Yale and Boehringer Ingelheim have partnered to create a Biomedical Data Science Fellowship program for postdoctoral fellows. The program awards postdoctoral researchers a three-year fellowship that includes access to Yale’s robust computational resources, biomedical data repositories, and faculty expertise as well as Boehringer Ingelheim’s corporate labs, scientists, and executives.
“The collaboration with Boehringer Ingelheim is designed to create a world-class data
science program that will drive development of novel methods and tools to analyze and interpret the many large and complex bio-medical datasets that have been generated in recent years,” said Hongyu Zhao, PhD, Ira V. Hiscock Professor of Biostatistics and a Yale professor of genetics and of statistics and data science. Zhao is the program’s principal investigator.
With the program now in its second year, four new postdoctoral fellows—Rong Li, Dylan Duchen, Chuanpeng Dong, and Shubham Tripathi—began their work in September.
Li plans to analyze tumor, gene, and protein data in order to identify more specific subtypes of cancers for personalized patient treatment.
Duchen will use graphs to model immune cell profiles in individuals and identify which biological factors lead to better efficacy of treatments in patients.
Dong will use machine learning models to predict which paralog pairs (gene copies with different functions) could be effective in cancer immunotherapy.
Tripathi will create a mathematical model to determine which genes and cells directly affect immune responses, with the ultimate goal of being able to modulate this response.
“These projects rely on data from both Yale and Boehringer Ingelheim, and the more data we share, the more we progress,’’ said Xinxin “Katie” Zhu, MD, executive director of the Yale Center for Biomedical Data Science and manager of the fellowship program. “You cannot look at yourself as industry or academia. Boehringer Ingelheim and Yale share the same goal of talent development and retention and through this [partnership], we find the best of the best in the candidate and keep growing them.”
Dhananjay Bhaskar, a 2021 program fellow, said the program reshaped how he approaches research. “The scientific process is iterative and nonlinear, and the partnership with BI [Boehringer Ingelheim] has given me insight into the unique challenges and opportunities in conducting research for industry. It has been a wonderful learning experience that has broadened my perspective on how computational biology research can be applied to product development, cascading down to improved clinical outcomes and benefits to society,” he said.
The purpose of the fellowships goes far beyond advanced training in biomedical data science. “Of course, we’re going to sharpen their [technical] skills, but that’s not the only thing this fellowship is for,” Zhu said. “We would like to prepare them to be the next generation of leaders in the field and to have them serve as a bridge between universities and industry.”
Zhao considers the partnership as only the beginning of what will eventually be many future collaborations. “I think it’s an anchor to really start bringing people together,” he said. “There are a lot of things that can be derived from this.” In the past year, Yale and Boehringer Ingelheim have already partnered on a project sponsored independently of the fellowship program.
“This is a win-win both for Yale and for BI, where the partnership is a matchmaker, a platform for people to get to know each other,” said Zhu. “And we don’t want to stop there … we want to be the bridge. We want to be the liaison. We want to build a community.”