Cytel Blog

In 2018, Cytel ran a qualitative survey among biostatisticians and programmers on trends in data science and perceptions about the goals, barriers and future of the field in the biopharma and life science industry.  Our analysis and report revealed a range of insights from the respondents including :

Lack of shared understanding of what data science represents with less than 1 in 7 of all respondents suggesting a definition of data science.
Clear trend of investment in data science across organizational types with three-quarters of all respondents saying their organizations had a dedicated data science department.

An opportunity for improved clinical trial design by using data science techniques was recognized by the majority of respondents. In addition, respondents across all functions perceive the key opportunity for data science to be in maximizing the value of real-world data. 

In a recently published discussion on The Effective Statistician podcast ( a weekly podcast produced in association with PSI)  Ursula Garczarek, Associate Director Strategic Consulting at Cytel sat down with hosts Alexander Schacht and Benjamin Piske to discuss where the biopharma and life science industries are headed with the application of data science.

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. A recent Deloitte survey (1) found that 90 percent of biopharma companies are making significant investments in
real-world evidence capabilities to drive drug development and meet regulatory requirements.

Real-world evidence (RWE) has historically been used for post-marketing endorsement and in pricing and reimbursement negotiations. But could data science offer an opportunity to fundamentally shift this
paradigm, leading to better and more affordable medications being approved on the basis of RWE?

In June 2018, Cytel created and ran a survey asking respondents from our audience about the potential of data science approaches in the sector.  We are now excited to share the insights from the survey* ( designed as a qualitative pulse check) which reveal a powerful potential shift in the current drug development and approval paradigm.  

In this blog, Paul Fardy, Executive Director of Data Management at Cytel shares his thoughts on how the data manager role has evolved. 

There is a consensus in the industry that data on rare diseases is limited, incomplete, and difficult to find or access. Recently we came across the CoRDS patient registry based at Sanford University and learned that the registry is an effective tool used to gather information useful to researchers studying rare diseases.

We sat down with Benjamin Forred, Project Manager, and Austin Letcher, Senior Research Associate at CoRDS to learn more about the registry and hopes for the future.

In this blog we share a case study in which our statistical consulting team helped a client redesign an oncology pragmatic trial to address regulatory agency questions.