From An Expert Statistician's Tool Kit: R Vs Python Programming Language

By VP Prasanth, Associate Director, Business Solutions

In recent years, leaders in the pharmaceutical industry have relied on data science to guide their decision making around vital drug development objectives. Data science experts have multiple layers of responsibilities that include exploring and evaluating data; model development and validation; examining research patterns and generating data insights. And, after all of that, they have to effectively communicate the results in a meaningful way that impacts decisions. Requiring key expertise, functional service providers (FSPs) can play a critical role in guiding and advancing these responsibilities.

In clinical research, sponsors and some service partners typically use legacy systems like SAS to analyze data, input results and generate insights from it. It’s a conventional method to data analysis. However, being a paid software, SAS does not allow for open-source algorithms. In the last decade, it has gradually become apparent to industry stakeholders that taking advantage of historical data has benefits worthy of consideration for sponsors.