The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.

Role of Prediction and Causal Inference in Clinical Research

November 17, 2020

 

As a part of Cytel’s "New Horizons Webinar Series", Alind Gupta, Senior Data Scientist, presents case studies from his research on applying machine learning for predictive analysis and evidence generation.

The biopharmaceutical and healthcare industries now collect more data than ever before due to advances in the variety of information sources combined with the ability to store vast quantities of diverse data. Sophisticated machine learning (ML) and AI techniques allow us to access and analyze any combination of a multitude of data sources. The way that traditional controlled sources are viewed is being adapted in light of new evidence that emerges from real-world data. In his presentation, Alind introduces us to the concept of ML and Causal Inference and discusses case studies from randomized clinical trials and real-world data.

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Head to Head Comparisons Using Real World Data – Design and Data Considerations from Cardiovascular Pilot Investigation

August 5, 2020

Cytel is conducting two pilot projects on head-to-head comparisons using real world data. These projects in oncology and cardiovascular will occur in real time and will take place across our latest webinar series on the topic. The aim of this series is to introduce our audience to head to head to comparison using Real World Data (RWD) while focusing on practical application and results from the pilot projects.

The second webinar from this series was held on July 28, 2020 and outlines the design of the cardiovascular pilot investigation. None of the existing randomized trials of recently developed second-line antihyperglycemic agents can provide adequate information on their comparative effectiveness and safety regarding cardiovascular outcomes. Conducting Target Trials to get information of interest would be costly, difficult to perform, and would take many years to complete. As a result, we need to use observational databases to emulate it. This blog provides a brief on the design of the cardiovascular pilot project. Our team of experts also discussed the data requirements and the data source to be used in the pilot investigation, with the primary challenge focusing on how to assess if data are sufficient for the purposes of trial emulation. Continue reading the blog for a summary of the webinar.

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