For pharmaceutical companies analyzing clinical trial data, many insights can be gained by applying Machine Learning techniques to the data.

Utilizing a data lake approach to build a more robust data architecture allows for flexible exploration and the ability to apply these advanced Data Science and Machine Learning procedures.

In this recorded webcast, Thorogood consultants Tim Tague, Marina Tullio and Fernando Takeshi share considerations to make when implementing this architecture, benefits and challenges that come with using Machine Learning to analyze clinical trial data, and various use-cases. Through this complete end-to-end view, from designing the architecture to the analysis, our webcast provides a holistic view of how to unleash the full potential of advanced clinical data analysis.