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Drug Discovery

What Are Clinical Trials and How to Solve Its Biggest Challenges

Steve Galen May 11, 2022 460


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Steve Galen has been involved in clinical trials for more than 27 years now, in various high-level positions. In this podcast episode, he will explain the different stages of the clinical trials and point out the most severe deficiencies in the industry and how to overcome there. 

By listening to this episode of watching it, you will learn about:

  • What is a clinical trial, and what’s the main goal?
  • What are the questions asked in clinical trials protocols?
  • What are the parts of a clinical trial? 
  • How are those parts connected to the primary goal?
  • What are the most common challenges with clinical trials nowadays? 
  • How can we make clinical trials more transparent and predictable?
  • What are the goals of VC-funded biotech in early-stage clinical development versus pharma in later-stage clinical development, and how are these goals related to the primary purpose of a clinical trial?

This episode is Sponsored by Dot Compliance, the industry’s first ready to use Quality Management Solution powered by the SalesForce platform. Implementation of a new eQMS has never been quicker nor easier.

Learn More About Dot Compliance


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Steve Galen

Steve has a Ph.D. in Engineering and more than 27 years of experience in Big Pharma and global CROs. He has run the CRO division of a life sciences company and held senior leadership positions in clinical operations, software development, risk-based monitoring, clinical data science, project management, drug development, and pharmaceutical manufacturing, including clinical trial drug supply. Steve has spent the last decade making clinical trial design and execution predictable, efficient, and transparent by applying his knowledge of engineering, manufacturing, clinical operations, math, and software development to large sets of clinical trial data. Steve asserts that a clinical trial is not an AI/ML "black box" but rather a set of characterizable and connected processes that predictably produces data, like a manufacturing line. Steve is keenly aware that ROI matters when designing and running trials. His approach makes it easy to determine ROI before committing to a course of action intended to improve trial performance.

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