International powerhouse for causal inference aimed at answering pressing statistical questions using both randomized control and observational studies.
CTML members involved: Maya Petersen M.D. Ph.D. and Mark van der Laan Ph.D.
In collaboration with Novo Nordisk and Copenhagen University, we aim to create an international powerhouse for causal inference aimed at answering pressing statistical questions using both Randomized Control and Observational Studies.
The Causal Targeted Learning Center works on developing, implementing and disseminating methods for exploiting vast, new health datasets using state-of-the art advances in machine learning, causal inference, and statistical theory, and to build industry-wide consensus around best practices for answering pressing health questions in the modern methodological and data ecosystem. The Center is actively developing open-source software for causal analyses of observational and randomized data, including general platforms (e.g. tlverse) and interface with scalable machine learning for big data (e.g. collaboration with H20.ai), as well as developing and teaching workshops and short courses. It is essential for drug development to gain an understanding of how, and when, it is possible to draw causal conclusions without protection from randomization to genuinely support the expensive and time-consuming generation of data from randomized control trials (RCTs). Development of elaborate statistical techniques that can replace randomization and allow for causal conclusions can support development programs by:
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reducing the cost of required RCTs by integrating clinical trial data with observational data and thereby boosting the scientific value;
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producing valid insights based on post-randomization events;
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supporting the evidence generation beyond RCTs and thereby met new requirements from regulatory and re-imbursement authorities.
More on Novo Nordisk
"We are a leading global healthcare company, founded in 1923 and headquartered in Denmark. Our purpose is to drive change to defeat diabetes and other serious chronic diseases such as obesity and rare blood and endocrine disorders. We do so by pioneering scientific breakthroughs, expanding access to our medicines and working to prevent and ultimately cure disease."