Novo Nordisk and UC Berkeley launch new joint initiative for causal inference
Joint Initiative will have hubs in Copenhagen and Berkeley
- 3 min. read ▪ Published
A 20 million DKK ($3.2 million) research gift from leading global healthcare company Novo Nordisk, headquartered in Denmark, will support an international joint initiative to advance work at the intersection of statistical methods, machine learning, and causal inference methods. Causal inference is an area of scientific inquiry that uses formal mathematical frameworks to move from studying statistical associations to studying causal and effect relationships.
The joint initiative will have two hubs: one at the University of Copenhagen and one at UC Berkeley. The UC Berkeley hub will be administered by the School of Public Health’s Center for Targeted Learning under the direction of Dr. Maya Petersen, the chair of Berkeley Public Health’s Division of Biostatistics, and Dr. Mark van der Laan, Jiann-Piang Hsu and Karl E. Peace Endowed Chair in Biostatistics.
“We are extremely excited about the opportunities this gift presents to develop new methods and improve best practices in the analysis of both randomized controlled drug trials and registry and electronic health record data,” said Petersen. “Methodologic advances in targeted learning provide an opportunity to improve the power, precision, and rigor of trial analyses, and allow us to address novel questions such as how best to personalize treatments, and the mechanisms by which drugs achieve their effects. We look forward to partnering with Novo Nordisk and the University of Copenhagen to translate these methodological advances into meaningful improvements in patient care.”
The center will implement and disseminate methods for exploiting vast, new health datasets using state-of-the art advances in machine learning, causal inference, and statistical theory, and build industry-wide consensus around best practices for answering pressing health questions in the modern methodological and data ecosystem. Determining causality is essential for the expensive and time-consuming generation of data from randomized control trials (RCTs) during the development of new drugs.
The Center is already actively developing open-source software for causal analyses of observational and randomized data, including interfaces with scalable machine learning for big data.
“We see tremendous potential in leveraging learnings from the enormous amount of clinical trial data and real-world data we have access to, and we are looking for new ways of accessing and analyzing data,” said Martin Holst Lange, senior vice president of Global Development for Novo Nordisk. “By collaborating with a world-leading partner like UC Berkeley, we enhance our data science capabilities and knowledge base, further enabling us to set the future direction for data science in Novo Nordisk for the benefit of patients.”
Center principals will also develop and teach workshops and short courses as part of the initiative. A free inaugural three-day webinar featuring experts from UC Berkeley, Copenhagen University, and Novo Nordisk offering presentations on utilizing causal inference and targeted learning methods to answer pressing health questions in the modern methodological and data ecosystem will take place Oct. 26, 28, and 30. Visit UC Berkeley’s website for more information.
Other center sponsors include the Inter-American Development Bank, the Bill & Melinda Gates Foundation, Accenture, the National Institutes of Health, the San Francisco Department Public Health, and the U.S. Food and Drug Administration’s Sentinel Initiative.