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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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
#008 Machine Learning Modeling in Neuroscience Clinical Trials Design
🤖🧬 Where Technology Meets Science
34 minutes
5 months ago
#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.
Appsilon empowers pharmaceutical and life sciences companies to leverage open-source technology for faster, data-driven decision-making in regulated environments.
For more insights about how technology helps scientists push the boundaries of data analysis and reporting check out our blog: ► http://appsilon.com/blog
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
