Our Story
Who is 4G Clinical?
4G Clinical is a leader in randomization and trial supply management (RTSM) for the global life sciences industry, offering the only fully cloud-based, 100% configurable and flexible solution utilizing natural language processing (NLP) and integrated supply forecasting.
Our expert staff possesses a combination of humility, confidence, curiosity and commitment to getting things done. Most importantly, everyone at 4G Clinical is passionate about our mission of bringing crucial medicines to those who need them, faster™.
Our Team Brings a Deep, Personal Connection to our Mission
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ED TOURTELLOTTE
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DAVID KELLEHER Founder, CEO
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| Why I Do This | Why I Do This | |||
| I was going back into the clinical technology space, and one of my old friends wrote asking, “How many times can you build the same system?” | My reason for launching 4G is very simple. We must do whatever we can to ensure that vital medicines get to those who need them as fast as we safely can. | |||
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4G Gives Back
RTSM Technology
Trial designs have become more complex. The fact that RTSM technology has not kept up with that complexity is preventing us from getting medications to patients faster. 1st - 3rd generation RTSMs have not evolved to support the trials of today and tomorrow.
4G Clinical, the 4th Generation of RTSM, is addressing the design complexity-technology bottleneck in clinical trials.
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100% Configurable and Flexible Solutions Powered by Natural Language Processing (NLP)
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The World's Most Innovative Randomization and Trial
Supply Management
- Accelerate study start-up with rapid build, test and deployment timelines
- Eliminate the need for change orders with 100% configurability
- Enhance data quality with agile technology stacks
- Solve complex forecasting challenges with Prancer RTSM™'s integrated forecasting engine
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The world's first integrated
RTSM and Clinical supply
forecasting solution
- Build, run and verify supply chain models in minutes instead of days
- Gain complete control and full transparency of how inputs affect outputs
- Reduce human error by removing manual processes
- Remove the need for external SMEs to build,
interpret and analyze your supply chain models