The Mount Sinai Health System and the Hasso Plattner Institute (HPI), a leading data science research and educational institution in Germany, have formed an affiliation that will combine their expertise in health care delivery, biomedical and digital engineering, and artificial intelligence. The aim is to develop digital health tools with real-time predictive and preventive capabilities that empower patients and health care providers and improve health outcomes.

Erwin P. Bottinger, MD, left, and Joel Dudley, PhD, are co-directors of the new Hasso Plattner Institute for Digital Health at Mount Sinai.

The newly formed Hasso Plattner Institute for Digital Health at Mount Sinai will be led by Joel Dudley, PhD, Executive Vice President for Precision Health, Mount Sinai Health System, Mount Sinai Professor in Biomedical Data Science, and Director of the Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai; and Erwin P. Bottinger, MD, Professor of Digital Health-Personalized Medicine, Hasso Plattner Institute, University of Potsdam, Germany, and Head of HPI’s Digital Health Center. A $15 million gift from the Hasso Plattner Foundation will establish the new Institute, which was announced in March at the Icahn School of Medicine.

“This endeavor will usher in a new era of digital health at Mount Sinai that advances the field of precision medicine,” says Dennis S. Charney, MD, Anne and Joel Ehrenkranz Dean, Icahn School of Medicine at Mount Sinai, and President for Academic Affairs, Mount Sinai Health System. “By leveraging our shared knowledge and academic excellence, Mount Sinai and HPI are positioned to find solutions that will revolutionize health care and science, and improve health nationally and globally.”

The Hasso Plattner Institute for Digital Health at Mount Sinai joins more than 20 institutes launched at the Icahn School of Medicine. Its goals include building a digital health population of engaged participants to collect comprehensive and longitudinal health data from wearable devices, genetic sequencing, and electronic health records; creating a cloud-based health data platform for research and care using machine learning and artificial intelligence; and researching and testing prototype digital health solutions for patients, providers, and health systems. Mount Sinai’s expertise in genomics, big data, supercomputing, and bioinformatics—along with a large and diverse patient population and an ability to translate from the lab directly to the clinic—provides a foundation for the Institute.

For example, the Institute for Next Generation Healthcare (INGH), under the leadership of Dr. Dudley, has developed a translational biomedical research model using advances in clinical medicine, digital health, and artificial intelligence, and INGH’s Lab 100 is leveraging data and technology to redesign the way health is measured and health care is delivered. In another innovative effort, the BioMe™ BioBank Program, housed at The Charles Bronfman Institute for Personalized Medicine at Mount Sinai, is enabling researchers to conduct genetic, epidemiologic, molecular, and genomic studies on large collections of research specimens linked with electronic health records. Until 2015, Dr. Bottinger was Professor of Medicine (Nephrology), and Pharmacological Sciences at the Icahn School of Medicine, and he helped lay the groundwork for the BioBank Program and The Institute for Personalized Medicine.

“Investigators at the Icahn School of Medicine at Mount Sinai and the Hasso Plattner Institute have been publishing groundbreaking work in the areas of genome diagnostics, precision medicine, digital health, biomedical data science, artificial intelligence, and information technology,” says Dr. Dudley. “We believe the new Institute will help turn the promise of digital health into reality at the front lines of next generation health care.”

Dr. Bottinger says, “We know we can save lives, prevent disease, and improve the health of patients with artificial intelligence in real-time analysis of health data from electronic health records, genetic information, and mobile sensor technologies.”

Benjamin Greenbaum, PhD

The quality, not quantity, of tumor neoantigens may best predict a patient’s response to cancer immunotherapy and his or her chance of long-term survival. That finding was based on two groundbreaking studies co-authored by Benjamin Greenbaum, PhD, Assistant Professor, Medicine (Hematology and Medical Oncology), and Pathology, Icahn School of Medicine at Mount Sinai. Now, it is being further explored by Dr. Greenbaum and Vinod Balachandran, MD, Memorial Sloan Kettering Cancer Center, through a Stand Up to Cancer Convergence 2.0 Grant and funding from the Lustgarten Foundation.

Their goal is to understand the underpinnings of pancreatic cancer survivorship, and their team is one of seven research groups that comprise Stand Up to Cancer’s broad $11 million initiative that was announced in January 2018. Neoantigens, or peptides found on the surface of cancer cells, are considered promising targets for cancer immunotherapy.

“Previous research has shown that T cell immunity is linked to exceptional outcomes for the few long-term survivors of pancreatic cancer, but it wasn’t clear if neoantigens played a role,” says Dr. Greenbaum. “Our newest research shows there are particular neoantigens that seem to be driving this long-term response in patients with pancreatic cancer, and further suggests that targeting those neoantigens might be a viable therapeutic strategy.”

According to Dr. Greenbaum, who was trained as a physicist and quantitative biologist, “One of the most exciting aspects of our work is collaborating with academic teams that can combine the tools and knowledge from diverse fields like theoretical physics, structural biology, mathematics, computer science, and translational genomics. We never lose sight of the fact that our combined efforts could one day result in clinical breakthroughs that benefit countless numbers of people.”

Earlier research formed the basis of the team’s efforts. In the first of two back-to-back studies published in Nature (November 2017), researchers described a mathematical model they developed—the first of its kind—to predict how a cancer patient would benefit from certain immunotherapies. Dr. Greenbaum was the senior author on this work with first author Marta Luksza, PhD, Assistant Professor of Oncological Sciences, Icahn School of Medicine at Mount Sinai.

By capturing aspects of a tumor’s evolution and ways in which it interacted with the underlying immune system, the new model appeared to offer an approach beyond previous biomarkers. Going forward, it also has the potential to uncover new therapeutic targets within the immune system, and help in the design of vaccines for patients who do not respond to immunotherapy.

The second study, whose first author was Dr. Balachandran, applied the modeling framework in order to better understand immune response in patients with pancreatic cancer and, more specifically, the unique role of neoantigens.

As part of the broad initiative, the Mount Sinai researchers are focused on better understanding what makes a neoantigen a good immune target, and the role of the microbiome in neoantigen recognition. By advancing the core science behind developing a vaccine for pancreatic cancer, the research could eventually improve treatment prospects for patients with this deadly form of the disease.

As they investigate the immune system’s response to cancers, the Convergence 2.0 team will be encouraged to draw upon the knowledge of Microsoft Research experts in machine learning and artificial intelligence. In addition to Dr. Luksza, the research team includes Nina Bhardwaj, MD, PhD, from the Icahn School of Medicine at Mount Sinai; and Eileen M. O’Reilly, MD; Taha Merghoub, PhD; and Jedd D. Wolchok, MD, PhD, from Memorial Sloan Kettering Cancer Center.