.com/files/hai_ai_index_report_2025.pdf Summary & takeaways: https://hai.stanford.edu/ai-index/2025-ai-index-reportMcKinsey & Company’s article on clinical development with AI & ML: https://www.mckinsey.com/industries/life-sciences/our-insights/unlocking-peak-operational-performance-in-clinical-development-with-artificial-intelligenceCDISC Dataset Generator for Synthetic Data: https://cdiscdataset.com/scMultiSim for Omics Data Simulation: https://www.nature.com/articles/s41592-025-02651-0Revolutionising Participant Safety Monitoring with Advanced Solutions (Risk Based Quality Management PHUSE Working Group): https://phuse.s3.eu-central-1.amazonaws.com/Archive/2025/Webinar/Worldwide/Virtual/REC_CF12.mp4 Slides: https://phuse.s3.eu-central-1.amazonaws.com/Advance/Community+Forums+/Revolutionizing+Participant+Safety+Monitoring+with+Advanced+Solutions.pdf Clinical Data Analysis: Open Source in Pharma (Free eBook): https://hubs.li/Q03kf2Pk0FDA Pilots Session (ShinyGatherings): https://youtu.be/zZMGFq57wnEOpen-Source packages: Novo Nordisk’s {connector} Package: https://novonordisk-opensource.github.io/connector/Genentech’s BRAID Foundation Models: https://github.com/Genentech/BRAIDbslib v0.9.0 is on CRAN: https://rstudio.github.io/bslib/news/index.html?_gl=1*125lu4v*_ga*NzczNzkyMTAxLjE3Mzc1NTYwMzA.*_ga_8QJS108GF1*MTc0NTkzMzIzMy4xLjAuMTc0NTkzMzIzOC4wLjAuMA..*_ga_2C0WZ1JHG0*MTc0NTkzMzIzMy45LjAuMTc0NTkzMzIzOC4wLjAuMA..#bslib-090Chores package: https://simonpcouch.github.io/chores/ Upcoming Events: Domino RevX Life Science Edition | 20 May 2025 | Philadelphia (PA), United StatesPHUSE Computational Science Symposium 2025 | 20-21 May 2025 | Utrecht, NetherlandsShinyGatherings x Pharmaverse: Presenting aNCA: From Idea to Clinical Impact | 27 May 2025 | VirtualPharmaSUG US Conference | 1-4 June 2025 | San Diego (CA), United StatesVeeva Summit | 4-5 June 2025 | Madrid, SpainPSI 2025 | 8-11 June 2025 | London, United KingdomPHUSE Single Day Event | 11 June 2025 | Boston (MA), United StatesSubscribe on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/  Nat Chrzanowska  https://www.linkedin.com/in/nat-chrzanowska/ __________________________________________ More about Appsilon: ► https://www.appsilon.com/ 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  __________________________________________ 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/

    6 min
  6. #006 Inside Novo Nordisk’s Path to Open Source for the Pharma and Beyond

    APR 24

    #006 Inside Novo Nordisk’s Path to Open Source for the Pharma and Beyond

    Ari Siggaard Knoph from Novo Nordisk shares how the company transitioned from SAS to R for FDA submissions. From early Shiny apps to full-scale open-source workflows, learn how this shift accelerated innovation, attracted top talent, and redefined clinical programming.  In this episode, you will learn:How Novo Nordisk transitioned from legacy systems to R for regulatory submissionsHow Shiny applications became the catalyst for internal buy-inHow open-source adoption has broadened the company’s talent pool and improved productivityFuture directions in pharma tech__________________________________________ More about Appsilon: ► https://www.appsilon.com/ 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  __________________________________________ or 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/

    32 min
  7. #005 Shiny’s Evolution: From Prototyping Tool to Critical Technology in Pharma

    APR 10

    #005 Shiny’s Evolution: From Prototyping Tool to Critical Technology in Pharma

    #datascience #dataanalysis #technology #clinicaltrials #rshiny #shinyforpython #pharmatech Shiny paved the way for R users to create interactive, production-ready applications without switching stacks. In this episode, Eric Nantz reflects on Shiny’s origins, its "lazy by design" reactivity model, and how the ecosystem matured. We dive into how Shiny for Python expands this power to new audiences, and how Shiny is becoming key to modern clinical trial workflows. Eric shares real-world examples, user reactions, and the future of interactive data science. In this episode, you will learn:How Shiny became a game changer for people working with RHow the framework evolved from a simple prototyping tool to a critical asset in life sciencesHow open source is surpassing proprietary softwareThe future of Shiny in drug developmentLinks for the episode:R-Podcast Episode 18 Interview with Joe Cheng https://r-podcast.org/018-interviews-with-the-rstudio-team/ Joe Cheng - The Past and Future of Shiny (rstudio::conf 2022 keynote) https://www.youtube.com/watch?v=HpqLXB_TnpI echarts4r - Interactive visualizations for R via Apache ECharts  https://echarts4r.john-coene.com reactable -Interactive data tables  https://glin.github.io/reactable/ htmlwidgets Gallery https://gallery.htmlwidgets.org/ renv - Project environments for R  https://rstudio.github.io/renv/articles/renv.html  rix - Reproducible data science environments for R with Nix https://docs.ropensci.org/rix/ R Weekly https://rweekly.org R Weekly Highlights podcast https://serve.podhome.fm/r-weekly-highlights Shiny Developer Series https://shinydevseries.com__________________________________________ More about Appsilon: ► https://www.appsilon.com/ 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 _________________________________________ 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/

