🤖🧬 Where Technology Meets Science

#datascience #dataanalysis #GxP #PharmaTech #SoftwareValidation #FDARegulations #ClinicalTrials #LifeSciences #R #PharmaInnovation #TechInPharma
GxP compliance is shaping the future of pharmaceutical software engineering, yet many companies still struggle with implementation. In this episode, Appsilon’s co-founder, Paweł Przytuła, unpacks GxP best practices, software validation, and how R-based submissions are gaining traction with regulatory bodies like the FDA. He also shares industry insights from Roche, Novo Nordisk, and GSK, explores emerging trends like AI in validation, and discusses how pharma companies can leverage open-source tools while ensuring compliance. Don’t miss this deep dive into the intersection of software and life sciences!
In this episode, you will learn:
What is GxP in software engineering and why it’s critical for regulatory approval in life sciences
What GxP compliance means for pharma software
How leading pharma companies approach R-based submissions
What are the risks of ignoring GxP in software development
How AI, statistical computing environments (SCEs), and open-source innovations are transforming software validation in pharma
How to build a strong GxP-ready data science team  

Guest: Paweł Przytuła https://www.linkedin.com/in/pawelprzytula
Your host: Nat Chrzanowska https://www.linkedin.com/in/nat-chrzanowska/ 
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Mentioned resources:
Paper on R-based Submissions to the FDA: https://pharmasug.org/proceedings/2024/SS/PharmaSUG-2024-SS-344.pdf
Presentation on Novo Nordisk's Journey towards open source: https://phuse.s3.eu-central-1.amazonaws.com/Archive/2023/Connect/EU/Birmingham/PRE_TT12.pdf
GSK's R Journey to Open Source: https://www.youtube.com/watch?v=xDrt6txplek&ab_channel=PositPBC
Roche's End-to-End R Journey to Submission: https://www.youtube.com/watch?v=BlJNILSoZlM&ab_channel=PositPBC 
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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 
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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/ 

In this episode of Technology Meets Science, we welcome David Meza, Head of Analytics at NASA’s Human Capital Office. David shares how data science and AI are transforming talent management at NASA, ensuring the right individuals are matched with critical missions. From knowledge graphs to generative AI, he explains how NASA is leveraging technology to optimize workforce planning, upskilling, and recruitment. Tune in for insights on AI-driven talent analytics, the challenges of data accessibility, and what it takes to land a career at NASA.

In this episode, you will learn:

• How NASA uses data science, analytics, knowledge graphs, and AI to align employees' skills and competencies with space mission roles
• How NASA tackles cleaning and structuring workforce data
• How AI models help to assess employee skills, identify gaps, and recommend training programs to upskill the workforce.
• How open-source tech stack, including Python, R, SQL, Databricks, and knowledge graphs enable smarter decision-making
• What it takes to work at NASA, from passion-driven careers to the importance of continuous learning

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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/ 

Together with Eric Genevois-Marlin, former Head of Data Sciences in R&D and Biostatistics at Sanofi, we uncover the reasons behind clinical trial failures. Drawing from his 20+ years of experience leading science and technology teams in bringing new drugs to market, we'll examine real-world examples and extract lessons from both successes and failures.In this episode, you will learn:

• What the risks are in clinical trials
• The main causes of clinical trial failures
• Examples of success stories
• Lessons learned from clinical trials that go wrong
• How to minimize the risks of failure

__________________________________________
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/

"Where Technology Meets Science" is a podcast series diving into the intersection of technology and life sciences. We bring together industry experts, innovators, and thought leaders to explore how advanced technologies are reshaping data science processes in biotechnology, biopharma, environmental sciences, genetics, and similar fields. Together with experts from companies like Roche, Novartis, NASA, and J&J, we uncover solutions that address complex challenges, accelerate research, and push beyond traditional scientific methods, offering listeners insights into the evolving landscape of scientific discovery.