NEW HAVEN, CONN. & INGELHEIM, GERMANY-- May 11, 2021 -- Yale University, in partnership with Boehringer Ingelheim, today announced the launch of a Biomedical Data Science Fellowship program designed to attract and support some of the brightest and most innovative minds in data science from around the world.

Post-doctoral researchers awarded a three-year fellowship will have access to Yale’s robust computational resources, biomedical data repositories and faculty expertise. In addition, they will benefit from access to Boehringer Ingelheim’s corporate labs, scientists and executives. Applicants are invited to submit research proposals for consideration by June 15. If approved for a fellowship, they will be jointly mentored throughout the research process by industry experts and scientists from Boehringer Ingelheim — one of the world’s leading pharmaceutical companies — as well as Yale’s world-class researchers and scholars. Fellowship training begins Sept. 1.

“This collaboration with Boehringer Ingelheim creates a world-class data science fellowship program that will drive development of novel methods and tools to analyze and interpret the many large and complex biomedical datasets that have been created in recent years,” said Yale School of Public Health Professor of Biostatistics, Genetics, Statistics, and Data Science Hongyu Zhao, PhD, principal investigator for the project.

The program will be based at the Yale Center for Biomedical Data Science (CBDS) in New Haven, Connecticut. The center is an essential part of a growing data science hub at Yale University, which has identified integrated data science as one of its primary investment areas over the next decade. CBDS is located within Yale School of Medicine and currently supports more than 100 faculty members and researchers representing such disciplines as bioinformatics, modeling, statistics, computer science, artificial intelligence, mathematics, biology, precision medicine and public health.

“In partnering with a top-tier academic and research institution like Yale, we aim to recruit and train a new generation of highly skilled data scientists to help us accelerate development of novel treatments and therapies for human disease and improve health outcomes for our patients,” said Jan Nygaard Jensen, PhD, Global Head of Computational Biology and Digital Sciences at Boehringer Ingelheim.

The partnership reflects a mutual vision between Boehringer Ingelheim and Yale University. It is part of a comprehensive strategic program at Boehringer Ingelheim which will harness the power of data science to transform drug discovery and development. The aim is to catalyze the next breakthrough therapies that change lives by accelerating timelines, improving scientific and clinical success and further elevating patient centricity.

“Boehringer Ingelheim is pleased to build upon our successful relationships with Yale to foster the next generation of scientists and harness the power of data science to bring our vision of making new and better medicines for patients in need,” said Clive R. Wood, PhD, Senior Corporate Senior Vice President, Global Head, Discovery Research, Boehringer Ingelheim. “We believe our shared ambition and outlook will build a world-class data science community to attract outstanding researchers and work to achieve breakthroughs that patients need.”

Initially the program will award as many as three competitive fellowships per year, up to a total of nine over the first five years. In addition to receiving research funding and mentorship, program fellows will be invited to participate in campus and corporate visits, networking events and annual symposia.

A joint selection committee comprising representatives of Yale and Boehringer Ingelheim will set annual data-driven research themes for the program. These themes may include such topics as genomic analysis, biomarkers, data-driven therapeutic research, medical image informatics, precision medicine and translational medicine. The selection committee will consider proposed research projects’ alignment with prioritized themes in judging submissions and post-doctoral applicants.

Yale’s data science ecosystem is supported by a host of cutting-edge research institutions working collaboratively. In addition to CBDS, they include Yale’s Systems Biology Institute, Center for Mendelian Genomics, Center for RNA Science and Medicine, and Center for Medical Informatics. Yale’s biobanks and technology core include: the Yale BioBank GENERATIONS, VA Million Veteran Program, Center for Research Computing, Center for Genomic Health, and Center for Genomic Analysis, which houses the ninth largest genomic library in the world.

Xinxin (Katie) Zhu, MD, PhD, executive director of the Yale Center for Biomedical Data Science, said the fellowship program offers an exciting opportunity for the development of innovative data-driven approaches for different medical conditions that can be translated from the lab to the patient’s bedside. It is an especially opportune time, she said.

“The vast amount of biomedical data being generated today has created a tremendous need for highly skilled data scientists who can use this information to advance care,” said Zhu.

Specialists in biomedical data science and health informatics can identify statistical associations and patterns of disease. They also can develop complex machine learning models and simulations of molecular, cellular and organismic systems to increase the probability of clinical success through precision medicine and other methods.

“This helps clinicians and pharmaceutical companies such as Boehringer Ingelheim identify potential new pathways for treatment and eradication of disease,” Zhu said.