    36 min
  8. #2 Pharma Brief: AI’s Impact on Clinical Trials, Must-See Open Source Tools, and Upcoming Pharma Events

    APR 2

    #2 Pharma Brief: AI’s Impact on Clinical Trials, Must-See Open Source Tools, and Upcoming Pharma Events

    Pharma Brief is back with the latest edition, packed with valuable insights and upcoming events you don’t want to miss. This month, we’re exploring AI’s impact on clinical development (trials could be 30% faster!), along with innovative tools that streamline processes. We’ve also highlighted open-source packages to optimize your workflows. You can follow Pharma Brief on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/ And now it’s available in audio on all your favorite podcasting platforms. Links from the episode:NVIDIA’s “State of AI in Healthcare and Life Sciences” Report: https://blogs.nvidia.com/blog/ai-healthcare-life-sciences-survey-2025/McKinsey & Company’s “Faster, Smarter Trials: Modernizing Biopharma’s R&D IT Applications”: https://www.mckinsey.com/industries/life-sciences/our-insights/faster-smarter-trials-modernizing-biopharmas-r-and-d-it-applicationsNovoScribe by Novo Nordisk: https://www.mongodb.com/solutions/customer-case-studies/novo-nordisk'Not a cost-cutting exercise': Novo Nordisk Chief Scientific Officer Marcus Schindler explains rationale behind pharma's R&D shake-up: https://www.fiercebiotech.com/biotech/not-cost-cutting-exercise-novo-nordisk-reshapes-rd-setupNovartis joins the Pharmaverse Council: https://pharmaverse.github.io/blog/posts/2025-03-14_welcoming__.../welcoming__novartis_to_the__pharmaverse__council!.htmlJohnson & Johnson's Open Source Journey with R in Clinical Trials | Webinar | Posit https://www.youtube.com/live/_bqeYh2kNgYWhy Clinical Trials Fail | Where Technology Meets Science Podcast | Appsilon https://youtu.be/UXfUUA1vo4IOpen-Source packages: mall: https://mlverse.github.io/mall/querychat: https://github.com/posit-dev/querychat multideploy: https://r-pkg.thecoatlessprofessor.com/multideploy/chatlas: https://posit.co/blog/announcing-chatlas/ nipals: https://github.com/johnsonandjohnson/open_nipals Events: Real World Data Spring Event 2025  |  9–10 April 2025  |  Virtual ShinyConf 2025: Life Sciences/Pharma track  |  9-11 April, 2025  |  Virtual PHUSE Risk Based Quality Management Working Group Webinar “Revolutionising Participant Safety Monitoring with Advanced Solutions”  |  23 April, 2025  |   Virtual Shiny Gathering: FDA Pilots: Key Insights, Lessons Learned, and What’s Next for 2025  |  29 April, 2025  |   Virtual PHUSE Single Day Event  |   2 May, 2025  |   Yerevan, Armenia PHUSE Single Day Event   |   9 May, 2025  |   Denver (CO), United States PHUSE Single Day Event   |    9 May, 2025  |   Beijing, China Open Call for Papers: R/Medicine 2025 https://rconsortium.github.io/RMedicine_website/Abstracts.html Deadline: Friday, 11 AprilPHUSE EU https://www.phuse-events.org/attend/frontend/reg/tOtherPage.csp?pageID=47086&ef_sel_menu=4278&eventID=74 Deadline: Friday, 25 AprilSubscribe on LinkedIn: https://www.linkedin.com/newsletters/pharma-brief-7300489155535380480/  Nat Chrzanowska https://www.linkedin.com/in/nat-chrzanowska/ _________________________________________ More about Appsilon: ► https://www.appsilon.com 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  __________________________________________ 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/

    6 min
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Where Science Meets Technology by Appsilon is a series of interviews and discussions focused on how technology can accelerate data science processes, particularly within life sciences and biopharmaceutical companies. Each episode will explore various aspects of innovation and its potential to address challenges where traditional methods may fall short. We will feature internal experts from our delivery teams, along with clients and partners as guest speakers, providing valuable insights into the intersection of science and technology. The podcast is brought to you by Appsilon. Appsilon empowers Fortune 500 companies to leverage open-source technology for faster, data-driven decision-making in regulated environments

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