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Statistical innovation is vital in the pharmaceutical industry as it drives evidence-based decisions and brings value to patients. However, it requires a delicate balance between invention and commercialization to achieve success. I, together with Mouna Akacha and Kaspar Rufibach – two leaders of statistical innovation groups in big pharma companies,
As a statistician, you’re likely already familiar with SAS and the value it brings to data analysis. But in this ever-evolving world of statistics and data science, relying on your go-to language might not be enough to stay competitive anymore. The open-source language R is gaining traction within the healthcare
In our world of clinical trials and observational studies, missing data based on drop outs or for others reasons leads to a challenge in understanding how well treatments work. Treatment policy estimands help us to understand efficacy based on early treatment decisions. Various approaches, like reference-based imputation and delta adjustment, exist
In any industry, staying competitive and relevant requires a constant focus on innovation and the ability to communicate effectively with customers. In the pharmaceutical industry, this is particularly true as companies race to develop and market new compounds that can improve patient outcomes. In this episode, I share insights into
We statisticians play a significant role in the clinical development of pharmaceutical products and medical devices. Many of us focus on designing and analyzing clinical trials to provide evidence for regulatory approval and Health Technology Assessment (HTA). In these set-up, we often talk rather directly to our external clients –
Interpretable machine learning (IML) is rapidly gaining popularity in the data science community. It offers a new way to build and interpret models that are more transparent and understandable. In this episode, we have the privilege of interviewing Serg Masis. Serg authored the book “Interpretable Machine Learning with Python: Learn
When it comes to clinical trial design, there are many challenges to overcome, including recruitment, protocol design, and data analysis, among others. Fortunately, simulations can provide a solution to some of those challenges. Simulations allow us to test the influence of assumptions, optimize designs, and understand probabilities of success before
In today’s highly competitive work environment, developing leadership skills such as vulnerability and empathy will mean the difference between success and failure. In this podcast episode, Marius and I discuss Brené Brown’s “Dare to Lead”, a book that dives into the importance of vulnerability-based leadership. This episode will explore some of the
The field of statistics is rapidly growing, and statisticians play an important role in providing a competitive advantage to companies. However, finding the right job or candidate for a position can be challenging. That’s where Clivoffective comes in – a collaboration between Clivolution and The Effective Statistician focused on connecting
In the field of statistics, we need specific skills necessary for being successfull. Debarshi Dey, currently the head of the Statistics and Programming and Data Management department at Morphosys, has spent the past 13 years in the pharmaceutical industry. With a PhD in statistics from UC Riverside, Debarshi believes that
We statisticians have always been important for brining new therapies to patients. We design experiments, analyze and interpret data to provide valuable insights that can help make informed decisions. However, the value of our work increases if we’re able to lead others. But becoming an inspirational statistician requires more than
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