Data Science: Bridging The Gap Between Controlled Experiment And Real-World Data?

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 artificial intelligence (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.

This 2018 survey report from Cytel based on data from over 140 industry respondents reveals how the evolution of data science could lead to a revolution of real-world data being accepted as robust evidence for regulatory approval of new drugs. The report shares new insights on:

• The main goals and current sources for data science approaches within the respondents’ organizations
• The key opportunities that data science presents for the industry
• The key barriers and challenges faced by the industry to maximize the potential for healthcare